Publications - Lehrstuhl für Informatik III

Book or Conference Proceedings

Performance Modeling and Analysis of Communication Networks. Tran-Gia, Phuoc; Hoßfeld, Tobias. In . Würzburg University Press, https://modeling.systems/, 2021.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
This textbook provides an introduction to common methods of performance modeling and analysis of communication systems. These methods form the basis of traffic engineering, teletraffic theory, and analytical system dimensioning. The fundamentals of probability theory, stochastic processes, Markov processes, and embedded Markov chains are presented. Basic queueing models are described with applications in communication networks. Advanced methods are presented that have been frequently used in recent practice, especially discrete-time analysis algorithms, or which go beyond classical performance measures such as Quality of Experience or energy efficiency. Recent examples of modern communication networks include Software Defined Networking and the Internet of Things. Throughout the book, illustrative examples are used to provide practical experience in performance modeling and analysis. Download: https://modeling.systems/

@book{info3-book-2021-1, abstract = {This textbook provides an introduction to common methods of performance modeling and analysis of communication systems. These methods form the basis of traffic engineering, teletraffic theory, and analytical system dimensioning. The fundamentals of probability theory, stochastic processes, Markov processes, and embedded Markov chains are presented. Basic queueing models are described with applications in communication networks. Advanced methods are presented that have been frequently used in recent practice, especially discrete-time analysis algorithms, or which go beyond classical performance measures such as Quality of Experience or energy efficiency. Recent examples of modern communication networks include Software Defined Networking and the Internet of Things. Throughout the book, illustrative examples are used to provide practical experience in performance modeling and analysis. Download: https://modeling.systems/}, address = {https://modeling.systems/}, author = {Tran-Gia, Phuoc and Hoßfeld, Tobias}, booktitle = {Performance Modeling and Analysis of Communication Networks}, keywords = {sys:hidden:book}, publisher = {Würzburg University Press}, title = {Performance Modeling and Analysis of Communication Networks}, year = 2021 }

%0 Book %1 info3-book-2021-1 %A Tran-Gia, Phuoc %A Hoßfeld, Tobias %B Performance Modeling and Analysis of Communication Networks %C https://modeling.systems/ %D 2021 %I Würzburg University Press %T Performance Modeling and Analysis of Communication Networks %X This textbook provides an introduction to common methods of performance modeling and analysis of communication systems. These methods form the basis of traffic engineering, teletraffic theory, and analytical system dimensioning. The fundamentals of probability theory, stochastic processes, Markov processes, and embedded Markov chains are presented. Basic queueing models are described with applications in communication networks. Advanced methods are presented that have been frequently used in recent practice, especially discrete-time analysis algorithms, or which go beyond classical performance measures such as Quality of Experience or energy efficiency. Recent examples of modern communication networks include Software Defined Networking and the Internet of Things. Throughout the book, illustrative examples are used to provide practical experience in performance modeling and analysis. Download: https://modeling.systems/
Evaluation in the Crowd. Archambault, Daniel; Purchase, Helen C; Hoßfeld, Tobias. In . Springer, 2017.
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- [ EndNote ]
@book{info3-misc-2015-1, author = {Archambault, Daniel and Purchase, Helen C and Hoßfeld, Tobias}, booktitle = {Crowdsourcing and Human-Centered Experiments}, keywords = {sys:hidden:book}, publisher = {Springer}, title = {Evaluation in the Crowd}, year = 2017 }

%0 Book %1 info3-misc-2015-1 %A Archambault, Daniel %A Purchase, Helen C %A Hoßfeld, Tobias %B Crowdsourcing and Human-Centered Experiments %D 2017 %I Springer %T Evaluation in the Crowd
Proceedings of The 28th International Teletraffic Congress 2016 (ITC 28). Hoßfeld, Tobias; Chan, Gary; Mark, Brian L.; Timm-Giel, Andreas. ITC, IEEE, ACM, Würzburg, Germany, 2016.
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- [ EndNote ]
@book{info3-book-2016-2, address = {Würzburg, Germany}, author = {Hoßfeld, Tobias and Chan, Gary and Mark, Brian L. and Timm-Giel, Andreas}, keywords = {sys:hidden:book}, month = {09}, publisher = {ITC, IEEE, ACM}, title = {Proceedings of The 28th International Teletraffic Congress 2016 (ITC 28)}, year = 2016 }

%0 Book %1 info3-book-2016-2 %A Hoßfeld, Tobias %A Chan, Gary %A Mark, Brian L. %A Timm-Giel, Andreas %C Würzburg, Germany %D 2016 %I ITC, IEEE, ACM %T Proceedings of The 28th International Teletraffic Congress 2016 (ITC 28)

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Book Chapter

Context Monitoring for Improved System Performance and QoE. Metzger, Florian; Hoßfeld, Tobias; Skorin-Kapov, Lea; Liotou, Eirini; Pocta, Peter; Melvin, Hugh; Siris, Vasilios; Zgank, Andrej; Jarschel, Michael. In Autonomous Control for a Reliable Internet of Services: Methods, Models, Approaches, Techniques, Algorithms, and Tools, I. Ganchev, R. D. van der Mei, H. van den Berg (eds.). Springer International Publishing, 2018.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
Whereas some application domains show a certain consensus on the role of system factors, human factors, and context factors, QoE management of multimedia systems and services is still faced with the challenge of identifying the key QoE influence factors. In this chapter, we focus on the potential of enhancing QoE management mechanisms by exploiting valuable context information. To get a good grip on the basics we first discuss a general framework for context monitoring and define context information, including technical, usage, social, economic, temporal, and physical factors. We then iterate the opportunities and challenges in involving context in QoE monitoring solutions, as context may be, e.g., hard to ascertain or very situational. The benefits of including context in QoE monitoring and management are demonstrated through use cases involving video flash crowds as well as online and cloud gaming. Finally, we discuss potential technical realizations of context-aware QoE monitoring and management derived based on the SDN paradigm.

@incollection{info3-incollection-2018-3, abstract = {Whereas some application domains show a certain consensus on the role of system factors, human factors, and context factors, QoE management of multimedia systems and services is still faced with the challenge of identifying the key QoE influence factors. In this chapter, we focus on the potential of enhancing QoE management mechanisms by exploiting valuable context information. To get a good grip on the basics we first discuss a general framework for context monitoring and define context information, including technical, usage, social, economic, temporal, and physical factors. We then iterate the opportunities and challenges in involving context in QoE monitoring solutions, as context may be, e.g., hard to ascertain or very situational. The benefits of including context in QoE monitoring and management are demonstrated through use cases involving video flash crowds as well as online and cloud gaming. Finally, we discuss potential technical realizations of context-aware QoE monitoring and management derived based on the SDN paradigm.}, author = {Metzger, Florian and Hoßfeld, Tobias and Skorin-Kapov, Lea and Liotou, Eirini and Pocta, Peter and Melvin, Hugh and Siris, Vasilios and Zgank, Andrej and Jarschel, Michael}, booktitle = {Autonomous Control for a Reliable Internet of Services: Methods, Models, Approaches, Techniques, Algorithms, and Tools}, editor = {Ganchev, Ivan and van der Mei, R. D. and van den Berg, Hans}, keywords = {ua-net}, month = {05}, publisher = {Springer International Publishing}, title = {Context Monitoring for Improved System Performance and QoE}, year = 2018 }

%0 Book Section %1 info3-incollection-2018-3 %A Metzger, Florian %A Hoßfeld, Tobias %A Skorin-Kapov, Lea %A Liotou, Eirini %A Pocta, Peter %A Melvin, Hugh %A Siris, Vasilios %A Zgank, Andrej %A Jarschel, Michael %B Autonomous Control for a Reliable Internet of Services: Methods, Models, Approaches, Techniques, Algorithms, and Tools %D 2018 %E Ganchev, Ivan %E van der Mei, R. D. %E van den Berg, Hans %I Springer International Publishing %T Context Monitoring for Improved System Performance and QoE %X Whereas some application domains show a certain consensus on the role of system factors, human factors, and context factors, QoE management of multimedia systems and services is still faced with the challenge of identifying the key QoE influence factors. In this chapter, we focus on the potential of enhancing QoE management mechanisms by exploiting valuable context information. To get a good grip on the basics we first discuss a general framework for context monitoring and define context information, including technical, usage, social, economic, temporal, and physical factors. We then iterate the opportunities and challenges in involving context in QoE monitoring solutions, as context may be, e.g., hard to ascertain or very situational. The benefits of including context in QoE monitoring and management are demonstrated through use cases involving video flash crowds as well as online and cloud gaming. Finally, we discuss potential technical realizations of context-aware QoE monitoring and management derived based on the SDN paradigm.
The Value of Context-Awareness in Bandwidth-Challenging HTTP Adaptive Streaming Scenarios. Liotou, Eirini; Hoßfeld, Tobias; Moldovan, Christian; Metzger, Florian; Tsolkas, Dimitris; Passas, Nikos. In Autonomous Control for a Reliable Internet of Services: Methods, Models, Approaches, Techniques, Algorithms, and Tools, I. Ganchev, R. D. van der Mei, H. van den Berg (eds.). Springer International Publishing, 2018.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
Video streaming has become an indispensable technology in people’s lives, while its usage keeps constantly increasing. The variability, instability and unpredictability of network conditions pose one of the biggest challenges to video streaming. In this chapter, we analyze HTTP Adaptive Streaming, a technology that relieves these issues by adapting the video reproduction to the current network conditions. Particularly, we study how context awareness can be combined with the adaptive streaming logic to design a proactive client-based video streaming strategy. Our results show that such a context-aware strategy manages to successfully mitigate stallings in light of network connectivity problems, such as an outage. Moreover, we analyze the performance of this strategy by comparing it to the optimal case, as well as by considering situations where the awareness of the context lacks reliability.

@incollection{info3-incollection-2018-4, abstract = {Video streaming has become an indispensable technology in people’s lives, while its usage keeps constantly increasing. The variability, instability and unpredictability of network conditions pose one of the biggest challenges to video streaming. In this chapter, we analyze HTTP Adaptive Streaming, a technology that relieves these issues by adapting the video reproduction to the current network conditions. Particularly, we study how context awareness can be combined with the adaptive streaming logic to design a proactive client-based video streaming strategy. Our results show that such a context-aware strategy manages to successfully mitigate stallings in light of network connectivity problems, such as an outage. Moreover, we analyze the performance of this strategy by comparing it to the optimal case, as well as by considering situations where the awareness of the context lacks reliability.}, author = {Liotou, Eirini and Hoßfeld, Tobias and Moldovan, Christian and Metzger, Florian and Tsolkas, Dimitris and Passas, Nikos}, booktitle = {Autonomous Control for a Reliable Internet of Services: Methods, Models, Approaches, Techniques, Algorithms, and Tools}, editor = {Ganchev, Ivan and van der Mei, R. D. and van den Berg, Hans}, keywords = {fullstack}, month = {05}, publisher = {Springer International Publishing}, title = {The Value of Context-Awareness in Bandwidth-Challenging HTTP Adaptive Streaming Scenarios}, year = 2018 }

%0 Book Section %1 info3-incollection-2018-4 %A Liotou, Eirini %A Hoßfeld, Tobias %A Moldovan, Christian %A Metzger, Florian %A Tsolkas, Dimitris %A Passas, Nikos %B Autonomous Control for a Reliable Internet of Services: Methods, Models, Approaches, Techniques, Algorithms, and Tools %D 2018 %E Ganchev, Ivan %E van der Mei, R. D. %E van den Berg, Hans %I Springer International Publishing %T The Value of Context-Awareness in Bandwidth-Challenging HTTP Adaptive Streaming Scenarios %X Video streaming has become an indispensable technology in people’s lives, while its usage keeps constantly increasing. The variability, instability and unpredictability of network conditions pose one of the biggest challenges to video streaming. In this chapter, we analyze HTTP Adaptive Streaming, a technology that relieves these issues by adapting the video reproduction to the current network conditions. Particularly, we study how context awareness can be combined with the adaptive streaming logic to design a proactive client-based video streaming strategy. Our results show that such a context-aware strategy manages to successfully mitigate stallings in light of network connectivity problems, such as an outage. Moreover, we analyze the performance of this strategy by comparing it to the optimal case, as well as by considering situations where the awareness of the context lacks reliability.
Big-Data Helps SDN to Improve Application Specific Quality of Service. Schwarzmann, Susanna; Blenk, Andreas; Dobrijevic, Ognjen; Jarschel, Michael; Hotho, Andreas; Zinner, Thomas; Wamser, Florian. In Big Data and Software Defined Networks. Institution of Engineering and Technology (IET), 2018.
- [ Abstract ]
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This chapter first provides an outline of the current results in the domains of: (a) quality-of-service (QoS) / quality-of-experience (QoE) control and management (CaM) for real-time multimedia services that is supported by software-defined networking (SDN), and (b) big data analytics and methods that are used for QoS/QoE CaM. Then, three specific use case scenarios with respect to video streaming services are presented, so as to illustrate the expected benefits of incorporating big data analytics into SDN-based CaM for the purposes of improving or optimizing QoS/QoE. In the end, we describe our vision and a high-level view of an SDN-based architecture for QoS/QoE CaM that is enriched with big data analytics' functional blocks and summarize corresponding challenges.

@incollection{info3-incollection-2018-2, abstract = {This chapter first provides an outline of the current results in the domains of: (a) quality-of-service (QoS) / quality-of-experience (QoE) control and management (CaM) for real-time multimedia services that is supported by software-defined networking (SDN), and (b) big data analytics and methods that are used for QoS/QoE CaM. Then, three specific use case scenarios with respect to video streaming services are presented, so as to illustrate the expected benefits of incorporating big data analytics into SDN-based CaM for the purposes of improving or optimizing QoS/QoE. In the end, we describe our vision and a high-level view of an SDN-based architecture for QoS/QoE CaM that is enriched with big data analytics' functional blocks and summarize corresponding challenges.}, author = {Schwarzmann, Susanna and Blenk, Andreas and Dobrijevic, Ognjen and Jarschel, Michael and Hotho, Andreas and Zinner, Thomas and Wamser, Florian}, booktitle = {Big Data and Software Defined Networks}, keywords = {dfg-sdn}, month = {03}, publisher = {Institution of Engineering and Technology (IET)}, title = {Big-Data Helps SDN to Improve Application Specific Quality of Service}, year = 2018 }

%0 Book Section %1 info3-incollection-2018-2 %A Schwarzmann, Susanna %A Blenk, Andreas %A Dobrijevic, Ognjen %A Jarschel, Michael %A Hotho, Andreas %A Zinner, Thomas %A Wamser, Florian %B Big Data and Software Defined Networks %D 2018 %I Institution of Engineering and Technology (IET) %T Big-Data Helps SDN to Improve Application Specific Quality of Service %X This chapter first provides an outline of the current results in the domains of: (a) quality-of-service (QoS) / quality-of-experience (QoE) control and management (CaM) for real-time multimedia services that is supported by software-defined networking (SDN), and (b) big data analytics and methods that are used for QoS/QoE CaM. Then, three specific use case scenarios with respect to video streaming services are presented, so as to illustrate the expected benefits of incorporating big data analytics into SDN-based CaM for the purposes of improving or optimizing QoS/QoE. In the end, we describe our vision and a high-level view of an SDN-based architecture for QoS/QoE CaM that is enriched with big data analytics' functional blocks and summarize corresponding challenges.

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