Journal Articles

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2021 [ to top ]

Loh, F., Mehling, N., Metzger, F., Hoßfeld, T.: LoRaPlan: A Software to Evaluate Gateway Placement in LoRaWAN. 17th International Conference on Network and Service Management. (2021).

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Nguyen Huu, T., Trung Kien, N., Van Hoa, N., Thu Huong, T., Wamser, F., Hoßfeld, T.: Energy-Aware Service Function Chain Embedding in Edge-Cloud Environments for IoT Applications. IEEE Internet of Things Journal. (2021).

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@article{info3-article-2021-2,
  abstract = {The implementation of IoT applications faces several challenges in practice, such as compliance with QoS requirements, resource constraints and energy consumption. In this context, the joint paradigm for IoT applications can resolve some of the issues arising in pure cloud computing scenarios, such as those related to latency, energy or privacy. Therefore, an environment could be promising for resource and energy-efficient IoT applications that implement VNF bound together into SFC. However, a resource and energy efficient SFC placement requires smart SFC embedding mechanisms in the environment, as several challenges arise, such as IoT service chain modeling and evaluation, the trade-off between resource allocation, energy efficiency and performance, and the resource dynamics. In this article, we address issues in modeling resource and energy utilization for IoT applications in environments. A smart traffic monitoring IP camera system is deployed as a use case for a realistic modeling of a service chain. The system is implemented in our testbed, which is designed and developed specifically to model and investigate the resource and energy utilization of SFC embedding strategies. A resource and energy-aware SFC strategy in the environment for IoT applications is then proposed. Our algorithm is able to cope with dynamic load and resource situations emerging from dynamic SFC requests. The strategy is evaluated systematically in terms of acceptance ratio of SFC requests, resource efficiency and utilization, power consumption, and VNF migrations depending on the offered system load. Results show that our strategy outperforms some existing approaches in terms of resource and energy efficiency, thus it overcomes the relevant challenges from practice and meets the demands of IoT applications.},
  author = {Nguyen Huu, Thanh and Trung Kien, Nguyen and Van Hoa, Ngo and Thu Huong, Truong and Wamser, Florian and Hoßfeld, Tobias},
  journal = {IEEE Internet of Things Journal},
  keywords = {myown sys:hidden:article ecodane},
  month = 3,
  title = {Energy-Aware Service Function Chain Embedding in Edge-Cloud Environments for IoT Applications},
  year = 2021
}

%0 Journal Article
%1 info3-article-2021-2
%A Nguyen Huu, Thanh
%A Trung Kien, Nguyen
%A Van Hoa, Ngo
%A Thu Huong, Truong
%A Wamser, Florian
%A Hoßfeld, Tobias
%D 2021
%J IEEE Internet of Things Journal
%T Energy-Aware Service Function Chain Embedding in Edge-Cloud Environments for IoT Applications
%X The implementation of IoT applications faces several challenges in practice, such as compliance with QoS requirements, resource constraints and energy consumption. In this context, the joint paradigm for IoT applications can resolve some of the issues arising in pure cloud computing scenarios, such as those related to latency, energy or privacy. Therefore, an environment could be promising for resource and energy-efficient IoT applications that implement VNF bound together into SFC. However, a resource and energy efficient SFC placement requires smart SFC embedding mechanisms in the environment, as several challenges arise, such as IoT service chain modeling and evaluation, the trade-off between resource allocation, energy efficiency and performance, and the resource dynamics. In this article, we address issues in modeling resource and energy utilization for IoT applications in environments. A smart traffic monitoring IP camera system is deployed as a use case for a realistic modeling of a service chain. The system is implemented in our testbed, which is designed and developed specifically to model and investigate the resource and energy utilization of SFC embedding strategies. A resource and energy-aware SFC strategy in the environment for IoT applications is then proposed. Our algorithm is able to cope with dynamic load and resource situations emerging from dynamic SFC requests. The strategy is evaluated systematically in terms of acceptance ratio of SFC requests, resource efficiency and utilization, power consumption, and VNF migrations depending on the offered system load. Results show that our strategy outperforms some existing approaches in terms of resource and energy efficiency, thus it overcomes the relevant challenges from practice and meets the demands of IoT applications.

Wehner, N., Seufert, M., Schüler, J., Wassermann, S., Casas, P., Hoßfeld, T.: Improving Web QoE Monitoring for Encrypted Network Traffic through Time Series Modeling. ACM SIGMETRICS Performance Evaluation Review. 48, 37–40 (2021).

[ Abstract ] [ BibTeX ] [ EndNote ]

Tran, H.T., Pham Ngoc, N., Hoßfeld, T., Seufert, M., Thang, T.C.: Cumulative Quality Modeling for HTTP Adaptive Streaming. ACM Transactions on Multimedia Computing, Communications, and Applications. 17, 22 (1–24) (2021).

[ BibTeX ] [ EndNote ]

Seufert, A., Schröder, S., Seufert, M.: Delivering User Experience over Networks: Towards a Quality of Experience Centered Design Cycle for Improved Design of Networked Applications. SN Computer Science. 2, (2021).

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Loh, F., Poignée, F., Wamser, F., Leidinger, F., Hoßfeld, T.: Uplink vs. Downlink: Machine Learning-Based Quality Prediction for HTTP Adaptive Video Streaming. Sensors. 21, 4172 (2021).

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Wamser, F., Seufert, A., Hall, A., Wunderer, S., Hoßfeld, T.: Valid Statements by the Crowd: Statistical Measures for Precision in Crowdsourced Mobile Measurements. Network. 1, 215–232 (2021).

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Hirth, M., Seufert, M., Lange, S., Meixner, M., Tran-Gia, P.: Performance Evaluation of Hybrid Crowdsensing and Fixed Sensor Systems for Event Detection in Urban Environments. Sensors. 21, 5880 (1–19) (2021).

[ Abstract ] [ BibTeX ] [ EndNote ]

@article{info3-article-2021-4,
  abstract = {Crowdsensing offers a cost-effective way to collect large amounts of environmental sensor data. However, the spatial distribution of crowdsensing sensors can hardly be influenced, as the participants carry the sensors, and, additionally, the quality of the crowdsensed data can vary significantly. Hybrid systems that use mobile users in conjunction with fixed sensors might help to overcome these limitations, as such system allow assessing the quality of the submitted crowdsensed data and provide sensor values where no crowdsensing data is available. In this work, we use a simulation study to first analyze a simple crowdsensing system concerning the detection performance of spatial events to highlight the potential and limitations of a pure crowdsourcing system. The results indicate that even if only a small share of inhabitants participates in crowdsensing, events that have locations correlated with the population density can be easily and quickly detected using such a system. On the contrary, events with uniformly randomly distributed locations are much harder to detect using a simple crowdsensing-based approach. A second evaluation shows that hybrid systems improve the detection probability and time. Finally, we illustrate how to compute the minimum number of fixed sensors for given detection time thresholds in our exemplary scenario.},
  author = {Hirth, Matthias and Seufert, Michael and Lange, Stanislav and Meixner, Markus and Tran-Gia, Phuoc},
  journal = {Sensors},
  keywords = {myown sys:hidden:article gbc ucn},
  month = 8,
  number = 17,
  pages = {5880 (1-19)},
  title = {Performance Evaluation of Hybrid Crowdsensing and Fixed Sensor Systems for Event Detection in Urban Environments},
  volume = 21,
  year = 2021
}

2020 [ to top ]

Seufert, M.: Statistical Methods and Models based on Quality of Experience Distributions. Quality and User Experience. 6, (2020).

[ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]

@article{info3-article-2020-7,
  abstract = {Due to biased assumptions on the underlying ordinal rating scale in subjective Quality of Experience (QoE) studies, Mean Opinion Score (MOS)-based evaluations provide results, which are hard to interpret and can be misleading. This paper proposes to consider the full QoE distribution for evaluating, reporting, and modeling QoE results instead of relying on MOS-based metrics derived from results based on ordinal rating scales. The QoE distribution can be represented in a concise way by using the parameters of a multinomial distribution without losing any information about the underlying QoE ratings, and even keeps backward compatibility with previous, biased MOS-based results. Considering QoE results as a realization of a multinomial distribution allows to rely on a well-established theoretical background, which enables meaningful evaluations also for ordinal rating scales. Moreover, QoE models based on QoE distributions keep detailed information from the results of a QoE study of a technical system, and thus, give an unprecedented richness of insights into the end users’ experience with the technical system. In this work, existing and novel statistical methods for QoE distributions are summarized and exemplary evaluations are outlined. Furthermore, using the novel concept of quality steps, simulative and analytical QoE models based on QoE distributions are presented and showcased. The goal is to demonstrate the fundamental advantages of considering QoE distributions over MOS-based evaluations if the underlying rating data is ordinal in nature.},
  author = {Seufert, Michael},
  journal = {Quality and User Experience},
  keywords = {myown sys:hidden:article ucn},
  month = 12,
  number = 1,
  title = {Statistical Methods and Models based on Quality of Experience Distributions},
  volume = 6,
  year = 2020
}

Borchert, K., Seufert, A., Gamboa, E., Hirth, M., Hoßfeld, T.: In vitro vs in vivo: does the study’s interface design influence crowdsourced video QoE?. Quality and User Experience. (2020).

[ Abstract ] [ BibTeX ] [ EndNote ]

@article{info3-article-2020-6,
  abstract = {Evaluating the Quality of Experience (QoE) of video streaming and its influence factors has become paramount for streaming providers, as they want to maintain high satisfaction for their customers. In this context, crowdsourced user studies became a valuable tool to evaluate different factors which can affect the perceived user experience on a large scale. In general, most of these crowdsourcing studies either use, what we refer to, as an in vivo or an in vitro interface design. In vivo design means that the study participant has to rate the QoE of a video that is embedded in an application similar to a real streaming service, e.g., YouTube or Netflix. In vitro design refers to a setting, in which the video stream is separated from a specific service and thus, the video plays on a plain background. Although these interface designs vary widely, the results are often compared and generalized. In this work, we use a crowdsourcing study to investigate the influence of three interface design alternatives, an in vitro and two in vivo designs with different levels of interactiveness, on the perceived video QoE. Contrary to our expectations, the results indicate that there is no significant influence of the study’s interface design in general on the video experience. Furthermore, we found that the in vivo design does not reduce the test takers’ attentiveness. However, we observed that participants who interacted with the test interface reported a higher video QoE than other groups.},
  author = {Borchert, Kathrin and Seufert, Anika and Gamboa, Edwin and Hirth, Matthias and Hoßfeld, Tobias},
  journal = {Quality and User Experience},
  keywords = {myown sys:hidden:article ua-net},
  month = 11,
  title = {In vitro vs in vivo: does the study’s interface design influence crowdsourced video QoE?},
  year = 2020
}

Wassermann, S., Seufert, M., Casas, P., Li, G., Kuang, L.: ViCrypt to the Rescue: Real-time, Machine-Learning-driven Video-QoE Monitoring for Encrypted Streaming Traffic. IEEE Transactions on Network and Service Management. 17, 2007–2023 (2020).

[ Abstract ] [ BibTeX ] [ EndNote ]

@article{info3-article-2020-5,
  abstract = {Video streaming is the killer application of the Internet today. In this paper, we address the problem of real-time, passive Quality-of-Experience (QoE) monitoring of HTTP Adaptive Video Streaming (HAS), from the Internet-Service-Provider (ISP) perspective - i.e., relying exclusively on in-network traffic measurements. Given the wide adoption of end-to-end encryption, we resort to machine-learning (ML) models to estimate multiple key video-QoE indicators (KQIs) from the analysis of the encrypted traffic. We present ViCrypt, an ML-driven monitoring solution able to infer the most important KQIs for HTTP Adaptive Streaming (HAS), namely stalling, initial delay, video resolution, and average video bitrate. ViCrypt performs estimations in real-time, during the playback of an ongoing video-streaming session, with a fine-grained temporal resolution of just one second. For this, it relies on lightweight, stream-like features continuously extracted from the encrypted stream of packets. Empirical evaluations on a large and heterogeneous corpus of YouTube measurements show that ViCrypt can infer the targeted KQIs with high accuracy, enabling large-scale passive video-QoE monitoring and proactive QoE-aware traffic management. Different from the state of the art, and besides real-time operation, ViCrypt is not bound to coarse-grained KQI-classes, providing better and sharper insights than other solutions. Finally, ViCrypt does not require chunk-detection approaches for feature extraction, significantly reducing the complexity of the monitoring approach, and potentially improving on generalization to different HAS protocols used by other video-streaming services such as Netflix and Amazon.},
  author = {Wassermann, Sarah and Seufert, Michael and Casas, Pedro and Li, Gang and Kuang, Li},
  journal = {IEEE Transactions on Network and Service Management},
  keywords = {myown sys:hidden:article ucn},
  month = 12,
  number = 4,
  pages = {2007 - 2023},
  title = {ViCrypt to the Rescue: Real-time, Machine-Learning-driven Video-QoE Monitoring for Encrypted Streaming Traffic},
  volume = 17,
  year = 2020
}

%0 Journal Article
%1 info3-article-2020-5
%A Wassermann, Sarah
%A Seufert, Michael
%A Casas, Pedro
%A Li, Gang
%A Kuang, Li
%D 2020
%J IEEE Transactions on Network and Service Management
%N 4
%P 2007 - 2023
%T ViCrypt to the Rescue: Real-time, Machine-Learning-driven Video-QoE Monitoring for Encrypted Streaming Traffic
%V 17
%X Video streaming is the killer application of the Internet today. In this paper, we address the problem of real-time, passive Quality-of-Experience (QoE) monitoring of HTTP Adaptive Video Streaming (HAS), from the Internet-Service-Provider (ISP) perspective - i.e., relying exclusively on in-network traffic measurements. Given the wide adoption of end-to-end encryption, we resort to machine-learning (ML) models to estimate multiple key video-QoE indicators (KQIs) from the analysis of the encrypted traffic. We present ViCrypt, an ML-driven monitoring solution able to infer the most important KQIs for HTTP Adaptive Streaming (HAS), namely stalling, initial delay, video resolution, and average video bitrate. ViCrypt performs estimations in real-time, during the playback of an ongoing video-streaming session, with a fine-grained temporal resolution of just one second. For this, it relies on lightweight, stream-like features continuously extracted from the encrypted stream of packets. Empirical evaluations on a large and heterogeneous corpus of YouTube measurements show that ViCrypt can infer the targeted KQIs with high accuracy, enabling large-scale passive video-QoE monitoring and proactive QoE-aware traffic management. Different from the state of the art, and besides real-time operation, ViCrypt is not bound to coarse-grained KQI-classes, providing better and sharper insights than other solutions. Finally, ViCrypt does not require chunk-detection approaches for feature extraction, significantly reducing the complexity of the monitoring approach, and potentially improving on generalization to different HAS protocols used by other video-streaming services such as Netflix and Amazon.

Kunz, F., Hirth, M., Schweitzer, T., Linz, C., Goetz, B., Stellzig-Eisenhauer, A., Borchert, K., Böhm, H.: Subjective perception of craniofacial growth asymmetries in patients with deformational plagiocephaly. Springer Clinical Oral Investigations. 24, https://doi.org/10.1007/s00784–020 (2020).

[ BibTeX ] [ EndNote ]

Hoßfeld, T., Heegaard, P.E., Skorin-Kapov, L., Varela, M.: Deriving QoE in systems: from fundamental relationships to a QoE‑based Service‑level Quality Index. Springer Quality and User Experience. 5, https://rdcu.be/b483m (2020).

[ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]

@article{info3-article-2020-2,
  abstract = {With Quality of Experience (QoE) research having made significant advances over the years, service and network providers aim at user-centric evaluation of the services provided in their system. The question arises how to derive QoE in systems. In the context of subjective user studies conducted to derive relationships between influence factors and QoE, user diversity leads to varying distributions of user rating scores for different test conditions. Such models are commonly exploited by providers to derive various QoE metrics in their system, such as expected QoE, or the percentage of users rating above a certain threshold. The question then becomes how to combine (a) user rating distributions obtained from subjective studies, and (b) system parameter distributions, so as to obtain the actual observed QoE distribution in the system? Moreover, how can various QoE metrics of interest in the system be derived? We prove fundamental relationships for the derivation of QoE in systems, thus providing an important link between the QoE community and the systems community. In our numerical examples, we focus mainly on QoE metrics. We furthermore provide a more generalized view on quantifying the quality of systems by defining a QoE-based Service-level Quality Index. This index exploits the fact that quality can be seen as a proxy measure for utility. Following the assumption that not all user sessions should be weighted equally, we aim to provide a generic framework that can be utilized to quantify the overall utility of a service delivered by a system.},
  author = {Hoßfeld, Tobias and Heegaard, Poul E. and Skorin-Kapov, Lea and Varela, Martin},
  journal = {Springer Quality and User Experience},
  keywords = {myown sys:hidden:article dfg-sdn qoe-ia},
  month = 7,
  number = 7,
  pages = {https://rdcu.be/b483m},
  title = {Deriving QoE in systems: from fundamental relationships to a QoE‑based Service‑level Quality Index},
  volume = 5,
  year = 2020
}

Wamser, F., Alay, Özgü, Metzger, F., Valentin, S.: IJNM Special Issue - Editorial - QoE-centric Analysis and Management of Communication Networks. International Journal of Network Management. Special Issue: QoE-centric Analysis and Management of Communication Networks, (2020).

[ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]

@article{info3-article-2020-1,
  abstract = {The heterogeneity and variability of Internet applications has increased considerably in recent years. Applications such as video streaming are responsible for a large part of data traffic on the Internet. Internet telephony and video conferencing systems have become part of our daily lives. At the same time, the Internet of Things is striving to exceed previous expectations regarding the number of devices. Furthermore, the proliferation of video games, virtual reality applications, and 360° video applications is increasing. All this leads to specific but different requirements from applications to frameworks, service platforms, and networks. For each service, users desire special service criteria, such as smooth interactivity, fast downloads, high availability, or extensive content. Such requirements can usually be summarized under the term Quality of Experience, i.e., the overall satisfaction of a user with the system cur- rently in use. In the age of big data and dynamic networks, Quality of Experience is still looking for its place, and good solutions are in high demand. This Special Issue addresses the latest advances and challenges in analysis, design, modeling, measurement, and performance evaluation of Quality of Experience and Quality of Experience-oriented metrics and management.},
  author = {Wamser, Florian and Alay, Özgü and Metzger, Florian and Valentin, Stefan},
  journal = {International Journal of Network Management},
  keywords = {myown sys:hidden:article can},
  month = 3,
  title = {IJNM Special Issue - Editorial - QoE-centric Analysis and Management of Communication Networks},
  volume = {Special Issue: QoE-centric Analysis and Management of Communication Networks},
  year = 2020
}

2019 [ to top ]

Linguaglossa, L., Lange, S., Pontarelli, S., Retvari, G., Rossi, D., Zinner, T., Bificulo, R., Jarschel, M., Bianchi, G.: Survey of Performance Acceleration Techniques for Network Function Virtualization. Proceedings of the IEEE. (2019).

[ Abstract ] [ BibTeX ] [ EndNote ]

Göritz, A., Borchert, K., Hirth, M.: Using Attention Testing to Select Crowdsourced Workers and Research Participants. Social Science Computer Review. (2019).

[ BibTeX ] [ EndNote ]

Metzger, F., Hoßfeld, T., Bauer, A., Kounev, S., Heegaard, P.E.: Modeling of Aggregated IoT Traffic and Its Application to an IoT Cloud. Proceedings of the IEEE. 107, 679–694 (2019).

[ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]

@article{info3-article-2019-3,
  abstract = {As the Internet of Things (IoT) continues to gain traction in telecommunication networks, a very large number of devices are expected to be connected and used in the near future. In order to appropriately plan and dimension the network, as well as the back-end cloud systems and the resulting signaling load, traffic models are employed. These models are designed to accurately capture and predict the properties of IoT traffic in a concise manner. To achieve this, Poisson process approximations, based on the Palm–Khintchine theorem, have often been used in the past. Due to the scale (and the difference in scales in various IoT networks) of the modeled systems, the fidelity of this approximation is crucial, as, in practice, it is very challenging to accurately measure or simulate large-scale IoT deployments. The main goal of this paper is to understand the level of accuracy of the Poisson approximation model. To this end, we first survey both common IoT network properties and network scales as well as traffic types. Second, we explain and discuss the Palm–Khintiche theorem, how it is applied to the problem, and which inaccuracies can occur when using it. Based on this, we derive guidelines as to when a Poisson process can be assumed for aggregated periodic IoT traffic. Finally, we evaluate our approach in the context of an IoT cloud scaler use case.},
  author = {Metzger, Florian and Hoßfeld, Tobias and Bauer, André and Kounev, Samuel and Heegaard, Poul E.},
  journal = {Proceedings of the IEEE},
  keywords = {myown sys:hidden:article fullstack 5g-net doi:10.1109/JPROC.2019.2901578},
  month = 4,
  number = 4,
  pages = {679-694},
  title = {Modeling of Aggregated IoT Traffic and Its Application to an IoT Cloud},
  volume = 107,
  year = 2019
}

Schwind, A., Midoglu, C., Alay, Özgü, Griwodz, C., Wamser, F.: Dissecting the performance of YouTube video streaming in mobile networks. International Journal of Network Management. (2019).

[ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]

@article{info3-article-2019-2,
  abstract = {Video streaming applications constitute a significant portion of the Internet traffic today, with mobile accounting for more than half of the online video views. The high share of video in the current Internet traffic mix has prompted many studies that examine video streaming through measurements. However, streaming performance depends on many different factors at different layers of the TCP/IP stack. For example, browser selection at the application layer or the choice of protocol in transport layer can have significant impact on the video performance. Furthermore, video performance heavily depends on the underlying network conditions (eg, network and link layers). For mobile networks, the conditions vary significantly, since each operator has a different deployment strategy and configuration. In this paper, we focus on YouTube and carry out a comprehensive study investigating the influence of different factors on streaming performance. Leveraging the Measuring Mobile Broadband Networks in Europe (MONROE) test bed that enables experimentation with 13 different network configurations in four countries, we collect more than 1800 measurement samples in operational mobile networks. With this campaign, our goal is to quantify the impact of parameters from different layers on YouTube's streaming quality of experience (QoE). More specifically, we analyze the role of the browser (eg, Firefox and Chrome), the impact of transport protocol (eg, TCP or QUIC), the influence of network bandwidth, and signal coverage on streaming QoE. Our analysis reveals that all these parameters need to be taken into account jointly for network management practices, in order to ensure a high end‐user experience.},
  author = {Schwind, Anika and Midoglu, Cise and Alay, Özgü and Griwodz, Carsten and Wamser, Florian},
  journal = {International Journal of Network Management},
  keywords = {myown sys:hidden:article can},
  month = 1,
  title = {Dissecting the performance of YouTube video streaming in mobile networks},
  year = 2019
}

%0 Journal Article
%1 info3-article-2019-2
%A Schwind, Anika
%A Midoglu, Cise
%A Alay, Özgü
%A Griwodz, Carsten
%A Wamser, Florian
%D 2019
%J International Journal of Network Management
%T Dissecting the performance of YouTube video streaming in mobile networks
%X Video streaming applications constitute a significant portion of the Internet traffic today, with mobile accounting for more than half of the online video views. The high share of video in the current Internet traffic mix has prompted many studies that examine video streaming through measurements. However, streaming performance depends on many different factors at different layers of the TCP/IP stack. For example, browser selection at the application layer or the choice of protocol in transport layer can have significant impact on the video performance. Furthermore, video performance heavily depends on the underlying network conditions (eg, network and link layers). For mobile networks, the conditions vary significantly, since each operator has a different deployment strategy and configuration. In this paper, we focus on YouTube and carry out a comprehensive study investigating the influence of different factors on streaming performance. Leveraging the Measuring Mobile Broadband Networks in Europe (MONROE) test bed that enables experimentation with 13 different network configurations in four countries, we collect more than 1800 measurement samples in operational mobile networks. With this campaign, our goal is to quantify the impact of parameters from different layers on YouTube's streaming quality of experience (QoE). More specifically, we analyze the role of the browser (eg, Firefox and Chrome), the impact of transport protocol (eg, TCP or QUIC), the influence of network bandwidth, and signal coverage on streaming QoE. Our analysis reveals that all these parameters need to be taken into account jointly for network management practices, in order to ensure a high end‐user experience.

Wassermann, S., Wehner, N., Casas, P.: Machine Learning Models for YouTube QoE and User Engagement Prediction in Smartphones. ACM SIGMETRICS Performance Evaluation Review. 46, 155–158 (2019).

[ Abstract ] [ BibTeX ] [ EndNote ]

Seufert, M., Wassermann, S., Casas, P.: Considering User Behavior in the Quality of Experience Cycle: Towards Proactive QoE-aware Traffic Management. IEEE Communications Letters. 23, 1145–1148 (2019).

[ Abstract ] [ BibTeX ] [ EndNote ]

Geissler, S., Herrnleben, S., Bauer, R., Grigorjew, A., Jarschel, M., Zinner, T.: The Power of Composition: Abstracting a Multi-Device SDN Data Path Through a Single API. IEEE Transactions on Network and Service Management. (2019).

[ BibTeX ] [ EndNote ]

Seufert, M., Wehner, N., Casas, P.: A Fair Share for All: TCP-inspired Adaptation Logic for QoE Fairness among Heterogeneous HTTP Adaptive Video Streaming Clients. IEEE Transactions on Network and Service Management. 16, 475–488 (2019).

[ BibTeX ] [ EndNote ]

2018 [ to top ]

Dinh-Xuan, L., Popp, C., Burger, V., Wamser, F., Hoßfeld, T.: Impact of VNF Placements on QoE Monitoring in the Cloud. International Journal of Network Management. (2018).

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Schütz, A., Fertig, T., Weber, K., Vu, H., Hirth, M., Tran-Gia, T.: Vertrauen ist gut, Blockchain ist besser - Einsatzmöglichkeiten von Blockchain für Vertrauensprobleme im Crowdsourcing. HMD Praxis der Wirtschaftsinformatik. (2018).

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Burger, V., Zinner, T., Dinh-Xuan, L., Wamser, F., Tran-Gia, P.: A Generic Approach to Video Buffer Modeling using Discrete-Time Analysis. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM). 14, 23 (2018).

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Hoßfeld, T., Skorin-Kapov, L., Heegaard, P.E., Varela, M.: A new QoE fairness index for QoE management. Quality and User Experience. (2018).

[ BibTeX ] [ EndNote ]

Sieber, C., Hagn, K., Moldovan, C., Hoßfeld, T., Kellerer, W.: Towards Machine Learning-Based Optimal HAS. arXiv preprint arXiv:1808.08065. (2018).

[ BibTeX ] [ EndNote ]

Hoßfeld, T., Timmerer, C.: Quality of experience column: an introduction. ACM SIGMultimedia Records. 10 (2018).

[ BibTeX ] [ EndNote ]

Hoßfeld, T., Heegaard, P.E., Varela, M., Skorin-Kapov, L.: Confidence Interval Estimators for MOS Values. arXiv preprint arXiv:1806.01126. (2018).

[ BibTeX ] [ EndNote ]

Chang, H.-S., Hsu, C.-F., Hoßfeld, T., Chen, K.-T.: Active Learning for Crowdsourced QoE Modeling. IEEE Transactions on Multimedia. (2018).

[ BibTeX ] [ EndNote ]

Skorin-Kapov, L., Varela, M., Hoßfeld, T., Chen, K.-T.: A Survey of Emerging Concepts and Challenges for QoE Management of Multimedia Services. ACM Transactions on Multimedia Computing, Communications and Applications. (2018).

[ BibTeX ] [ EndNote ]

10.

Hoßfeld, T., Skorin-Kapov, L., Varela, M., Chen, K.-T.: Guest Editorial: Special Issue on “QoE Management for Multimedia Services”. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM). (2018).

[ BibTeX ] [ EndNote ]

2017 [ to top ]

Cofano, G., De Cicco, L., Zinner, T., Nguyen-Ngoc, A., Tran-Gia, P., Mascolo, S.: Design and Performance Evaluation of Network-assisted Control Strategies for HTTP Adaptive Streaming. ACM Transactions on Multimedia Computing, Communications, and Applications. (2017).

[ BibTeX ] [ EndNote ]

Zinner, T., Geissler, S., Lange, S., Gebert, S., Seufert, M., Tran-Gia, P.: A Discrete-Time Model for Optimizing the Processing Time of Virtualized Network Functions. Computer Networks. 125, 4–14 (2017).

[ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]

@article{info3-article-2017-1,
  abstract = {The softwarization of networks promises cost savings and better scalability of network functions by moving functionality from specialized devices into commercial off-the-shelf hardware. Generalized computing hardware offers many degrees of adjustment and tuning, which can affect performance and resource utilization. One of these adjustments are interrupt moderation techniques implemented by modern network interface cards and operating systems. Using these, an administrator can optimize either for low latencies or low CPU overhead for processing of network traffic. In this work, an analytical model that allows the computation of relevant performance metrics like packet processing time and packet loss for generic virtualized network functions running on commodity hardware is presented. Based on this model, impact factors like average packet interarrival time, interarrival time distribution, and duration of the interrupt aggregation interval are studied. Furthermore, we significantly improve the computational tractability of this discrete-time model by proving and leveraging a property regarding its limit behavior. We also demonstrate that using this property does not affect the accuracy of the model in the context of realistic parameter combinations. Finally, the improved runtime for numerical evaluations allows administrators to dynamically adapt their interrupt mitigation settings to changing network conditions by recalculating optimal parameters.},
  author = {Zinner, Thomas and Geissler, Stefan and Lange, Stanislav and Gebert, Steffen and Seufert, Michael and Tran-Gia, Phuoc},
  journal = {Computer Networks},
  keywords = {myown sys:hidden:article sendate sendate-planets ngn},
  pages = {4-14},
  title = {A Discrete-Time Model for Optimizing the Processing Time of Virtualized Network Functions},
  volume = 125,
  year = 2017
}

Hoffmann, M., Jarschel, M., Pries, R., Schneider, P., Jukan, A., Bziuk, W., Gebert, S., Zinner, T., Tran-Gia, P.: SDN and NFV as Enabler for the Distributed Network Cloud. Mobile Networks and Applications. (2017).

[ BibTeX ] [ EndNote ]

Metter, C., Seufert, M., Wamser, F., Zinner, T., Tran-Gia, P.: Analytical Model for SDN Signaling Traffic and Flow Table Occupancy and its Application for Various Types of Traffic. IEEE Transactions on Network and Service Management. 14, 603–615 (2017).

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@article{info3-article-2017-5,
  abstract = {Software Defined Networking (SDN) has emerged as a promising networking paradigm overcoming various drawbacks of current communication networks. The control and data plane of switching devices is decoupled and control functions are centralized at the network controller. In SDN, each new flow introduces additional signaling traffic between the switch and the controller. Based on this traffic, rules are created in the flow table of the switch, which specify the forwarding behavior. To avoid table overflows, unused entries are removed after a predefined time-out period. Given a specific traffic mix, the choice of this time-out period affects the trade-off between signaling rate and table occupancy. As a result, network operators have to adjust this parameter to enable a smooth and efficient network operation. Due to the complexity of this problem caused by the various traffic flows in a network, a suitable abstraction is necessary in order to derive valid parameter values in time. The contribution of this work is threefold. Firstly, we formulate a simple analytical model that allows optimizing the network performance with respect to the table occupancy and the signaling rate. Secondly, we validate the model by means of simulation. Thirdly, we illustrate the impact of the time-out period on the signaling traffic and the flow table occupancy for different data-plane traffic mixes and characteristics. This includes scenarios with single application instances, as well as multiple application instances of different application types in an SDN-enabled network.},
  author = {Metter, Christopher and Seufert, Michael and Wamser, Florian and Zinner, Thomas and Tran-Gia, Phuoc},
  journal = {IEEE Transactions on Network and Service Management},
  keywords = {myown sys:hidden:article sdn-ras can},
  month = 9,
  number = 3,
  pages = {603-615},
  title = {Analytical Model for SDN Signaling Traffic and Flow Table Occupancy and its Application for Various Types of Traffic},
  volume = 14,
  year = 2017
}

%0 Journal Article
%1 info3-article-2017-5
%A Metter, Christopher
%A Seufert, Michael
%A Wamser, Florian
%A Zinner, Thomas
%A Tran-Gia, Phuoc
%D 2017
%J IEEE Transactions on Network and Service Management
%N 3
%P 603-615
%T Analytical Model for SDN Signaling Traffic and Flow Table Occupancy and its Application for Various Types of Traffic
%V 14
%X Software Defined Networking (SDN) has emerged as a promising networking paradigm overcoming various drawbacks of current communication networks. The control and data plane of switching devices is decoupled and control functions are centralized at the network controller. In SDN, each new flow introduces additional signaling traffic between the switch and the controller. Based on this traffic, rules are created in the flow table of the switch, which specify the forwarding behavior. To avoid table overflows, unused entries are removed after a predefined time-out period. Given a specific traffic mix, the choice of this time-out period affects the trade-off between signaling rate and table occupancy. As a result, network operators have to adjust this parameter to enable a smooth and efficient network operation. Due to the complexity of this problem caused by the various traffic flows in a network, a suitable abstraction is necessary in order to derive valid parameter values in time. The contribution of this work is threefold. Firstly, we formulate a simple analytical model that allows optimizing the network performance with respect to the table occupancy and the signaling rate. Secondly, we validate the model by means of simulation. Thirdly, we illustrate the impact of the time-out period on the signaling traffic and the flow table occupancy for different data-plane traffic mixes and characteristics. This includes scenarios with single application instances, as well as multiple application instances of different application types in an SDN-enabled network.

Lorenz, C., Hock, D., Scherer, J., Durner, R., Kellerer, W., Gebert, S., Gray, N., Zinner, T., Tran-Gia, P.: An SDN/NFV-enabled Enterprise Network Architecture Offering Fine-Grained Security Policy Enforcement. IEEE Communications Magazine. 55, 217–223 (2017).

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Schwarzmann, S., Zinner, T., Dobrijevic, O.: Quantitative Comparison of Application-Network Interaction: A Case Study of Adaptive Video Streaming. Springer Quality and User Experience. (2017).

[ Abstract ] [ BibTeX ] [ EndNote ]

@article{info3-article-2017-4,
  abstract = {Managing quality of experience (QoE) is now widely accepted as a critical objective for multimedia applications and the supporting communication systems. In general, QoE management encompasses: (i) monitoring of the key influence factors and QoE indicators, and (ii) deciding on the appropriate control actions as specified by the management goal. Many multimedia applications, e.g. video streaming and audio conferencing, are able to adjust their operational parameters so as to react to variations in the network performance. However, such an adaptation feature is mostly based on a local client view of the network conditions, which may lead to an unfair allocation of network resources among heterogeneous clients and, thus, an unfair QoE distribution. In order to tackle this issue, there is the call for a cooperation between the applications and the underlying network, which includes application-network interaction (App-Net) in terms of: (1) exchanging information on the monitored QoE indicators, and (2) coordinating the QoE control actions. Various App-Net mechanisms focusing on specific use cases and applications have been proposed to date. This paper gives an overview of App-Net mechanisms and proposes a generic App-Net model that provides the means to realize a coordinated QoE-centric management. Based on the App-Net model, we develop an evaluation methodology to compare three App-Net mechanisms for managing QoE of HTTP adaptive streaming (HAS) against a baseline HAS service. The aim of this quantitative comparison is to explore the trade-offs between QoE gains and the complexity of App-Net implementation, with respect to the number of monitoring and control messages, achieved video quality, and QoE fairness among heterogeneous clients. Our ultimate goal is to set up reproducible experiments that facilitate a holistic evaluation of different App-Net mechanisms.},
  author = {Schwarzmann, Susanna and Zinner, Thomas and Dobrijevic, Ognjen},
  journal = {Springer Quality and User Experience},
  keywords = {myown sys:hidden:article dfg-sdn ngn},
  title = {Quantitative Comparison of Application-Network Interaction: A Case Study of Adaptive Video Streaming},
  year = 2017
}

%0 Journal Article
%1 info3-article-2017-4
%A Schwarzmann, Susanna
%A Zinner, Thomas
%A Dobrijevic, Ognjen
%D 2017
%J Springer Quality and User Experience
%T Quantitative Comparison of Application-Network Interaction: A Case Study of Adaptive Video Streaming
%X Managing quality of experience (QoE) is now widely accepted as a critical objective for multimedia applications and the supporting communication systems. In general, QoE management encompasses: (i) monitoring of the key influence factors and QoE indicators, and (ii) deciding on the appropriate control actions as specified by the management goal. Many multimedia applications, e.g. video streaming and audio conferencing, are able to adjust their operational parameters so as to react to variations in the network performance. However, such an adaptation feature is mostly based on a local client view of the network conditions, which may lead to an unfair allocation of network resources among heterogeneous clients and, thus, an unfair QoE distribution. In order to tackle this issue, there is the call for a cooperation between the applications and the underlying network, which includes application-network interaction (App-Net) in terms of: (1) exchanging information on the monitored QoE indicators, and (2) coordinating the QoE control actions. Various App-Net mechanisms focusing on specific use cases and applications have been proposed to date. This paper gives an overview of App-Net mechanisms and proposes a generic App-Net model that provides the means to realize a coordinated QoE-centric management. Based on the App-Net model, we develop an evaluation methodology to compare three App-Net mechanisms for managing QoE of HTTP adaptive streaming (HAS) against a baseline HAS service. The aim of this quantitative comparison is to explore the trade-offs between QoE gains and the complexity of App-Net implementation, with respect to the number of monitoring and control messages, achieved video quality, and QoE fairness among heterogeneous clients. Our ultimate goal is to set up reproducible experiments that facilitate a holistic evaluation of different App-Net mechanisms.

Hoßfeld, T., Chan, S.-H.G., Mark, B.L., Timm-Giel, A.: Softwarization and Caching in NGN. Computer Networks. 125, 1–3 (2017).

[ BibTeX ] [ EndNote ]

Hoßfeld, T.: 2016 International Teletraffic Congress (ITC 28) Report. ACM SIGCOMM Computer Communication Review. (2017).

[ BibTeX ] [ EndNote ]

2016 [ to top ]

Seufert, M., Burger, V., Lorey, K., Seith, A., Loh, F., Tran-Gia, P.: Assessment of Subjective Influence and Trust with an Online Social Network Game. Computers in Human Behavior. 64, 233–246 (2016).

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Hoßfeld, T., Skorin-Kapov, L., Heegaard, P.E., Varela, M.: Definition of QoE Fairness in Shared Systems. IEEE Communications Letters. (2016).

[ BibTeX ] [ EndNote ]

Seufert, M., Lange, S., Hoßfeld, T.: More than Topology: Joint Topology and Attribute Sampling and Generation of Social Network Graphs. Computer Communications. 73, 176–187 (2016).

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@article{info3-article-2016-1,
  abstract = {Graph sampling refers to the process of deriving a small subset of nodes from a possibly huge graph in order to estimate properties of the whole graph from examining the sample. Whereas topological properties can already be obtained accurately by sampling, current approaches do not take possibly hidden dependencies between node topology and attributes into account. Especially in the context of online social networks, node attributes are of importance as they correspond to properties of the social network's users. Therefore, existing sampling algorithms can be extended to attribute sampling, but still lack the capturing of structural properties. Analyzing topology (e.g., node degree, clustering coefficient) and attribute properties (e.g., age, location) jointly can provide valuable insights into the social network and allows for a better understanding of social processes. As major contribution, this work proposes a novel sampling algorithm which provides unbiased and reliable estimates of joint topological and attribute based graph properties in a resource efficient fashion. Furthermore, the obtained samples allow for the generation of synthetic graphs, which show high similarity to the original graph with respect to topology and attributes. The proposed sampling and generation algorithms are evaluated on real world social network graphs, for which they demonstrate to be effective.},
  author = {Seufert, Michael and Lange, Stanislav and Hoßfeld, Tobias},
  journal = {Computer Communications},
  keywords = {myown sys:hidden:article can},
  month = 1,
  number = {Part B},
  pages = {176-187},
  title = {More than Topology: Joint Topology and Attribute Sampling and Generation of Social Network Graphs},
  volume = 73,
  year = 2016
}

Seufert, M., Griepentrog, T., Burger, V., Hoßfeld, T.: A Simple WiFi Hotspot Model for Cities. IEEE Communications Letters. 20, 384–387 (2016).

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Burger, V., Seufert, M., Hoßfeld, T., Tran-Gia, P.: Performance Evaluation of Backhaul Bandwidth Aggregation Using a Partial Sharing Scheme. Physical Communication. 19, 135–144 (2016).

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Casas, P., Seufert, M., Wamser, F., Gardlo, B., Sackl, A., Schatz, R.: Next to You: Monitoring Quality of Experience in Cellular Networks from the End-devices. IEEE Transactions on Network and Service Management. 13, 181–196 (2016).

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@article{info3-article-2016-4,
  abstract = {A quarter of the world population will be using smartphones to access the Internet in the near future. In this context, understanding the Quality of Experience (QoE) of popular apps in such devices becomes paramount to cellular network operators, who need to offer high quality levels to reduce the risks of customers churning for quality dissatisfaction. In this paper we address the problem of QoE provisioning in smartphones from a double perspective, combining the results obtained from subjective lab tests with end-device passive measurements and QoE crowd-sourced feedback obtained in operational cellular networks. The study addresses the impact of both access bandwidth and latency on the QoE of five different services and mobile apps: YouTube, Facebook, Web browsing through Chrome, Google Maps, and WhatsApp. We evaluate the influence of both constant and dynamically changing network access conditions, tackling in particular the case of fluctuating downlink bandwidth, which is typical in cellular networks. As a main contribution, we show that the results obtained in the lab are highly applicable in the live scenario, as mappings track the QoE provided by users in real networks. We additionally provide hints and bandwidth thresholds for good QoE levels on such apps, as well as discussion on end-device passive measurements and analysis. The results presented in this paper provide a sound basis to better understand the QoE requirements of popular mobile apps, as well as for monitoring the underlying provisioning network. To the best of our knowledge, this is the first paper providing such a comprehensive analysis of QoE in mobile devices, combining network measurements with users QoE feedback in lab tests and operational networks.},
  author = {Casas, Pedro and Seufert, Michael and Wamser, Florian and Gardlo, Bruno and Sackl, Andreas and Schatz, Raimund},
  journal = {IEEE Transactions on Network and Service Management},
  keywords = {myown sys:hidden:article smartqoe youtube can},
  month = 3,
  number = 2,
  pages = {181-196},
  title = {Next to You: Monitoring Quality of Experience in Cellular Networks from the End-devices},
  volume = 13,
  year = 2016
}

%0 Journal Article
%1 info3-article-2016-4
%A Casas, Pedro
%A Seufert, Michael
%A Wamser, Florian
%A Gardlo, Bruno
%A Sackl, Andreas
%A Schatz, Raimund
%D 2016
%J IEEE Transactions on Network and Service Management
%N 2
%P 181-196
%T Next to You: Monitoring Quality of Experience in Cellular Networks from the End-devices
%V 13
%X A quarter of the world population will be using smartphones to access the Internet in the near future. In this context, understanding the Quality of Experience (QoE) of popular apps in such devices becomes paramount to cellular network operators, who need to offer high quality levels to reduce the risks of customers churning for quality dissatisfaction. In this paper we address the problem of QoE provisioning in smartphones from a double perspective, combining the results obtained from subjective lab tests with end-device passive measurements and QoE crowd-sourced feedback obtained in operational cellular networks. The study addresses the impact of both access bandwidth and latency on the QoE of five different services and mobile apps: YouTube, Facebook, Web browsing through Chrome, Google Maps, and WhatsApp. We evaluate the influence of both constant and dynamically changing network access conditions, tackling in particular the case of fluctuating downlink bandwidth, which is typical in cellular networks. As a main contribution, we show that the results obtained in the lab are highly applicable in the live scenario, as mappings track the QoE provided by users in real networks. We additionally provide hints and bandwidth thresholds for good QoE levels on such apps, as well as discussion on end-device passive measurements and analysis. The results presented in this paper provide a sound basis to better understand the QoE requirements of popular mobile apps, as well as for monitoring the underlying provisioning network. To the best of our knowledge, this is the first paper providing such a comprehensive analysis of QoE in mobile devices, combining network measurements with users QoE feedback in lab tests and operational networks.

Tavakoli, S., Egger, S., Seufert, M., Schatz, R., Brunnström, K., García, N.: Perceptual Quality of HTTP Adaptive Streaming Strategies: Cross-Experimental Analysis of Multi-Laboratory and Crowdsourced Subjective Studies. IEEE Journal on Selected Areas in Communications. 34, 2141–2153 (2016).

[ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]

@article{info3-article-2016-5,
  abstract = {Today’s packet-switched networks are subject to bandwidth fluctuations that cause for degradation of user experience of multimedia services. In order to cope with this problem, HTTP Adaptive Streaming (HAS) has been proposed in recent years as a video delivery solution for the future Internet and being adopted by an increasing number of streaming services such as Netflix and Youtube. HAS enables service providers to improve users’ Quality of Experience (QoE) and network resource utilization by adapting the quality of the video stream to the current network conditions. However, the resulting timevarying video quality caused by adaptation introduces a new type of impairment and thus novel QoE research challenges. Despite of various recent attempts to investigate these challenges, many fundamental questions regarding HAS perceptual performance are still open. In this paper, the QoE impact of different technical adaptation parameters including chunk length, switching amplitude, switching frequency and temporal recency are investigated. In addition, the influence of content on perceptual quality of these parameters is analyzed. To this end, a large number of adaptation scenarios have been subjectively evaluated in four laboratory experiments and one crowdsourcing study. Statistical analysis of the combined dataset reveals results that partly contradict widely held assumptions and provide novel insights in perceptual quality of adapted video sequences, e.g. interaction effects between quality switching direction (up/down) and switching strategy (smooth/abrupt). The large variety of experimental configurations across different studies ensures the consistency and external validity of the presented results that can be utilized for enhancing the perceptual performance of adaptive streaming services.},
  author = {Tavakoli, Samira and Egger, Sebastian and Seufert, Michael and Schatz, Raimund and Brunnström, Kjell and García, Narciso},
  journal = {IEEE Journal on Selected Areas in Communications},
  keywords = {myown sys:hidden:article can},
  month = 6,
  number = 8,
  pages = {2141-2153},
  title = {Perceptual Quality of HTTP Adaptive Streaming Strategies: Cross-Experimental Analysis of Multi-Laboratory and Crowdsourced Subjective Studies},
  volume = 34,
  year = 2016
}

%0 Journal Article
%1 info3-article-2016-5
%A Tavakoli, Samira
%A Egger, Sebastian
%A Seufert, Michael
%A Schatz, Raimund
%A Brunnström, Kjell
%A García, Narciso
%D 2016
%J IEEE Journal on Selected Areas in Communications
%N 8
%P 2141-2153
%T Perceptual Quality of HTTP Adaptive Streaming Strategies: Cross-Experimental Analysis of Multi-Laboratory and Crowdsourced Subjective Studies
%V 34
%X Today’s packet-switched networks are subject to bandwidth fluctuations that cause for degradation of user experience of multimedia services. In order to cope with this problem, HTTP Adaptive Streaming (HAS) has been proposed in recent years as a video delivery solution for the future Internet and being adopted by an increasing number of streaming services such as Netflix and Youtube. HAS enables service providers to improve users’ Quality of Experience (QoE) and network resource utilization by adapting the quality of the video stream to the current network conditions. However, the resulting timevarying video quality caused by adaptation introduces a new type of impairment and thus novel QoE research challenges. Despite of various recent attempts to investigate these challenges, many fundamental questions regarding HAS perceptual performance are still open. In this paper, the QoE impact of different technical adaptation parameters including chunk length, switching amplitude, switching frequency and temporal recency are investigated. In addition, the influence of content on perceptual quality of these parameters is analyzed. To this end, a large number of adaptation scenarios have been subjectively evaluated in four laboratory experiments and one crowdsourcing study. Statistical analysis of the combined dataset reveals results that partly contradict widely held assumptions and provide novel insights in perceptual quality of adapted video sequences, e.g. interaction effects between quality switching direction (up/down) and switching strategy (smooth/abrupt). The large variety of experimental configurations across different studies ensures the consistency and external validity of the presented results that can be utilized for enhancing the perceptual performance of adaptive streaming services.

Wamser, F., Casas, P., Seufert, M., Moldovan, C., Tran-Gia, P., Hoßfeld, T.: Modeling the YouTube Stack: from Packets to Quality of Experience. Computer Networks. 109, 211–224 (2016).

[ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]

@article{info3-article-2016-6,
  abstract = {YouTube is one of the most popular and volume-dominant services in today’s Internet, and has changed the Web for ever. Consequently, network operators are forced to consider it in the design, deployment, and optimization of their networks. Taming YouTube requires a good understanding of the complete YouTube stack, from the network streaming service to the application itself. Understanding the interplays between individual YouTube functionalities and their implications for traffic and user Quality of Experience (QoE) becomes paramount nowadays. In this paper we characterize and model the YouTube stack at different layers, going from the generated network traffic to the QoE perceived by the users watching YouTube videos. Firstly, we present a network traffic model for the YouTube flow control mechanism, which permits to understand how YouTube provisions video traffic flows to users. Secondly, we investigate how traffic is consumed at the client side, deriving a simple model for the YouTube application. Thirdly, we analyze the implications for the end user, and present a model for the quality as perceived by them. This model is finally integrated into a system for real time QoE-based YouTube monitoring, highly useful to operators to assess the performance of their networks for provisioning YouTube videos. The central parameter for all the presented models is the buffer level at the YouTube application layer. This paper provides an extensive compendium of objective tools and models for network operators to better understand the YouTube traffic in their networks, to predict the playback behavior of the video player, and to assess how well they do it in the practice with the satisfaction of their customers watching YouTube.},
  author = {Wamser, Florian and Casas, Pedro and Seufert, Michael and Moldovan, Christian and Tran-Gia, Phuoc and Hoßfeld, Tobias},
  journal = {Computer Networks},
  keywords = {myown sys:hidden:article input qoedz selected-findings-and-results-youtube youtube can},
  month = 11,
  number = 2,
  pages = {211-224},
  title = {Modeling the YouTube Stack: from Packets to Quality of Experience},
  volume = 109,
  year = 2016
}

%0 Journal Article
%1 info3-article-2016-6
%A Wamser, Florian
%A Casas, Pedro
%A Seufert, Michael
%A Moldovan, Christian
%A Tran-Gia, Phuoc
%A Hoßfeld, Tobias
%D 2016
%J Computer Networks
%N 2
%P 211-224
%T Modeling the YouTube Stack: from Packets to Quality of Experience
%V 109
%X YouTube is one of the most popular and volume-dominant services in today’s Internet, and has changed the Web for ever. Consequently, network operators are forced to consider it in the design, deployment, and optimization of their networks. Taming YouTube requires a good understanding of the complete YouTube stack, from the network streaming service to the application itself. Understanding the interplays between individual YouTube functionalities and their implications for traffic and user Quality of Experience (QoE) becomes paramount nowadays. In this paper we characterize and model the YouTube stack at different layers, going from the generated network traffic to the QoE perceived by the users watching YouTube videos. Firstly, we present a network traffic model for the YouTube flow control mechanism, which permits to understand how YouTube provisions video traffic flows to users. Secondly, we investigate how traffic is consumed at the client side, deriving a simple model for the YouTube application. Thirdly, we analyze the implications for the end user, and present a model for the quality as perceived by them. This model is finally integrated into a system for real time QoE-based YouTube monitoring, highly useful to operators to assess the performance of their networks for provisioning YouTube videos. The central parameter for all the presented models is the buffer level at the YouTube application layer. This paper provides an extensive compendium of objective tools and models for network operators to better understand the YouTube traffic in their networks, to predict the playback behavior of the video player, and to assess how well they do it in the practice with the satisfaction of their customers watching YouTube.

Metzger, F., Liotou, E., Moldovan, C., Hoßfeld, T.: TCP video streaming and mobile networks: Not a love story, but better with context. Computer Networks. 109, 246–256 (2016).

[ BibTeX ] [ EndNote ]

10.

Wamser, F.: Leistungsbewertung von Ressourcenmanagementstrategien für zelluläre und drahtlose Mesh-Netzwerke. Lecture Notes in Informatics (LNI). Ausgezeichnete Informatikdissertationen 2015, (2016).

[ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]

11.

Hoßfeld, T., Heegaard, P.E., Varela, M., Möller, S.: Formal definition of QoE metrics. arXiv preprint arXiv:1607.00321. (2016).

[ BibTeX ] [ EndNote ]

12.

Hoßfeld, T., Heegaard, P.E., Varela, M., Möller, S.: QoE beyond the MOS: an in-depth look at QoE via better metrics and their relation to MOS. Quality and User Experience. 1, (2016).

[ BibTeX ] [ EndNote ]

2015 [ to top ]

Seufert, M., Egger, S., Slanina, M., Zinner, T., Hoßfeld, T., Tran-Gia, P.: A Survey on Quality of Experience of HTTP Adaptive Streaming. IEEE Communications Surveys & Tutorials. 17, 469–492 (2015).

[ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]

Changing network conditions pose severe problems to video streaming in the Internet. HTTP adaptive streaming (HAS) is a technology employed by numerous video services which relieves these issues by adapting the video to the current network conditions. It enables service providers to improve resource utilization and Quality of Experience (QoE) by incorporating information from different layers in order to deliver and adapt a video in its best possible quality. Thereby, it allows to take into account end user device capabilities, available video quality levels, current network conditions, and current server load. For end users, the major benefits of HAS compared to classical HTTP video streaming are reduced interruptions of the video playback and higher bandwidth utilization, which both generally result in a higher QoE. Adaptation is possible by changing the frame rate, resolution, or quantization of the video, which can be done with various adaptation strategies and related client- and server-side actions. The technical development of HAS, existing open standardized solutions, but also proprietary solutions are reviewed in this article as fundament to derive the QoE influence factors which emerge as a result of adaptation. The main contribution is a comprehensive survey of QoE related works from human computer interaction and networking domains which are structured according to the QoE impact of video adaptation. To be more precise, subjective studies which cover QoE aspects of adaptation dimensions and strategies are revisited. As a result, QoE influence factors of HAS and corresponding QoE models are identified, but also open issues and conflicting results are discussed. Furthermore, technical influence factors, which are often ignored in the context of HAS, affect perceptual QoE influence factors and are consequently analyzed. This survey gives the reader an overview of the current state of the art and recent developments. At the same time it targets networking researchers who develop new solutions for HTTP video streaming or assess video streaming from a user centric point of view. Therefore, the article is a major step towards truly improving HAS.

@article{info3-article-2015-126,
  abstract = {Changing network conditions pose severe problems to video streaming in the Internet. HTTP adaptive streaming (HAS) is a technology employed by numerous video services which relieves these issues by adapting the video to the current network conditions. It enables service providers to improve resource utilization and Quality of Experience (QoE) by incorporating information from different layers in order to deliver and adapt a video in its best possible quality. Thereby, it allows to take into account end user device capabilities, available video quality levels, current network conditions, and current server load. For end users, the major benefits of HAS compared to classical HTTP video streaming are reduced interruptions of the video playback and higher bandwidth utilization, which both generally result in a higher QoE. Adaptation is possible by changing the frame rate, resolution, or quantization of the video, which can be done with various adaptation strategies and related client- and server-side actions. The technical development of HAS, existing open standardized solutions, but also proprietary solutions are reviewed in this article as fundament to derive the QoE influence factors which emerge as a result of adaptation. The main contribution is a comprehensive survey of QoE related works from human computer interaction and networking domains which are structured according to the QoE impact of video adaptation. To be more precise, subjective studies which cover QoE aspects of adaptation dimensions and strategies are revisited. As a result, QoE influence factors of HAS and corresponding QoE models are identified, but also open issues and conflicting results are discussed. Furthermore, technical influence factors, which are often ignored in the context of HAS, affect perceptual QoE influence factors and are consequently analyzed. This survey gives the reader an overview of the current state of the art and recent developments. At the same time it targets networking researchers who develop new solutions for HTTP video streaming or assess video streaming from a user centric point of view. Therefore, the article is a major step towards truly improving HAS.},
  author = {Seufert, Michael and Egger, Sebastian and Slanina, Martin and Zinner, Thomas and Hoßfeld, Tobias and Tran-Gia, Phuoc},
  journal = {IEEE Communications Surveys & Tutorials},
  keywords = {myown sys:hidden:article oekonet smartenit},
  month = 3,
  pages = {469-492},
  title = {A Survey on Quality of Experience of HTTP Adaptive Streaming},
  volume = 17,
  year = 2015
}

%0 Journal Article
%1 info3-article-2015-126
%A Seufert, Michael
%A Egger, Sebastian
%A Slanina, Martin
%A Zinner, Thomas
%A Hoßfeld, Tobias
%A Tran-Gia, Phuoc
%D 2015
%J IEEE Communications Surveys & Tutorials
%P 469-492
%T A Survey on Quality of Experience of HTTP Adaptive Streaming
%V 17
%X Changing network conditions pose severe problems to video streaming in the Internet. HTTP adaptive streaming (HAS) is a technology employed by numerous video services which relieves these issues by adapting the video to the current network conditions. It enables service providers to improve resource utilization and Quality of Experience (QoE) by incorporating information from different layers in order to deliver and adapt a video in its best possible quality. Thereby, it allows to take into account end user device capabilities, available video quality levels, current network conditions, and current server load. For end users, the major benefits of HAS compared to classical HTTP video streaming are reduced interruptions of the video playback and higher bandwidth utilization, which both generally result in a higher QoE. Adaptation is possible by changing the frame rate, resolution, or quantization of the video, which can be done with various adaptation strategies and related client- and server-side actions. The technical development of HAS, existing open standardized solutions, but also proprietary solutions are reviewed in this article as fundament to derive the QoE influence factors which emerge as a result of adaptation. The main contribution is a comprehensive survey of QoE related works from human computer interaction and networking domains which are structured according to the QoE impact of video adaptation. To be more precise, subjective studies which cover QoE aspects of adaptation dimensions and strategies are revisited. As a result, QoE influence factors of HAS and corresponding QoE models are identified, but also open issues and conflicting results are discussed. Furthermore, technical influence factors, which are often ignored in the context of HAS, affect perceptual QoE influence factors and are consequently analyzed. This survey gives the reader an overview of the current state of the art and recent developments. At the same time it targets networking researchers who develop new solutions for HTTP video streaming or assess video streaming from a user centric point of view. Therefore, the article is a major step towards truly improving HAS.

Hoßfeld, T., Tran-Gia, P., Vukovic, M.: Special issue on crowdsourcing. Computer Networks: The International Journal of Computer and Telecommunications Networking. (2015).

[ BibTeX ] [ EndNote ]

Blenk, A., Basta, A., Kellerer, W., Zinner, T., Wamser, F., Tran-Gia, P.: Network Functions Virtualization (NFV) und Software Defined Networking (SDN): Forschungsfragen und Anwendungsfälle. ITG Mitgliederbeiträge / VDE dialog (invited article). 10–13 (2015).

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Hoßfeld, T., Metzger, F., Jarschel, M.: QoE for Cloud Gaming. IEEE Communications Society E-Letter. (2015).

[ Abstract ] [ BibTeX ] [ EndNote ]

@article{info3-article-2015-9,
  abstract = {Cloud Gaming combines the successful concepts of Cloud Computing and Online Gaming. It provides the entire game experience to the users by processing the game in the cloud and streaming the contents to the player. The player is no longer dependent on a specific type or quality of gaming hardware, but is able to use common devices. However, at the same time the end device needs a broadband internet connection and the ability to display a video stream properly. While this may reduce hardware costs for users and increase the revenue for developers by leaving out the retail chain, it also raises new challenges for Quality of Service (QoS) in terms of bandwidth and latency for the underlying network. In particular, there is a strong interest in the player’s Quality of Experience (QoE) by the involved stakeholders, ie, the game providers and the network operators. Given similar pricing schemes, players are likely to be influenced by expected and experienced quality. Thus, a provider is interested to understand QoE and to react on QoE problems by managing or adapting the service. There is also a strong academic interest, since QoE for cloud gaming as well as managing QoE for cloud gaming addresses a multitude of fascinating challenges in QoE. One might think that the topic of online video games is equally popular in research, but efforts are often solely focused on cloud gaming and its subjective QoE through user studies. Compared to plain video streaming, the inner properties of video games are not that straight-forward to observe from the outside. But to conduct proper measurements, it is essential to understand them.},
  author = {Hoßfeld, Tobias and Metzger, Florian and Jarschel, Michael},
  journal = {IEEE Communications Society E-Letter},
  keywords = {myown sys:hidden:article},
  month = 11,
  title = {QoE for Cloud Gaming},
  year = 2015
}

Hirth, M., Hoßfeld, T., Mellia, M., Schwartz, C., Lehrieder, F.: Crowdsourced Network Measurements: Benefits and Best Practices. Computer Networks Special Issue on Crowdsourcing. (2015).

[ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]

Wamser, F., Blenk, A., Seufert, M., Zinner, T., Kellerer, W., Tran-Gia, P.: Modeling and Performance Analysis of Application-Aware Resource Management. International Journal of Network Management. 25, 223–241 (2015).

[ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]

@article{info3-article-2015-134,
  abstract = {Application-aware resource management is the approach to tailor access networks to have characteristics beneficial for the running applications and services. This is achieved through the monitoring and integration of key performance indicators from the application layer within the network resource management. The aim is to increase user-perceived quality and network resource efficiency by traffic engineering with the help of these indicators. Using analytic and simulative approaches, this paper provides analysis methods for network operators to quantify the performance gains of alternative resource allocation algorithms that implement the application-aware concept. Network operators can use the proposed methods to evaluate possible performance gain trade-offs between investing in a pure capacity increase (over-provisioning) and the realization of an application-aware resource allocation. For this purpose, we model and analyze the application quality trade-offs of four algorithms for application-aware resource management at a single link in varying traffic situations. The algorithms are chosen with respect to different complexity and implementation level in order to cover the design space in a systematic way. The study of the algorithms focuses on the application-layer performance for the most used applications today, namely web browsing and video streaming with constant bit-rate as well as HTTP progressive streaming with variable bit-rate. Application quality trade-offs are analyzed in particular for a high resource utilization at a bottleneck link. The results confirm that application-aware resource management outperforms best-effort resource management in terms of QoE. Moreover, our study provides guidelines for the selection and configuration of the evaluated algorithms.},
  author = {Wamser, Florian and Blenk, Andreas and Seufert, Michael and Zinner, Thomas and Kellerer, Wolfgang and Tran-Gia, Phuoc},
  journal = {International Journal of Network Management},
  keywords = {myown sys:hidden:article},
  month = 7,
  pages = {223-241},
  title = {Modeling and Performance Analysis of Application-Aware Resource Management},
  volume = 25,
  year = 2015
}

%0 Journal Article
%1 info3-article-2015-134
%A Wamser, Florian
%A Blenk, Andreas
%A Seufert, Michael
%A Zinner, Thomas
%A Kellerer, Wolfgang
%A Tran-Gia, Phuoc
%D 2015
%J International Journal of Network Management
%P 223-241
%T Modeling and Performance Analysis of Application-Aware Resource Management
%V 25
%X Application-aware resource management is the approach to tailor access networks to have characteristics beneficial for the running applications and services. This is achieved through the monitoring and integration of key performance indicators from the application layer within the network resource management. The aim is to increase user-perceived quality and network resource efficiency by traffic engineering with the help of these indicators. Using analytic and simulative approaches, this paper provides analysis methods for network operators to quantify the performance gains of alternative resource allocation algorithms that implement the application-aware concept. Network operators can use the proposed methods to evaluate possible performance gain trade-offs between investing in a pure capacity increase (over-provisioning) and the realization of an application-aware resource allocation. For this purpose, we model and analyze the application quality trade-offs of four algorithms for application-aware resource management at a single link in varying traffic situations. The algorithms are chosen with respect to different complexity and implementation level in order to cover the design space in a systematic way. The study of the algorithms focuses on the application-layer performance for the most used applications today, namely web browsing and video streaming with constant bit-rate as well as HTTP progressive streaming with variable bit-rate. Application quality trade-offs are analyzed in particular for a high resource utilization at a bottleneck link. The results confirm that application-aware resource management outperforms best-effort resource management in terms of QoE. Moreover, our study provides guidelines for the selection and configuration of the evaluated algorithms.

Hoßfeld, T., Seufert, M., Sieber, C., Zinner, T., Tran-Gia, P.: Identifying QoE Optimal Adaptation of HTTP Adaptive Streaming Based on Subjective Studies. Computer Networks. 81, 320–332 (2015).

[ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]

Lange, S., Gebert, S., Zinner, T., Tran-Gia, P., Hock, D., Jarschel, M., Hoffmann, M.: Heuristic Approaches to the Controller Placement Problem in Large Scale SDN Networks. IEEE Transactions on Network and Service Management - Special Issue on Efficient Management of SDN and NFV-based Systems. 12, 4–17 (2015).

[ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]

@article{info3-article-2015-131,
  abstract = {Software Defined Networking (SDN) marks a paradigm shift towards an externalized and logically centralized network control plane. A particularly important task in SDN architectures is that of controller placement, i.e., the positioning of a limited number of resources within a network in order to meet various requirements. These requirements range from latency constraints to failure tolerance and load balancing. In most scenarios, at least some of these objectives are competing, thus no single best placement is available and decision makers need to find a balanced trade-off. This work presents POCO, a framework for Pareto-based Optimal COntroller placement that provides operators with Pareto optimal placements with respect to different performance metrics. In its default configuration, POCO performs an exhaustive evaluation of all possible placements. While this is practically feasible for small and medium sized networks, realistic time and resource constraints call for an alternative in the context of large scale networks or dynamic networks whose properties change over time. For these scenarios, the POCO toolset is extended by a heuristic approach that is less accurate, but yields faster computation times. An evaluation of this heuristic is performed on a collection of real world network topologies from the Internet Topology Zoo. Utilizing a measure for quantifying the error introduced by the heuristic approach allows an analysis of the resulting trade-off between time and accuracy. Additionally, the proposed methods can be extended to solve similar virtual functions placement problems which appear in the context of Network Functions Virtualization (NFV).},
  author = {Lange, Stanislav and Gebert, Steffen and Zinner, Thomas and Tran-Gia, Phuoc and Hock, David and Jarschel, Michael and Hoffmann, Marco},
  journal = {IEEE Transactions on Network and Service Management - Special Issue on Efficient Management of SDN and NFV-based Systems},
  keywords = {myown sys:hidden:article poco saser-siegfried},
  number = 1,
  pages = {4 - 17},
  title = {Heuristic Approaches to the Controller Placement Problem in Large Scale SDN Networks},
  volume = 12,
  year = 2015
}

%0 Journal Article
%1 info3-article-2015-131
%A Lange, Stanislav
%A Gebert, Steffen
%A Zinner, Thomas
%A Tran-Gia, Phuoc
%A Hock, David
%A Jarschel, Michael
%A Hoffmann, Marco
%D 2015
%J IEEE Transactions on Network and Service Management - Special Issue on Efficient Management of SDN and NFV-based Systems
%N 1
%P 4 - 17
%T Heuristic Approaches to the Controller Placement Problem in Large Scale SDN Networks
%V 12
%X Software Defined Networking (SDN) marks a paradigm shift towards an externalized and logically centralized network control plane. A particularly important task in SDN architectures is that of controller placement, i.e., the positioning of a limited number of resources within a network in order to meet various requirements. These requirements range from latency constraints to failure tolerance and load balancing. In most scenarios, at least some of these objectives are competing, thus no single best placement is available and decision makers need to find a balanced trade-off. This work presents POCO, a framework for Pareto-based Optimal COntroller placement that provides operators with Pareto optimal placements with respect to different performance metrics. In its default configuration, POCO performs an exhaustive evaluation of all possible placements. While this is practically feasible for small and medium sized networks, realistic time and resource constraints call for an alternative in the context of large scale networks or dynamic networks whose properties change over time. For these scenarios, the POCO toolset is extended by a heuristic approach that is less accurate, but yields faster computation times. An evaluation of this heuristic is performed on a collection of real world network topologies from the Internet Topology Zoo. Utilizing a measure for quantifying the error introduced by the heuristic approach allows an analysis of the resulting trade-off between time and accuracy. Additionally, the proposed methods can be extended to solve similar virtual functions placement problems which appear in the context of Network Functions Virtualization (NFV).

2014 [ to top ]

Hoßfeld, T., Keimel, C., Hirth, M., Gardlo, B., Habigt, J., Diepold, K., Tran-Gia, P.: Best Practices for QoE Crowdtesting: QoE Assessment with Crowdsourcing. Transactions on Multimedia. 16, (2014).

[ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]

@article{info3-article-2014-117,
  abstract = {Quality of Experience (QoE) in multimedia applications is closely linked to the end users’ perception and therefore its assessment requires subjective user studies in order to evaluate the degree of delight or annoyance as experienced by the users. QoE crowdtesting refers to QoE assessment using crowdsourcing, where anonymous test subjects conduct subjective tests remotely in their preferred environment. The advantages of QoE crowdtesting lie not only in the reduced time and costs for the tests, but also in a large and diverse panel of international, geographically distributed users in realistic user settings. However, conceptual and technical challenges emerge due to the remote test settings. Key issues arising from QoE crowdtesting include the reliability of user ratings, the influence of incentives, payment schemes and the unknown environmental context of the tests on the results. In order to counter these issues, strategies and methods need to be developed, included in the test design, and also implemented in the actual test campaign, while statistical methods are required to identify reliable user ratings and to ensure high data quality. This contribution therefore provides a collection of best practices addressing these issues based on our experience gained in a large set of conducted QoE crowdtesting studies. The focus of this article is in particular on the issue of reliability and we use video quality assessment as an example for the proposed best practices, showing that our recommended two-stage QoE crowdtesting design leads to more reliable results.},
  author = {Hoßfeld, Tobias and Keimel, Christian and Hirth, Matthias and Gardlo, Bruno and Habigt, Julian and Diepold, Klaus and Tran-Gia, Phuoc},
  journal = {Transactions on Multimedia},
  keywords = {myown sys:hidden:article crowdsourcing-design oekonet},
  month = 2,
  title = {Best Practices for QoE Crowdtesting: QoE Assessment with Crowdsourcing},
  volume = 16,
  year = 2014
}

Schwerdel, D., Reuther, B., Zinner, T., Müller, P., Tran-Gia, P.: Future Internet Research and Experimentation: The G-Lab Approach. Computer Networks. (2014).

[ Abstract ] [ BibTeX ] [ EndNote ]

Hoßfeld, T.: On Training the Crowd for Subjective Quality Studies. VQEG eLetter. 1, (2014).

[ Abstract ] [ BibTeX ] [ EndNote ]

Zinner, T., Hoßfeld, T., Fiedler, M., Liers, F., Volkert, T., Khondoker, R., Schatz, R.: Requirement Driven Prospects for Realizing User-Centric Network Orchestration. Multimedia Tools and Applications. (2014).

[ Abstract ] [ BibTeX ] [ EndNote ]

@article{info3-article-2014-122,
  abstract = {The Internet’s infrastructure shows severe limitations when an optimal end user experience for multimedia applications should be achieved in a resource-efficiently way. In order to realize truly user-centric networking, an information exchange between applications and networks is required. To this end, network-application interfaces need to be deployed that enable a better mediation of application data through the Internet. For smart multimedia applications and services, the application and the network should directly communicate with each other and exchange information in order to ensure an optimal Quality of Experience (QoE). In this article, we follow a use-case driven approach towards user-centric network orchestration. We derive user, application, and network requirements for three complementary use cases: HD live TV streaming, video-on-demand streaming and user authentication with high security and privacy demands, as typically required for payed multimedia services. We provide practical guidelines for achieving an optimal QoE efficiently in the context of these use cases. Based on these results, we demonstrate how to overcome one of the main limitations of today’s Internet by introducing the major steps required for user-centric network orchestration. Finally, we show conceptual prospects for realizing these steps by discussing a possible implementation with an inter-network architecture based on functional blocks.},
  author = {Zinner, Thomas and Hoßfeld, Tobias and Fiedler, Markus and Liers, Florian and Volkert, Thomas and Khondoker, Rahamatullah and Schatz, Raimund},
  journal = {Multimedia Tools and Applications},
  keywords = {myown sys:hidden:article},
  month = 6,
  title = {Requirement Driven Prospects for Realizing User-Centric Network Orchestration},
  year = 2014
}

Hoßfeld, T., Burger, V., Hinrichsen, H., Hirth, M., Tran-Gia, P.: On the computation of entropy production in stationary social networks. Social Network Analysis and Mining. 4, (2014).

[ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]

@article{info3-article-2014-123,
  abstract = {Completing their initial phase of rapid growth, social networks are expected to reach a plateau from where on they are in a statistically stationary state. Such stationary conditions may have different dynamical properties. For example, if each message in a network is followed by a reply in opposite direction, the dynamics is locally balanced. Otherwise, if messages are ignored or forwarded to a different user, one may reach a stationary state with a directed flow of information. To distinguish between the two situations, we propose a quantity called entropy production that was introduced in statistical physics as a measure for non-vanishing probability currents in nonequilibrium stationary states. The proposed quantity closes a gap for characterizing online social networks. As major contribution, we show the relation and difference between entropy production and existing metrics. The comparison shows that computational intensive metrics like centrality can be approximated by entropy production for typical online social networks. To compute the entropy production from real-world measurements, the need for Bayesian inference and the limits of naïve estimates for those probability currents are shown. As further contribution, a general scheme is presented to measure the entropy production in small-world networks using Bayesian inference. The scheme is then applied for a specific example of the R mailing list.},
  author = {Hoßfeld, Tobias and Burger, Valentin and Hinrichsen, Haye and Hirth, Matthias and Tran-Gia, Phuoc},
  journal = {Social Network Analysis and Mining},
  keywords = {myown sys:hidden:article smartenit SoNetAn},
  month = 4,
  title = {On the computation of entropy production in stationary social networks},
  volume = 4,
  year = 2014
}

Hoßfeld, T., Seufert, M., Sieber, C., Zinner, T., Tran-Gia, P.: Close to Optimum? User-centric Evaluation of Adaptation Logics for HTTP Adaptive Streaming. PIK - Praxis der Informationsverarbeitung und Kommunikation. 37, 275–285 (2014).

[ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]

@article{info3-article-2014-127,
  abstract = {HTTP Adaptive Streaming (HAS) is the de-facto standard for over-the-top (OTT) video streaming services. It allows to react to fluctuating network conditions on short time scales by adapting the video bit rate in order to avoid stalling of the video playback. With HAS the video content is split into small segments of a few seconds playtime each, which are available in different bit rates, i.e., quality level representations. Depending on the current conditions, the adaptation algorithm on the client side chooses the appropriate quality level and downloads the respective segment. This allows to avoid stalling, which is seen as the worst possible disturbance of HTTP video streaming, to the most possible extend. Nevertheless, the user perceived Quality of Experience (QoE) may be affected, namely by playing back lower qualities and by switching between different qualities. Therefore, adaptation algorithms are desired which maximize the user’sQoEfor the currently available network resources. Many downloading strategies have been proposed in literature, but a solid user-centric comparison of these mechanisms among each other and with the global optimum is missing. The major contributions of this work are as follows. A proper analysis of the influence of quality switches and played out representations on QoE is conducted by means of subjective user studies. The results suggest that, in order to optimize QoE, first, the quality level of the video stream has to be maximized and second, the number of quality switches should be minimized. Based on our findings, a QoEoptimization problem is formulated and the performance of our proposed algorithm is compared to other algorithms and to the QoE-optimal adaptation.},
  author = {Hoßfeld, Tobias and Seufert, Michael and Sieber, Christian and Zinner, Thomas and Tran-Gia, Phuoc},
  journal = {PIK - Praxis der Informationsverarbeitung und Kommunikation},
  keywords = {myown sys:hidden:article oekonet smartenit},
  month = 10,
  pages = {275-285},
  title = {Close to Optimum? User-centric Evaluation of Adaptation Logics for HTTP Adaptive Streaming},
  volume = 37,
  year = 2014
}

%0 Journal Article
%1 info3-article-2014-127
%A Hoßfeld, Tobias
%A Seufert, Michael
%A Sieber, Christian
%A Zinner, Thomas
%A Tran-Gia, Phuoc
%D 2014
%J PIK - Praxis der Informationsverarbeitung und Kommunikation
%P 275-285
%T Close to Optimum? User-centric Evaluation of Adaptation Logics for HTTP Adaptive Streaming
%V 37
%X HTTP Adaptive Streaming (HAS) is the de-facto standard for over-the-top (OTT) video streaming services. It allows to react to fluctuating network conditions on short time scales by adapting the video bit rate in order to avoid stalling of the video playback. With HAS the video content is split into small segments of a few seconds playtime each, which are available in different bit rates, i.e., quality level representations. Depending on the current conditions, the adaptation algorithm on the client side chooses the appropriate quality level and downloads the respective segment. This allows to avoid stalling, which is seen as the worst possible disturbance of HTTP video streaming, to the most possible extend. Nevertheless, the user perceived Quality of Experience (QoE) may be affected, namely by playing back lower qualities and by switching between different qualities. Therefore, adaptation algorithms are desired which maximize the user’sQoEfor the currently available network resources. Many downloading strategies have been proposed in literature, but a solid user-centric comparison of these mechanisms among each other and with the global optimum is missing. The major contributions of this work are as follows. A proper analysis of the influence of quality switches and played out representations on QoE is conducted by means of subjective user studies. The results suggest that, in order to optimize QoE, first, the quality level of the video stream has to be maximized and second, the number of quality switches should be minimized. Based on our findings, a QoEoptimization problem is formulated and the performance of our proposed algorithm is compared to other algorithms and to the QoE-optimal adaptation.

Hoßfeld, T., Timmerer, C.: Quality of Experience Assessment using Crowdsourcing. IEEE COMSOC MMTC R-Letter. 5, (2014).

[ Abstract ] [ BibTeX ] [ EndNote ]

Hoßfeld, T., Keimel, C., Timmerer, C.: Crowdsourcing Quality-of-Experience Assessments. IEEE Computer. 47, 98–102 (2014).

[ Abstract ] [ BibTeX ] [ EndNote ]

Pham Ngoc, N., Nguyen Huu, T., Vu Quang, T., Tran Hoang, V., Truong Thu, H., Tran-Gia, P., Schwartz, C.: A new power profiling method and power scaling mechanism for energy-aware NetFPGA gigabit router. Computer Networks. (2014).

[ Abstract ] [ BibTeX ] [ EndNote ]

@article{info3-article-2014-133,
  abstract = {Today the ICT industry accounts for 2–4% of the worldwide carbon emissions that are estimated to double in a business-as-usual scenario by 2020. A remarkable part of the large energy volume consumed in the Internet today is due to the over-provisioning of network resources such as routers, switches and links to meet the stringent requirements on reliability. Therefore, performance and energy issues are important factors in designing gigabit routers for future networks. However, the design and prototyping of energy-efficient routers is challenging because of multiple reasons, such as the lack of power measurements from live networks and a good understanding of how the energy consumption varies under different traffic loads and switch/router configuration settings. Moreover, the exact energy saving level gained by adopting different energy-efficient techniques in different hardware prototypes is often poorly known. In this article, we first propose a measurement framework that is able to quantify and profile the detailed energy consumption of sub-components in the NetFPGA OpenFlow switch. We then propose a new power-scaling algorithm that can adapt the operational clock frequencies as well as the corresponding energy consumption of the FPGA core and the Ethernet ports to the actual traffic load. We propose a new energy profiling method, which allows studying the detailed power performance of network devices. Results show that our energy efficient solution obtains higher level of energy efficiency compared to some existing approaches as the upper and lower bounds of power consumption of the NetFPGA Openflow switch are proved to be 30% lower than ones of the commercial HP Enterprise switch. Moreover, the new switch architecture can save up to 97% of dynamic power consumption of the FPGA chip at lowest frequency mode.},
  author = {Pham Ngoc, Nam and Nguyen Huu, Thanh and Vu Quang, Trong and Tran Hoang, Vu and Truong Thu, Huong and Tran-Gia, Phuoc and Schwartz, Christian},
  journal = {Computer Networks},
  keywords = {myown sys:hidden:article},
  title = {A new power profiling method and power scaling mechanism for energy-aware NetFPGA gigabit router},
  year = 2014
}

%0 Journal Article
%1 info3-article-2014-133
%A Pham Ngoc, Nam
%A Nguyen Huu, Thanh
%A Vu Quang, Trong
%A Tran Hoang, Vu
%A Truong Thu, Huong
%A Tran-Gia, Phuoc
%A Schwartz, Christian
%D 2014
%J Computer Networks
%T A new power profiling method and power scaling mechanism for energy-aware NetFPGA gigabit router
%X Today the ICT industry accounts for 2–4% of the worldwide carbon emissions that are estimated to double in a business-as-usual scenario by 2020. A remarkable part of the large energy volume consumed in the Internet today is due to the over-provisioning of network resources such as routers, switches and links to meet the stringent requirements on reliability. Therefore, performance and energy issues are important factors in designing gigabit routers for future networks. However, the design and prototyping of energy-efficient routers is challenging because of multiple reasons, such as the lack of power measurements from live networks and a good understanding of how the energy consumption varies under different traffic loads and switch/router configuration settings. Moreover, the exact energy saving level gained by adopting different energy-efficient techniques in different hardware prototypes is often poorly known. In this article, we first propose a measurement framework that is able to quantify and profile the detailed energy consumption of sub-components in the NetFPGA OpenFlow switch. We then propose a new power-scaling algorithm that can adapt the operational clock frequencies as well as the corresponding energy consumption of the FPGA core and the Ethernet ports to the actual traffic load. We propose a new energy profiling method, which allows studying the detailed power performance of network devices. Results show that our energy efficient solution obtains higher level of energy efficiency compared to some existing approaches as the upper and lower bounds of power consumption of the NetFPGA Openflow switch are proved to be 30% lower than ones of the commercial HP Enterprise switch. Moreover, the new switch architecture can save up to 97% of dynamic power consumption of the FPGA chip at lowest frequency mode.

10.

Metzger, F., Rafetseder, A., Romirer-Maierhofer, P., Tutschku, K.: Exploratory Analysis of a GGSN’s PDP Context Signaling Load. Journal of Computer Networks and Communications. (2014).

[ BibTeX ] [ EndNote ]

11.

Jarschel, M., Zinner, T., Hoßfeld, T., Tran-Gia, P., Kellerer, W.: Interfaces, Attributes, and Use Cases: A Compass for SDN. IEEE Communications Magazine. 52, 210–217 (2014).

[ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]

2013 [ to top ]

Hoefling, M., Menth, M., Hartmann, M.: A Survey of Mapping Systems for Locator/Identifier Split Internet Routing. IEEE Communications Surveys & Tutorials. 14, 1842–1858 (2013).

[ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]

Lehrieder, F., Menth, M.: RCFT: A Termination Method for Simple PCN-Based Flow Control. Journal of Network and Systems Management. (2013).

[ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]

@article{info3-article-2013-107,
  abstract = {Pre-congestion notification (PCN) conveys information about load conditions in Differentiated Services IP networks to boundary nodes. This information is currently used for admission control and flow termination. Flow termination complements admission control, e.g., in case of failures when admitted traffic is rerouted and causes overload on backup paths. Existing approaches for PCN-based admission control and flow termination operate on ingress-egress aggregates and rely on a signalling protocol that regularly reports measured PCN feedback from all egress nodes to all ingress nodes. However, this signalling protocol is neither defined nor available, and the methods have also other intrinsic shortcomings that result from their operations on ingress-egress aggregates. While there is already a PCN-based admission control method that works without additional signalling of measured PCN feedback, a solid flow termination method with that property is still missing. In this paper we present the novel regular-check-based flow termination method (RCFT). It does not rely on measured PCN feedback, fills the identified gap, and allows for a PCN architecture without signalling of measured feedback. We explain RCFT in detail and investigate its termination behavior under various conditions. Moreover, we study the use of PCN-based flow control for on/off traffic. These results are of general nature and apply to any system using PCN-based flow termination.},
  author = {Lehrieder, Frank and Menth, Michael},
  journal = {Journal of Network and Systems Management},
  keywords = {myown sys:hidden:article},
  title = {RCFT: A Termination Method for Simple PCN-Based Flow Control},
  year = 2013
}

Schwartz, C., Hoßfeld, T., Lehrieder, F., Tran-Gia, P.: Angry Apps: The Impact of Network Timer Selection on Power Consumption, Signalling Load, and Web QoE. Journal of Computer Networks and Communications. 1–22 (2013).

[ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]

@article{info3-article-2013-108,
  abstract = {The popularity of smartphones and mobile applications has experienced a considerable growth during recent years and this growth is expected to continue in the future. Since smartphones have only very limited energy resources, battery efficiency is one of the deter- mining factors for a good user experience. Therefore, some smartphones tear down connec- tions to the mobile network soon after a completed data transmission to reduce the power consumption of their transmission unit. However, frequent connection re-establishments caused by apps which send or receive small amounts of data often lead to a heavy signalling load within the mobile network. One of the major contributions of this article is the investigation of the resulting trade-off between energy consumption at the smartphone and the generated signalling traffic in the mobile network. We explain that this trade-off can be controlled by the connection release timeout and study the impact of this parameter for a number of popular apps that cover a wide range of traffic characteristics in terms of bandwidth requirements and resulting signalling traffic. Finally, we study the impact of the timer settings on QoE for web traffic. This is an important aspect since connection establishments do not only lead to signalling traffic, but they also increase the load time of web pages.},
  author = {Schwartz, Christian and Hoßfeld, Tobias and Lehrieder, Frank and Tran-Gia, Phuoc},
  journal = {Journal of Computer Networks and Communications},
  keywords = {myown sys:hidden:article},
  month = 9,
  pages = {1 - 22},
  title = {Angry Apps: The Impact of Network Timer Selection on Power Consumption, Signalling Load, and Web QoE},
  year = 2013
}

Wamser, F., Hock, D., Seufert, M., Staehle, B., Pries, R., Tran-Gia, P.: Using Buffered Playtime for QoE-Oriented Resource Management of YouTube Video Streaming. Transactions on Emerging Telecommunications Technologies. 24, 288–302 (2013).

[ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]

Menth, M., Hartmann, M., Klein, D.: Global Locator, Local Locator, and Identifier Split (GLI-Split). Future Internet. 5, 67–94 (2013).

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Hock, D., Wamser, F., Seufert, M., Pries, R., Tran-Gia, P.: OC²E²AN: Optimized Control Center for Experience Enhancements in Access Networks. PIK - Praxis der Informationsverarbeitung und Kommunikation. 36, 40 (2013).

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Klein, D., Tran-Gia, P., Hartmann, M.: Aktuelles Schlagwort: Big Data. Informatik-Spektrum. 36, 319–323 (2013).

[ Abstract ] [ BibTeX ] [ EndNote ]

Tran-Gia, P., Hoßfeld, T., Hartmann, M., Hirth, M.: Crowdsourcing and its Impact on Future Internet Usage. it - Information Technology. 55, 139–145 (2013).

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Casas, P., Seufert, M., Schatz, R.: YOUQMON: A System for On-line Monitoring of YouTube QoE in Operational 3G Networks. ACM SIGMETRICS Performance Evaluation Review. 41, 44–46 (2013).

[ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]

10.

Zinner, T., Hoßfeld, T., Tran-Gia, P., Kellerer, W.: Software defined Networks - Das Internet flexibler gestalten und dynamischer steuern. ITG Mitgliederbeilage / VDE dialog (invited article). 6–9 (2013).

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11.

Hoßfeld, T., Hirth, M., Tran-Gia, P.: Crowdsourcing - Modell einer neuen Arbeitswelt im Internet. Informatik Spektrum, Wirtschaftsinformatik & Management. 5, (2013).

[ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]

12.

Nguyen, H.-T., Pham Ngoc, N., Truong, T.-H., Tran Ngoc, T., Nguyen Minh, D., Giang Nguyen, V., Nguyen, T.-H., Ngo Quynh, T., Hock, D., Schwartz, C.: Modeling and Experimenting Combined Smart Sleep and Power Scaling Algorithms in Energy-aware Data Center Networks. Simulation Modelling Practice and Theory. 39, (2013).

[ BibTeX ] [ EndNote ]

13.

Hock, D., Hartmann, M., Menth, M., Pióro, M., Tomaszewski, A., Żukowski, C.: Comparison of IP-Based and Explicit Paths for One-to-One Fast Reroute in MPLS Networks. Telecommunication Systems (TS) Journal. 52, 947–958 (2013).

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14.

Rafetseder, A., Metzger, F., Pühringer, L., Tutschku, K., Zhuang, Y., Cappos, J.: Sensorium – A Generic Sensor Framework. PIK - Praxis der Informationsverarbeitung und Kommunikation. 36, (2013).

[ BibTeX ] [ EndNote ]

2012 [ to top ]

Fiedler, M., Hoßfeld, T., Norros, I., Rodrigues, J., Rogério Pereira, P.: The Network of Excellence Euro-NF and its Specific Joint Research Projects. ICST Global Community Magazine. (2012).

[ Abstract ] [ BibTeX ] [ EndNote ]

Pussep, K., Lehrieder, F., Gross, C., Oechsner, S., Guenther, M., Meyer, S.: Cooperative Traffic Management for Video Streaming Overlays. Computer Networks. 56(3), 1118–1130 (2012).

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Hirth, M., Hoßfeld, T., Tran-Gia, P.: Analyzing Costs and Accuracy of Validation Mechanisms for Crowdsourcing Platforms. Mathematical and Computer Modelling. (2012).

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Lehrieder, F., Dán, G., Hoßfeld, T., Oechsner, S., Singeorzan, V.: Caching for BitTorrent-like P2P Systems: A Simple Fluid Model and its Implications. IEEE/ACM Transactions on Networking. 20(4), (2012).

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Hoßfeld, T., Schatz, R., Varela, M., Timmerer, C.: Challenges of QoE Management for Cloud Applications. IEEE Communications Magazine. April issue, (2012).

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Menth, M., Lehrieder, F.: Performance of PCN-Based Admission Control under Challenging Conditions. IEEE/ACM Transactions on Networking. 20(2), 422–435 (2012).

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Jarschel, M., Schlosser, D., Scheuring, S., Hoßfeld, T.: Gaming in the clouds: QoE and the users’ perspective. Mathematical and Computer Modelling. (2012).

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Biernacki, A., Metzger, F., Tutschku, K.: On the influence of network impairments on YouTube video streaming. Journal of Telecommunications and Information Technology. (2012).

[ Abstract ] [ BibTeX ] [ EndNote ]

Hoßfeld, T., Liers, F., Schatz, R., Staehle, B., Staehle, D., Volkert, T., Wamser, F.: Quality of Experience Management for YouTube: Clouds, FoG and the AquareYoum. PIK - Praxis der Informationverarbeitung und -kommunikation (PIK). (2012).

[ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]

@article{info3-article-2012-103,
  abstract = {Over the last decade, Quality of Experience (QoE) has become a new, central paradigm for understanding the quality of networks and services. In particular, the concept has attracted the interest of communication network and service providers, since being able to guarantee good QoE to customers provides an opportunity for differentiation. In this paper we investigate the potential as well as the implementation challenges of QoE management in the Internet. Using YouTube video streaming service as example, we discuss the different elements that are required for the realization of the paradigm-shift towards truly user-centric network orchestration. To this end, we elaborate QoE management requirements for two complementary network scenarios (wireless mesh Internet access networks vs. global Internet delivery) and provide a QoE model for YouTube taking into account impairments like stalling and initial delay. We present two YouTube QoE monitoring approaches operating on the network and the end user level. Finally, we demonstrate how QoE can be dynamically optimized in both network scenarios with two exemplary concepts, AquareYoum and FoG, respectively. Our results show how QoE management can truly improve the user experience while at the same time increase the efficiency of network resource allocation.},
  author = {Hoßfeld, Tobias and Liers, Florian and Schatz, Raimund and Staehle, Barbara and Staehle, Dirk and Volkert, Thomas and Wamser, Florian},
  journal = {PIK - Praxis der Informationverarbeitung und -kommunikation (PIK)},
  keywords = {myown sys:hidden:article aquareyoum demobenefit dessert multinext},
  month = 8,
  title = {Quality of Experience Management for YouTube: Clouds, FoG and the AquareYoum},
  year = 2012
}

10.

Hoßfeld, T., Hirth, M., Tran-Gia, P.: Aktuelles Schlagwort: Crowdsourcing. Informatik Spektrum. 35, (2012).

[ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]

Seit der Öffnung des Internets für die Allgemeinheit Anfang der 90er Jahre hat eine rasante Entwicklung stattgefunden. Neue Paradigmen wie Peer-to-Peer (P2P), Web 2.0 oder Cloud Computing führen zu neuartigen Diensten und Anwendungen, welche bei den Anwendern längst etabliert sind und einen Großteil des Datenverkehrs im Internet ausmachen. Beispiele hierfür sind unter anderem P2P-Anwendungen wie BitTorrent zum Austausch riesiger Datenmengen, Skype für Sprach- und Videokonferenzen, Soziale Medien wie Facebook oder Twitter, Cloud Anwendungen wie DropBox als synchronisiertes Netzwerk-Dateisystem für verteilte Rechner oder Cloud Gaming. Aktuell taucht ein neues Schlagwort im Internet auf: „Crowdsourcing“. Einige Aufgaben und Probleme, die für Menschen relativ einfach zu lösen sind, können derzeit selbst von modernen Machine Clouds noch nicht algorithmisch bewältigt werden. Hierzu zählen etwa Text- und Bilderkennung, das Verifizieren, Analysieren und Kategorisieren von Videoinhalten, das Schaffen von Wissen, das Verbessern und Kreieren von Produkten oder wissenschaftliche Forschung. Diese stellen Anwendungsgebiete von Crowdsourcing dar. Statt (oder zusätzlich zu) Machine Clouds wird die Masse der Internetnutzer in die Wertschöpfungskette eingebunden. Man spricht hier auch von Human Clouds. Neben Sozialen Medien ist Crowdsourcing eine der wichtigsten aktuell aufstrebenden Technologien und Geschäftsmodelle im Internet, die die Zukunft des Arbeitens und der Arbeitsorganisation von Grund auf verändern wird. Die wirtschaftliche und gesellschaftliche Bedeutung von Crowdsourcing-Plattformen wächst ständig und fördert die Entstehung neuer Formen der Arbeitsorganisation. Jobs in Crowdsourcing-Plattformen besitzen eine viel kleinere Granularität im Vergleich zu denen im traditionellen Outsourcing bzw. Outtasking Bereich. Das Aktuelle Schlagwort beleuchtet den Begriff „Crowdsourcing“ näher und wird zunächst wichtige Begriffe einführen, bevor die Anwendungsgebiete von Crowdsourcing sowie dessen Bedeutung in der Praxis und zukünftige Weiterentwicklung betrachtet werden.

@article{info3-article-2012-102,
  abstract = {Seit der Öffnung des Internets für die Allgemeinheit Anfang der 90er Jahre hat eine rasante Entwicklung stattgefunden. Neue Paradigmen wie Peer-to-Peer (P2P), Web 2.0 oder Cloud Computing führen zu neuartigen Diensten und Anwendungen, welche bei den Anwendern längst etabliert sind und einen Großteil des Datenverkehrs im Internet ausmachen. Beispiele hierfür sind unter anderem P2P-Anwendungen wie BitTorrent zum Austausch riesiger Datenmengen, Skype für Sprach- und Videokonferenzen, Soziale Medien wie Facebook oder Twitter, Cloud Anwendungen wie DropBox als synchronisiertes Netzwerk-Dateisystem für verteilte Rechner oder Cloud Gaming. Aktuell taucht ein neues Schlagwort im Internet auf: „Crowdsourcing“. Einige Aufgaben und Probleme, die für Menschen relativ einfach zu lösen sind, können derzeit selbst von modernen Machine Clouds noch nicht algorithmisch bewältigt werden. Hierzu zählen etwa Text- und Bilderkennung, das Verifizieren, Analysieren und Kategorisieren von Videoinhalten, das Schaffen von Wissen, das Verbessern und Kreieren von Produkten oder wissenschaftliche Forschung. Diese stellen Anwendungsgebiete von Crowdsourcing dar. Statt (oder zusätzlich zu) Machine Clouds wird die Masse der Internetnutzer in die Wertschöpfungskette eingebunden. Man spricht hier auch von Human Clouds. Neben Sozialen Medien ist Crowdsourcing eine der wichtigsten aktuell aufstrebenden Technologien und Geschäftsmodelle im Internet, die die Zukunft des Arbeitens und der Arbeitsorganisation von Grund auf verändern wird. Die wirtschaftliche und gesellschaftliche Bedeutung von Crowdsourcing-Plattformen wächst ständig und fördert die Entstehung neuer Formen der Arbeitsorganisation. Jobs in Crowdsourcing-Plattformen besitzen eine viel kleinere Granularität im Vergleich zu denen im traditionellen Outsourcing bzw. Outtasking Bereich. Das Aktuelle Schlagwort beleuchtet den Begriff „Crowdsourcing“ näher und wird zunächst wichtige Begriffe einführen, bevor die Anwendungsgebiete von Crowdsourcing sowie dessen Bedeutung in der Praxis und zukünftige Weiterentwicklung betrachtet werden.},
  author = {Hoßfeld, Tobias and Hirth, Matthias and Tran-Gia, Phuoc},
  journal = {Informatik Spektrum},
  keywords = {myown sys:hidden:article},
  month = 4,
  title = {Aktuelles Schlagwort: Crowdsourcing},
  volume = 35,
  year = 2012
}

%0 Journal Article
%1 info3-article-2012-102
%A Hoßfeld, Tobias
%A Hirth, Matthias
%A Tran-Gia, Phuoc
%D 2012
%J Informatik Spektrum
%T Aktuelles Schlagwort: Crowdsourcing
%V 35
%X Seit der Öffnung des Internets für die Allgemeinheit Anfang der 90er Jahre hat eine rasante Entwicklung stattgefunden. Neue Paradigmen wie Peer-to-Peer (P2P), Web 2.0 oder Cloud Computing führen zu neuartigen Diensten und Anwendungen, welche bei den Anwendern längst etabliert sind und einen Großteil des Datenverkehrs im Internet ausmachen. Beispiele hierfür sind unter anderem P2P-Anwendungen wie BitTorrent zum Austausch riesiger Datenmengen, Skype für Sprach- und Videokonferenzen, Soziale Medien wie Facebook oder Twitter, Cloud Anwendungen wie DropBox als synchronisiertes Netzwerk-Dateisystem für verteilte Rechner oder Cloud Gaming. Aktuell taucht ein neues Schlagwort im Internet auf: „Crowdsourcing“. Einige Aufgaben und Probleme, die für Menschen relativ einfach zu lösen sind, können derzeit selbst von modernen Machine Clouds noch nicht algorithmisch bewältigt werden. Hierzu zählen etwa Text- und Bilderkennung, das Verifizieren, Analysieren und Kategorisieren von Videoinhalten, das Schaffen von Wissen, das Verbessern und Kreieren von Produkten oder wissenschaftliche Forschung. Diese stellen Anwendungsgebiete von Crowdsourcing dar. Statt (oder zusätzlich zu) Machine Clouds wird die Masse der Internetnutzer in die Wertschöpfungskette eingebunden. Man spricht hier auch von Human Clouds. Neben Sozialen Medien ist Crowdsourcing eine der wichtigsten aktuell aufstrebenden Technologien und Geschäftsmodelle im Internet, die die Zukunft des Arbeitens und der Arbeitsorganisation von Grund auf verändern wird. Die wirtschaftliche und gesellschaftliche Bedeutung von Crowdsourcing-Plattformen wächst ständig und fördert die Entstehung neuer Formen der Arbeitsorganisation. Jobs in Crowdsourcing-Plattformen besitzen eine viel kleinere Granularität im Vergleich zu denen im traditionellen Outsourcing bzw. Outtasking Bereich. Das Aktuelle Schlagwort beleuchtet den Begriff „Crowdsourcing“ näher und wird zunächst wichtige Begriffe einführen, bevor die Anwendungsgebiete von Crowdsourcing sowie dessen Bedeutung in der Praxis und zukünftige Weiterentwicklung betrachtet werden.

11.

Felipe Botero, J., Hesselbach, X., Duelli, M., Schlosser, D., Fischer, A., de Meer, H.: Energy Efficient Virtual Network Embedding. IEEE Communication Letters. PP, (2012).

[ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]

2011 [ to top ]

Duelli, M., Ott, J., Qin, X., Weber, E.: MuLaNEO: Planung und Optimierung von Mehrdienstnetzen. PIK - Praxis der Informationsverarbeitung und Kommunikation. 34, 138–139 (2011).

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Zinner, T., Tutschku, K., Nakao, A., Tran-Gia, P.: Performance Evaluation of Packet Re-ordering on Concurrent Multipath Transmissions for Transport Virtualization. JCNDS Special Issue on: Network Virtualization - Concepts and Performance Aspects. Vol. 6, 322–340 (2011).

[ Abstract ] [ BibTeX ] [ EndNote ]

Lehrieder, F., Oechsner, S., Hoßfeld, T., Staehle, D., Despotovic, Z., Kellerer, W., Michel, M.: Mitigating Unfairness in Locality-Aware Peer-to-Peer Networks. International Journal of Network Management (IJNM), Special Issue on Economic Traffic Management. 21(1), (2011).

[ Abstract ] [ BibTeX ] [ EndNote ] [ Download ]

@article{info3-article-2011-82,
  abstract = {Locality-awareness is considered as a promising approach to increase the efficiency of content distribution by peer-to-peer (P2P) networks, e.g., BitTorrent. It is intended to reduce the inter-domain traffic which is costly for Internet service providers (ISPs) and to simultaneously increase the performance from the viewpoint of the P2P users, i.e., to shorten download times. This win-win situation should be achieved by a preferred exchange of information between peers which are located closely to each other in the underlying network topology. A set of studies shows that these approaches can lead to a win-win situation under certain conditions, and to a win-no lose situation in most cases. However, the scenarios used mostly assume homogeneous peer distributions. This is not the case in practice according to recent measurement studies. Therefore, we extend previous work in this paper by studying scenarios with real-life, skewed peer distributions. We show that even a win-no lose situation is difficult to achieve under those conditions and that the actual impact for a specific peer heavily depends on the used locality-aware peer selection and the specific scenario. This contradicts the principle of economic traffic management (ETM) which aims for a solution where all involved players benefit and consequently have an incentive to adopt locality-awareness. Therefore, we propose and evaluate refinements of current proposals, achieving that all users of P2P networks can be sure that their application performance is not reduced. This mitigates the unfairness introduced by current proposals which is a key requirement for a broad acceptance of the concept of locality-awareness in the user community of P2P networks.},
  author = {Lehrieder, Frank and Oechsner, Simon and Hoßfeld, Tobias and Staehle, Dirk and Despotovic, Zoran and Kellerer, Wolfgang and Michel, Maximilian},
  journal = {International Journal of Network Management (IJNM), Special Issue on Economic Traffic Management},
  keywords = {myown sys:hidden:article},
  month = 1,
  title = {Mitigating Unfairness in Locality-Aware Peer-to-Peer Networks},
  volume = {21(1)},
  year = 2011
}

%0 Journal Article
%1 info3-article-2011-82
%A Lehrieder, Frank
%A Oechsner, Simon
%A Hoßfeld, Tobias
%A Staehle, Dirk
%A Despotovic, Zoran
%A Kellerer, Wolfgang
%A Michel, Maximilian
%D 2011
%J International Journal of Network Management (IJNM), Special Issue on Economic Traffic Management
%T Mitigating Unfairness in Locality-Aware Peer-to-Peer Networks
%V 21(1)
%X Locality-awareness is considered as a promising approach to increase the efficiency of content distribution by peer-to-peer (P2P) networks, e.g., BitTorrent. It is intended to reduce the inter-domain traffic which is costly for Internet service providers (ISPs) and to simultaneously increase the performance from the viewpoint of the P2P users, i.e., to shorten download times. This win-win situation should be achieved by a preferred exchange of information between peers which are located closely to each other in the underlying network topology. A set of studies shows that these approaches can lead to a win-win situation under certain conditions, and to a win-no lose situation in most cases. However, the scenarios used mostly assume homogeneous peer distributions. This is not the case in practice according to recent measurement studies. Therefore, we extend previous work in this paper by studying scenarios with real-life, skewed peer distributions. We show that even a win-no lose situation is difficult to achieve under those conditions and that the actual impact for a specific peer heavily depends on the used locality-aware peer selection and the specific scenario. This contradicts the principle of economic traffic management (ETM) which aims for a solution where all involved players benefit and consequently have an incentive to adopt locality-awareness. Therefore, we propose and evaluate refinements of current proposals, achieving that all users of P2P networks can be sure that their application performance is not reduced. This mitigates the unfairness introduced by current proposals which is a key requirement for a broad acceptance of the concept of locality-awareness in the user community of P2P networks.

Hoßfeld, T., Lehrieder, F., Hock, D., Oechsner, S., Despotovic, Z., Kellerer, W., Michel, M.: Characterization of BitTorrent Swarms and their Distribution in the Internet. Computer Networks. 55(5), 1197–1215 (2011).

[ Abstract ] [ BibTeX ] [ EndNote ]

Pióro, M., Zotkiewicz, M., Staehle, B., Staehle, D., Yuan, D.: On Max-Min Fair Flow Optimization in Wireless Mesh Networks. Ad Hoc Networks, Special Issue on Models and Algorithms for Wireless Mesh Networks. (2011).

[ Abstract ] [ BibTeX ] [ EndNote ]

Staehle, B., Wamser, F., Hirth, M., Stezenbach, D., Staehle, D.: AquareYoum: Application and Quality of Experience-Aware Resource Management for YouTube in Wireless Mesh Networks. PIK - Praxis der Informationsverarbeitung und Kommunikation. (2011).

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Hoßfeld, T., Tran-Gia, P.: EuroView 2010: Visions of Future Generation Networks. Computer Communications Review CCR. Volume 41, Number 2, (2011).

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Menth, M., Lehrieder, F.: PCN-Based Marked Flow Termination. Computer Communications. 34, 2082–2093 (2011).

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Meier, S., Barisch, M., Kirstädter, A., Schlosser, D., Duelli, M., Jarschel, M., Hoßfeld, T., Hoffmann, K., Hoffmann, M., Kellerer, W., Khan, A., Jurca, D., Kozu, K.: Provisioning and Operation of Virtual Networks. Electronic Communications of the EASST, Kommunikation in Verteilten Systemen 2011. 37, (2011).

[ Abstract ] [ BibTeX ] [ EndNote ]

10.

Fischer, A., Felipe Botero, J., Duelli, M., Schlosser, D., Hesselbach, X., de Meer, H.: ALEVIN - A Framework to Develop, Compare, and Analyze Virtual Network Embedding Algorithms. Electronic Communications of the EASST, Kommunikation in Verteilten Systemen 2011. 37, (2011).

[ Abstract ] [ BibTeX ] [ EndNote ]

11.

Hock, D., Hartmann, M., Schwartz, C., Menth, M.: ResiLyzer: Ein Werkzeug zur Analyse der Ausfallsicherheit in paketvermittelten Kommunikationsnetzen. PIK - Praxis der Informationsverarbeitung und Kommunikation. 34, 158–159 (2011).

[ BibTeX ] [ EndNote ]

12.

Żukowski, C., Tomaszewski, A., Pióro, M., Hock, D., Hartmann, M., Menth, M.: Compact node-link formulations for the optimal single path MPLS Fast Reroute layout. Advances in Electronics and Telecommunications. 2, (2011).

[ Abstract ] [ BibTeX ] [ EndNote ]

2010 [ to top ]

Wamser, F., Pries, R., Staehle, D., Heck, K., Tran-Gia, P.: Traffic characterization of a residential wireless Internet access. Special Issue of the Telecommunication Systems (TS) Journal. 48: 1-2, (2010).

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Menth, M., Martin, R., Hartmann, M., Spörlein, U.: Efficiency of Routing and Resilience Mechanisms in Packet-Switched Communication Networks. European Transactions on Telecommunications. 21, 108–120 (2010).

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Menth, M., Hartmann, M., Martin, R., Cicic, T., Kvalbein, A.: Loop-Free Alternates and Not-Via Addresses: A Proper Combination for IP Fast Reroute?. Computer Networks. 54, 1300–1315 (2010).

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Fiedler, M., Hoßfeld, T., Tran-Gia, P.: A Generic Quantitative Relationship between Quality of Experience and Quality of Service. IEEE Network Special Issue on Improving QoE for Network Services. (2010).

[ Abstract ] [ BibTeX ] [ EndNote ]