Frank Loh M. Sc.

• Generic Model to Quantify Energy Consumption for Different LoRaWAN Channel Access Methods Loh, Frank; Raffeck, Simon; Geißler, Stefan; Hoßfeld, Tobias in 18th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob) (2022).
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  LoRaWAN is one of the most promising Internet of Things technologies with regard to low energy consumption. However, the currently used random channel access has much potential for improvement. Thus, current literature studies alternative channel access approaches, but the energy consumption is often not taken into consideration. For that reason, we present a generic model to quantify energy consumption in LoRaWAN for different channel access mechanisms based on a state machine. With our model, we can describe the energy consumption for specific access mechanisms or for the complete network. Our model shows that random access only performs best if no additional receive windows are opened. A simple improvement is Listen before Talk. For networks with high load, improvements are achieved by a more complex scheduled MAC. Our model serves as a basis for future energy consumption studies, conducted through measurements or simulations.

  @inproceedings{info3-inproceedings-2022-21, abstract = {LoRaWAN is one of the most promising Internet of Things technologies with regard to low energy consumption. However, the currently used random channel access has much potential for improvement. Thus, current literature studies alternative channel access approaches, but the energy consumption is often not taken into consideration. For that reason, we present a generic model to quantify energy consumption in LoRaWAN for different channel access mechanisms based on a state machine. With our model, we can describe the energy consumption for specific access mechanisms or for the complete network. Our model shows that random access only performs best if no additional receive windows are opened. A simple improvement is Listen before Talk. For networks with high load, improvements are achieved by a more complex scheduled MAC. Our model serves as a basis for future energy consumption studies, conducted through measurements or simulations.}, author = {Loh, Frank and Raffeck, Simon and Geißler, Stefan and Hoßfeld, Tobias}, booktitle = {18th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)}, keywords = {5mart}, month = 10, title = {Generic Model to Quantify Energy Consumption for Different LoRaWAN Channel Access Methods}, year = 2022 }

  %0 Conference Paper %1 info3-inproceedings-2022-21 %A Loh, Frank %A Raffeck, Simon %A Geißler, Stefan %A Hoßfeld, Tobias %B 18th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob) %D 2022 %T Generic Model to Quantify Energy Consumption for Different LoRaWAN Channel Access Methods %X LoRaWAN is one of the most promising Internet of Things technologies with regard to low energy consumption. However, the currently used random channel access has much potential for improvement. Thus, current literature studies alternative channel access approaches, but the energy consumption is often not taken into consideration. For that reason, we present a generic model to quantify energy consumption in LoRaWAN for different channel access mechanisms based on a state machine. With our model, we can describe the energy consumption for specific access mechanisms or for the complete network. Our model shows that random access only performs best if no additional receive windows are opened. A simple improvement is Listen before Talk. For networks with high load, improvements are achieved by a more complex scheduled MAC. Our model serves as a basis for future energy consumption studies, conducted through measurements or simulations.
• LoRaWAN Network Planning in Smart Environments: Towards Reliability, Scalability, and Cost Reduction Loh, Frank; Geißler, Stefan; Hoßfeld, Tobias in WueWoWAS 22 - KuVS Fachgespräch - Würzburg Workshop on Next-Generation Communication Networks (2022).
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  The goal in this work is to present a guidance for LoRaWAN planning to improve overall reliability for message transmissions and scalability. At the end, the cost component is discussed. Therefore, a five step approach is presented that helps to plan a LoRaWAN deployment step by step: Based on the device locations, an initial gateway placement is suggested followed by in-depth frequency and channel access planning. After an initial planning phase, updates for channel access and the initial gateway planning is suggested that should also be done periodically during network operation. Since current gateway placement approaches are only studied with random channel access, there is a lot of potential in the cell planning phase. Furthermore, the performance of different channel access approaches is highly related on network load, and thus cell size and sensor density. Last, the influence of different cell planning ideas on expected costs are discussed.

  @inproceedings{info3-inproceedings-2022-20, abstract = {The goal in this work is to present a guidance for LoRaWAN planning to improve overall reliability for message transmissions and scalability. At the end, the cost component is discussed. Therefore, a five step approach is presented that helps to plan a LoRaWAN deployment step by step: Based on the device locations, an initial gateway placement is suggested followed by in-depth frequency and channel access planning. After an initial planning phase, updates for channel access and the initial gateway planning is suggested that should also be done periodically during network operation. Since current gateway placement approaches are only studied with random channel access, there is a lot of potential in the cell planning phase. Furthermore, the performance of different channel access approaches is highly related on network load, and thus cell size and sensor density. Last, the influence of different cell planning ideas on expected costs are discussed.}, author = {Loh, Frank and Geißler, Stefan and Hoßfeld, Tobias}, booktitle = {WueWoWAS 22 - KuVS Fachgespräch - Würzburg Workshop on Next-Generation Communication Networks}, keywords = {5mart}, month = 7, title = {LoRaWAN Network Planning in Smart Environments: Towards Reliability, Scalability, and Cost Reduction}, year = 2022 }

  %0 Conference Paper %1 info3-inproceedings-2022-20 %A Loh, Frank %A Geißler, Stefan %A Hoßfeld, Tobias %B WueWoWAS 22 - KuVS Fachgespräch - Würzburg Workshop on Next-Generation Communication Networks %D 2022 %T LoRaWAN Network Planning in Smart Environments: Towards Reliability, Scalability, and Cost Reduction %X The goal in this work is to present a guidance for LoRaWAN planning to improve overall reliability for message transmissions and scalability. At the end, the cost component is discussed. Therefore, a five step approach is presented that helps to plan a LoRaWAN deployment step by step: Based on the device locations, an initial gateway placement is suggested followed by in-depth frequency and channel access planning. After an initial planning phase, updates for channel access and the initial gateway planning is suggested that should also be done periodically during network operation. Since current gateway placement approaches are only studied with random channel access, there is a lot of potential in the cell planning phase. Furthermore, the performance of different channel access approaches is highly related on network load, and thus cell size and sensor density. Last, the influence of different cell planning ideas on expected costs are discussed.
• Graph-Based Gateway Placement for Better Performance in LoRaWAN Deployments Loh, Frank; Mehling, Noah; Geißler, Stefan; Hoßfeld, Tobias in 20th Mediterranean Communication and Computer Networking Conference (MedComNet) (2022).
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  Low Power Wide Area Networks with Long Range Wide Area Networks (LoRaWANs) as one of their most prominent representatives are very promising solutions for future Internet of Things deployments. The technology is characterized by low energy requirements leading to long battery lifetimes. However, the drawback is very limited throughput rates. However, the unreliable nature of the LoRa technology is hindering the adoption. Especially its random channel access approach leads to significant message collisions and thus, data loss in larger deployments. From a network planning point of view, one possibility to deal with collisions is the reduction of potentially colliding messages at the frequency bands in combination with limiting the transmission duration of messages. For that reason, we present a novel graph-based gateway placement approach. The main focus is collision probability reduction, which directly increases reliability in LoRaWAN deployments. We show that our approach performs similar to state-of-the-art related work in the worst case and reduces the required number of gateways by up to 40% while reducing the collision probability by up to 70%. Furthermore, we discuss the scalability of our approach to cover arbitrarily large networks with gateways and only little overhead by splitting the problem into smaller sub-problems.

  @inproceedings{info3-inproceedings-2022-19, abstract = {Low Power Wide Area Networks with Long Range Wide Area Networks (LoRaWANs) as one of their most prominent representatives are very promising solutions for future Internet of Things deployments. The technology is characterized by low energy requirements leading to long battery lifetimes. However, the drawback is very limited throughput rates. However, the unreliable nature of the LoRa technology is hindering the adoption. Especially its random channel access approach leads to significant message collisions and thus, data loss in larger deployments. From a network planning point of view, one possibility to deal with collisions is the reduction of potentially colliding messages at the frequency bands in combination with limiting the transmission duration of messages. For that reason, we present a novel graph-based gateway placement approach. The main focus is collision probability reduction, which directly increases reliability in LoRaWAN deployments. We show that our approach performs similar to state-of-the-art related work in the worst case and reduces the required number of gateways by up to 40% while reducing the collision probability by up to 70%. Furthermore, we discuss the scalability of our approach to cover arbitrarily large networks with gateways and only little overhead by splitting the problem into smaller sub-problems.}, author = {Loh, Frank and Mehling, Noah and Geißler, Stefan and Hoßfeld, Tobias}, booktitle = {20th Mediterranean Communication and Computer Networking Conference (MedComNet)}, keywords = {5mart}, month = 6, title = {Graph-Based Gateway Placement for Better Performance in LoRaWAN Deployments}, year = 2022 }

  %0 Conference Paper %1 info3-inproceedings-2022-19 %A Loh, Frank %A Mehling, Noah %A Geißler, Stefan %A Hoßfeld, Tobias %B 20th Mediterranean Communication and Computer Networking Conference (MedComNet) %D 2022 %T Graph-Based Gateway Placement for Better Performance in LoRaWAN Deployments %X Low Power Wide Area Networks with Long Range Wide Area Networks (LoRaWANs) as one of their most prominent representatives are very promising solutions for future Internet of Things deployments. The technology is characterized by low energy requirements leading to long battery lifetimes. However, the drawback is very limited throughput rates. However, the unreliable nature of the LoRa technology is hindering the adoption. Especially its random channel access approach leads to significant message collisions and thus, data loss in larger deployments. From a network planning point of view, one possibility to deal with collisions is the reduction of potentially colliding messages at the frequency bands in combination with limiting the transmission duration of messages. For that reason, we present a novel graph-based gateway placement approach. The main focus is collision probability reduction, which directly increases reliability in LoRaWAN deployments. We show that our approach performs similar to state-of-the-art related work in the worst case and reduces the required number of gateways by up to 40% while reducing the collision probability by up to 70%. Furthermore, we discuss the scalability of our approach to cover arbitrarily large networks with gateways and only little overhead by splitting the problem into smaller sub-problems.
• An Introduction to Online Video Game QoS and QoE Influencing Factors Metzger, Florian; Geißler, Stefan; Grigorjew, Alexej; Loh, Frank; Moldovan, Christian; Seufert, Michael; Hoßfeld, Tobias in IEEE Communications Surveys & Tutorials (2022).
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  Online video games and cloud gaming are rapidly growing in pervasiveness. Their resource demands can put significant stress on the global communication infrastructure. And network conditions are amongst the chief factors that influence one's enjoyment while playing games. This makes it imperative for video games to be considered for network dimensioning, server placement or protocol development. For that reason, in this work we provide an introduction to the technical aspects of video games in general and of their network aspects in particular. This understanding forms the basis for a rich taxonomy of factors that influence and provide context to a video game's Quality of Service (QoS) and Quality of Experience (QoE). The taxonomy covers influence factors from all aspects involved in a video game, from the subjective player and game influence factors to the system and networking influence factors. Finally, this work gives an overview of conducted and ongoing research as well as future research opportunities while taking into account lessons learned from past approaches.

  @article{info3-article-2022-16, abstract = {Online video games and cloud gaming are rapidly growing in pervasiveness. Their resource demands can put significant stress on the global communication infrastructure. And network conditions are amongst the chief factors that influence one's enjoyment while playing games. This makes it imperative for video games to be considered for network dimensioning, server placement or protocol development. For that reason, in this work we provide an introduction to the technical aspects of video games in general and of their network aspects in particular. This understanding forms the basis for a rich taxonomy of factors that influence and provide context to a video game's Quality of Service (QoS) and Quality of Experience (QoE). The taxonomy covers influence factors from all aspects involved in a video game, from the subjective player and game influence factors to the system and networking influence factors. Finally, this work gives an overview of conducted and ongoing research as well as future research opportunities while taking into account lessons learned from past approaches.}, author = {Metzger, Florian and Geißler, Stefan and Grigorjew, Alexej and Loh, Frank and Moldovan, Christian and Seufert, Michael and Hoßfeld, Tobias}, journal = {IEEE Communications Surveys & Tutorials}, keywords = {sys:hidden:article}, month = 5, title = {An Introduction to Online Video Game QoS and QoE Influencing Factors}, year = 2022 }

  %0 Journal Article %1 info3-article-2022-16 %A Metzger, Florian %A Geißler, Stefan %A Grigorjew, Alexej %A Loh, Frank %A Moldovan, Christian %A Seufert, Michael %A Hoßfeld, Tobias %D 2022 %J IEEE Communications Surveys & Tutorials %T An Introduction to Online Video Game QoS and QoE Influencing Factors %X Online video games and cloud gaming are rapidly growing in pervasiveness. Their resource demands can put significant stress on the global communication infrastructure. And network conditions are amongst the chief factors that influence one's enjoyment while playing games. This makes it imperative for video games to be considered for network dimensioning, server placement or protocol development. For that reason, in this work we provide an introduction to the technical aspects of video games in general and of their network aspects in particular. This understanding forms the basis for a rich taxonomy of factors that influence and provide context to a video game's Quality of Service (QoS) and Quality of Experience (QoE). The taxonomy covers influence factors from all aspects involved in a video game, from the subjective player and game influence factors to the system and networking influence factors. Finally, this work gives an overview of conducted and ongoing research as well as future research opportunities while taking into account lessons learned from past approaches.
• Analytical Model for the Energy Efficiency in Low Power IoT Deployments Hoßfeld, Tobias; Raffeck, Simon; Loh, Frank; Geißler, Stefan in 1st International Workshop on Network Energy Efficiency in the Softwarization Era (2022).
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  The recent rise of the Internet of Things (IoT) has given way to numerous challenges and research questions. One of the most critical issues in the area of low powered devices is the question of energy efficiency. Here, technologies like LoRa or Zigbee emerged, promising low power consumption while maintaining adequate performance. However, even when using these tailor made technologies, several configuration aspects need to be taken into account to provide high performance, energy efficient operation. To this end, we propose a generic model to compute the energy efficiency of wireless sensors under the assumption of perfect CSMA/CA channel access. We present numerical results for a typical LoRa device and highlight extensions towards other channel access mechanisms. Finally, we apply Kleinrock's power metric to obtain ideal system configurations for varying load parameters.

  @inproceedings{info3-inproceedings-2022-6, abstract = {The recent rise of the Internet of Things (IoT) has given way to numerous challenges and research questions. One of the most critical issues in the area of low powered devices is the question of energy efficiency. Here, technologies like LoRa or Zigbee emerged, promising low power consumption while maintaining adequate performance. However, even when using these tailor made technologies, several configuration aspects need to be taken into account to provide high performance, energy efficient operation. To this end, we propose a generic model to compute the energy efficiency of wireless sensors under the assumption of perfect CSMA/CA channel access. We present numerical results for a typical LoRa device and highlight extensions towards other channel access mechanisms. Finally, we apply Kleinrock's power metric to obtain ideal system configurations for varying load parameters.}, author = {Hoßfeld, Tobias and Raffeck, Simon and Loh, Frank and Geißler, Stefan}, booktitle = {1st International Workshop on Network Energy Efficiency in the Softwarization Era}, keywords = {can}, month = 6, title = {Analytical Model for the Energy Efficiency in Low Power IoT Deployments}, year = 2022 }

  %0 Conference Paper %1 info3-inproceedings-2022-6 %A Hoßfeld, Tobias %A Raffeck, Simon %A Loh, Frank %A Geißler, Stefan %B 1st International Workshop on Network Energy Efficiency in the Softwarization Era %D 2022 %T Analytical Model for the Energy Efficiency in Low Power IoT Deployments %X The recent rise of the Internet of Things (IoT) has given way to numerous challenges and research questions. One of the most critical issues in the area of low powered devices is the question of energy efficiency. Here, technologies like LoRa or Zigbee emerged, promising low power consumption while maintaining adequate performance. However, even when using these tailor made technologies, several configuration aspects need to be taken into account to provide high performance, energy efficient operation. To this end, we propose a generic model to compute the energy efficiency of wireless sensors under the assumption of perfect CSMA/CA channel access. We present numerical results for a typical LoRa device and highlight extensions towards other channel access mechanisms. Finally, we apply Kleinrock's power metric to obtain ideal system configurations for varying load parameters.
• YouTube Dataset on Mobile Streaming for Internet Traffic Modeling and Streaming Analysis Loh, Frank; Wamser, Florian; Poignée, Fabian; Geißler, Stefan; Hoßfeld, Tobias in Nature, Scientific Data (2022).
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  Around 4.9 billion Internet users worldwide watch billions of hours of online video every day. As a result, streaming is by far the predominant type of traffic in communication networks. According to Google statistics, three out of five video views come from mobile devices. Thus, in view of the continuous technological advances in end devices and increasing mobile use, datasets for mobile streaming are indispensable in research but only sparsely dealt with in literature so far. With this public dataset, we provide 1,081 hours of time-synchronous video measurements at network, transport, and application layer with the native YouTube streaming client on mobile devices. The dataset includes 80 network scenarios with 171 different individual bandwidth settings measured in 5,181 runs with limited bandwidth, 1,939 runs with emulated 3 G/4 G traces, and 4,022 runs with pre-defined bandwidth changes. This corresponds to 332 GB video payload. We present the most relevant quality indicators for scientific use, i.e., initial playback delay, streaming video quality, adaptive video quality changes, video rebuffering events, and streaming phases.

  @article{info3-article-2022-17, abstract = {Around 4.9 billion Internet users worldwide watch billions of hours of online video every day. As a result, streaming is by far the predominant type of traffic in communication networks. According to Google statistics, three out of five video views come from mobile devices. Thus, in view of the continuous technological advances in end devices and increasing mobile use, datasets for mobile streaming are indispensable in research but only sparsely dealt with in literature so far. With this public dataset, we provide 1,081 hours of time-synchronous video measurements at network, transport, and application layer with the native YouTube streaming client on mobile devices. The dataset includes 80 network scenarios with 171 different individual bandwidth settings measured in 5,181 runs with limited bandwidth, 1,939 runs with emulated 3 G/4 G traces, and 4,022 runs with pre-defined bandwidth changes. This corresponds to 332 GB video payload. We present the most relevant quality indicators for scientific use, i.e., initial playback delay, streaming video quality, adaptive video quality changes, video rebuffering events, and streaming phases.}, author = {Loh, Frank and Wamser, Florian and Poignée, Fabian and Geißler, Stefan and Hoßfeld, Tobias}, journal = {Nature, Scientific Data}, keywords = {sys:hidden:article}, month = 6, title = {YouTube Dataset on Mobile Streaming for Internet Traffic Modeling and Streaming Analysis}, year = 2022 }

  %0 Journal Article %1 info3-article-2022-17 %A Loh, Frank %A Wamser, Florian %A Poignée, Fabian %A Geißler, Stefan %A Hoßfeld, Tobias %D 2022 %J Nature, Scientific Data %T YouTube Dataset on Mobile Streaming for Internet Traffic Modeling and Streaming Analysis %X Around 4.9 billion Internet users worldwide watch billions of hours of online video every day. As a result, streaming is by far the predominant type of traffic in communication networks. According to Google statistics, three out of five video views come from mobile devices. Thus, in view of the continuous technological advances in end devices and increasing mobile use, datasets for mobile streaming are indispensable in research but only sparsely dealt with in literature so far. With this public dataset, we provide 1,081 hours of time-synchronous video measurements at network, transport, and application layer with the native YouTube streaming client on mobile devices. The dataset includes 80 network scenarios with 171 different individual bandwidth settings measured in 5,181 runs with limited bandwidth, 1,939 runs with emulated 3 G/4 G traces, and 4,022 runs with pre-defined bandwidth changes. This corresponds to 332 GB video payload. We present the most relevant quality indicators for scientific use, i.e., initial playback delay, streaming video quality, adaptive video quality changes, video rebuffering events, and streaming phases.

• Machine-Learning Based Prediction of Next HTTP Request Arrival Time in Adaptive Video Streaming Pimpinella, Andrea; Redondi, Alessandro E.C.; Loh, Frank; Seufert, Michael in 3rd International Workshop on High-Precision, Predictable, and Low-Latency Networking (HiPNet) (2021).
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  @inproceedings{info3-inproceedings-2021-18, address = {Izmir, Turkey (Virtual Conference)}, author = {Pimpinella, Andrea and Redondi, Alessandro E.C. and Loh, Frank and Seufert, Michael}, booktitle = {3rd International Workshop on High-Precision, Predictable, and Low-Latency Networking (HiPNet)}, keywords = {ucn}, month = 10, title = {Machine-Learning Based Prediction of Next HTTP Request Arrival Time in Adaptive Video Streaming}, year = 2021 }

  %0 Conference Paper %1 info3-inproceedings-2021-18 %A Pimpinella, Andrea %A Redondi, Alessandro E.C. %A Loh, Frank %A Seufert, Michael %B 3rd International Workshop on High-Precision, Predictable, and Low-Latency Networking (HiPNet) %C Izmir, Turkey (Virtual Conference) %D 2021 %T Machine-Learning Based Prediction of Next HTTP Request Arrival Time in Adaptive Video Streaming
• Uplink vs. Downlink: Machine Learning-Based Quality Prediction for HTTP Adaptive Video Streaming Loh, Frank; Poignée, Fabian; Wamser, Florian; Leidinger, Ferdinand; Hoßfeld, Tobias in Sensors (2021). 21(12) 4172.
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  Streaming video is responsible for the bulk of Internet traffic these days. For this reason, Internet providers and network operators try to make predictions and assessments about the streaming quality for an end user. Current monitoring solutions are based on a variety of different machine learning approaches. The challenge for providers and operators nowadays is that existing approaches require large amounts of data. In this work, the most relevant quality of experience metrics, i.e., the initial playback delay, the video streaming quality, video quality changes, and video rebuffering events, are examined using a voluminous data set of more than 13,000 YouTube video streaming runs that were collected with the native YouTube mobile app. Three Machine Learning models are developed and compared to estimate playback behavior based on uplink request information. The main focus has been on developing a lightweight approach using as few features and as little data as possible, while maintaining state-of-the-art performance.

  @article{info3-article-2021-3, abstract = {Streaming video is responsible for the bulk of Internet traffic these days. For this reason, Internet providers and network operators try to make predictions and assessments about the streaming quality for an end user. Current monitoring solutions are based on a variety of different machine learning approaches. The challenge for providers and operators nowadays is that existing approaches require large amounts of data. In this work, the most relevant quality of experience metrics, i.e., the initial playback delay, the video streaming quality, video quality changes, and video rebuffering events, are examined using a voluminous data set of more than 13,000 YouTube video streaming runs that were collected with the native YouTube mobile app. Three Machine Learning models are developed and compared to estimate playback behavior based on uplink request information. The main focus has been on developing a lightweight approach using as few features and as little data as possible, while maintaining state-of-the-art performance.}, author = {Loh, Frank and Poignée, Fabian and Wamser, Florian and Leidinger, Ferdinand and Hoßfeld, Tobias}, journal = {Sensors}, keywords = {can}, number = 12, pages = 4172, title = {Uplink vs. Downlink: Machine Learning-Based Quality Prediction for HTTP Adaptive Video Streaming}, volume = 21, year = 2021 }

  %0 Journal Article %1 info3-article-2021-3 %A Loh, Frank %A Poignée, Fabian %A Wamser, Florian %A Leidinger, Ferdinand %A Hoßfeld, Tobias %D 2021 %J Sensors %N 12 %P 4172 %T Uplink vs. Downlink: Machine Learning-Based Quality Prediction for HTTP Adaptive Video Streaming %V 21 %X Streaming video is responsible for the bulk of Internet traffic these days. For this reason, Internet providers and network operators try to make predictions and assessments about the streaming quality for an end user. Current monitoring solutions are based on a variety of different machine learning approaches. The challenge for providers and operators nowadays is that existing approaches require large amounts of data. In this work, the most relevant quality of experience metrics, i.e., the initial playback delay, the video streaming quality, video quality changes, and video rebuffering events, are examined using a voluminous data set of more than 13,000 YouTube video streaming runs that were collected with the native YouTube mobile app. Three Machine Learning models are developed and compared to estimate playback behavior based on uplink request information. The main focus has been on developing a lightweight approach using as few features and as little data as possible, while maintaining state-of-the-art performance.
• Talk to Me: Investigating the Traffic Characteristics of Amazon Echo Dot and Google Home Loh, Frank; Geissler, Stefan; Schaible, Fabian; Hoßfeld, Tobias in International Conference on Communications and Electronics, ICCE (2021).
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  The application area of smart speakers is steadily increasing with the Amazon Echo family and Google Home being brand leaders. Use cases include, among others, updating the calendar, home automation, or simply assisting users in their every day life. With the increasing amount of devices, the traffic generation and requesting process becomes a relevant subject to be studied in order to create traffic models and predict the impact on networks by these types of devices. Furthermore, with a detailed understanding of the devices, service quality can be monitored and improved for the end user. For that reason, in this work the requesting and traffic generation process of the Amazon Echo Dot and Google Home are studied and the generated network load of both devices is compared. With the insights of this study and additional device usage statistics, detailed traffic and usage models can be created.

  @inproceedings{info3-inproceedings-2021-5, abstract = {The application area of smart speakers is steadily increasing with the Amazon Echo family and Google Home being brand leaders. Use cases include, among others, updating the calendar, home automation, or simply assisting users in their every day life. With the increasing amount of devices, the traffic generation and requesting process becomes a relevant subject to be studied in order to create traffic models and predict the impact on networks by these types of devices. Furthermore, with a detailed understanding of the devices, service quality can be monitored and improved for the end user. For that reason, in this work the requesting and traffic generation process of the Amazon Echo Dot and Google Home are studied and the generated network load of both devices is compared. With the insights of this study and additional device usage statistics, detailed traffic and usage models can be created.}, author = {Loh, Frank and Geissler, Stefan and Schaible, Fabian and Hoßfeld, Tobias}, booktitle = {International Conference on Communications and Electronics, ICCE}, keywords = {sys:hidden:inproceedings}, month = 1, title = {Talk to Me: Investigating the Traffic Characteristics of Amazon Echo Dot and Google Home}, year = 2021 }

  %0 Conference Paper %1 info3-inproceedings-2021-5 %A Loh, Frank %A Geissler, Stefan %A Schaible, Fabian %A Hoßfeld, Tobias %B International Conference on Communications and Electronics, ICCE %D 2021 %T Talk to Me: Investigating the Traffic Characteristics of Amazon Echo Dot and Google Home %X The application area of smart speakers is steadily increasing with the Amazon Echo family and Google Home being brand leaders. Use cases include, among others, updating the calendar, home automation, or simply assisting users in their every day life. With the increasing amount of devices, the traffic generation and requesting process becomes a relevant subject to be studied in order to create traffic models and predict the impact on networks by these types of devices. Furthermore, with a detailed understanding of the devices, service quality can be monitored and improved for the end user. For that reason, in this work the requesting and traffic generation process of the Amazon Echo Dot and Google Home are studied and the generated network load of both devices is compared. With the insights of this study and additional device usage statistics, detailed traffic and usage models can be created.
• Improving LoRaWAN’s Successful Information Transmission Rate with Redundancy Loh, Frank; Raffeck, Simon; Metzger, Florian; Hoßfeld, Tobias in 17th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob) (2021).
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  The adaptation of Internet of Things in our everyday life shows different new demands and challenges. One of the fastest growing technologies in this context are Low Power Wide Area Networks with LoRaWAN as one of their most prominent representatives. The promise of this technology is to transmit sensor data over large distances with very little energy consumption. But transmission behavior, and especially overhead and collision probability, must be studied in detail to improve transmission quality and energy consumption due to the random access nature of LoRaWAN. Because of that, this work investigates the LoRaWAN channel capacity by analyzing the transmission overhead, the collision probability, and the data loss. At the end, an energy consumption comparison is done. The contribution is a novel approach based on aggregation and retransmission that shows a decreased data loss of up to 20% compared to the currently used random channel access.

  @inproceedings{info3-inproceedings-2021-19, abstract = {The adaptation of Internet of Things in our everyday life shows different new demands and challenges. One of the fastest growing technologies in this context are Low Power Wide Area Networks with LoRaWAN as one of their most prominent representatives. The promise of this technology is to transmit sensor data over large distances with very little energy consumption. But transmission behavior, and especially overhead and collision probability, must be studied in detail to improve transmission quality and energy consumption due to the random access nature of LoRaWAN. Because of that, this work investigates the LoRaWAN channel capacity by analyzing the transmission overhead, the collision probability, and the data loss. At the end, an energy consumption comparison is done. The contribution is a novel approach based on aggregation and retransmission that shows a decreased data loss of up to 20% compared to the currently used random channel access.}, author = {Loh, Frank and Raffeck, Simon and Metzger, Florian and Hoßfeld, Tobias}, booktitle = {17th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)}, keywords = {5mart}, month = 10, title = {Improving LoRaWAN’s Successful Information Transmission Rate with Redundancy}, year = 2021 }

  %0 Conference Paper %1 info3-inproceedings-2021-19 %A Loh, Frank %A Raffeck, Simon %A Metzger, Florian %A Hoßfeld, Tobias %B 17th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob) %D 2021 %T Improving LoRaWAN’s Successful Information Transmission Rate with Redundancy %X The adaptation of Internet of Things in our everyday life shows different new demands and challenges. One of the fastest growing technologies in this context are Low Power Wide Area Networks with LoRaWAN as one of their most prominent representatives. The promise of this technology is to transmit sensor data over large distances with very little energy consumption. But transmission behavior, and especially overhead and collision probability, must be studied in detail to improve transmission quality and energy consumption due to the random access nature of LoRaWAN. Because of that, this work investigates the LoRaWAN channel capacity by analyzing the transmission overhead, the collision probability, and the data loss. At the end, an energy consumption comparison is done. The contribution is a novel approach based on aggregation and retransmission that shows a decreased data loss of up to 20% compared to the currently used random channel access.
• Robust Gateway Placement for Scalable LoRaWAN Loh, Frank; Bau, Dominique; Zink, Johannes; Wolff, Alexander; Hoßfeld, Tobias in 13th IFIP Wireless and Mobile Networking Conference (WMNC) (2021).
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  Many exciting applications are currently emerging due to the use of technology from the Internet of Things (IoT) in Smart Cities. In recent years, Long Range Wide Area Networks (LoRaWANs) have become one of the main technologies in this field due to long distance coverage, low power consumption sensors, and economic reasons. So far, LoRaWANs have been planned and deployed mainly with the aim of minimizing the number of gateways, while still providing coverage in a geographic area. Packet collisions and future traffic have not been considered. In contrast, we present a gateway placement strategy that is robust against an increase in the number of sensors and in the network load. To this end, we modify an existing local search algorithm for a geometric set cover problem such that it takes the capacities of gateways into account. If we set these capacities below the maximum, the network can accommodate additional sensors in the future. Moreover, our algorithm can extend the initial placement once the capacities are exhausted.

  @inproceedings{info3-inproceedings-2021-20, abstract = {Many exciting applications are currently emerging due to the use of technology from the Internet of Things (IoT) in Smart Cities. In recent years, Long Range Wide Area Networks (LoRaWANs) have become one of the main technologies in this field due to long distance coverage, low power consumption sensors, and economic reasons. So far, LoRaWANs have been planned and deployed mainly with the aim of minimizing the number of gateways, while still providing coverage in a geographic area. Packet collisions and future traffic have not been considered. In contrast, we present a gateway placement strategy that is robust against an increase in the number of sensors and in the network load. To this end, we modify an existing local search algorithm for a geometric set cover problem such that it takes the capacities of gateways into account. If we set these capacities below the maximum, the network can accommodate additional sensors in the future. Moreover, our algorithm can extend the initial placement once the capacities are exhausted.}, author = {Loh, Frank and Bau, Dominique and Zink, Johannes and Wolff, Alexander and Hoßfeld, Tobias}, booktitle = {13th IFIP Wireless and Mobile Networking Conference (WMNC)}, keywords = {5mart}, month = 10, title = {Robust Gateway Placement for Scalable LoRaWAN}, year = 2021 }

  %0 Conference Paper %1 info3-inproceedings-2021-20 %A Loh, Frank %A Bau, Dominique %A Zink, Johannes %A Wolff, Alexander %A Hoßfeld, Tobias %B 13th IFIP Wireless and Mobile Networking Conference (WMNC) %D 2021 %T Robust Gateway Placement for Scalable LoRaWAN %X Many exciting applications are currently emerging due to the use of technology from the Internet of Things (IoT) in Smart Cities. In recent years, Long Range Wide Area Networks (LoRaWANs) have become one of the main technologies in this field due to long distance coverage, low power consumption sensors, and economic reasons. So far, LoRaWANs have been planned and deployed mainly with the aim of minimizing the number of gateways, while still providing coverage in a geographic area. Packet collisions and future traffic have not been considered. In contrast, we present a gateway placement strategy that is robust against an increase in the number of sensors and in the network load. To this end, we modify an existing local search algorithm for a geometric set cover problem such that it takes the capacities of gateways into account. If we set these capacities below the maximum, the network can accommodate additional sensors in the future. Moreover, our algorithm can extend the initial placement once the capacities are exhausted.
• LoRaPlan: A Software to Evaluate Gateway Placement in LoRaWAN Loh, Frank; Mehling, Noah; Metzger, Florian; Hoßfeld, Tobias in 17th International Conference on Network and Service Management (2021).
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  Long Range Wide Area Network (LoRaWAN) is one of the fastest growing Internet of Things (IoT) access network solutions. One major challenge in current LoRaWAN planning is message collision due to the random channel access. To study the collision behavior in LoRaWAN, we present LoRaPlan in this demonstration. LoRaPlan is a software to evaluate gateway placement decisions by studying the collision probability. Therefore, sensor and gateway locations can be imported to create a LoRaWAN. Furthermore, existing networks can be extended by additional gateways. Based on this setup, network coverage, network quality with regard to the number of sensors a single gateway has to manage, and also transmission quality and collision probabilities can be studied. In this demonstration, first the process of network creation with gateway and sensor import and additional manual gateway placement in LoRaPlan is presented. Different adjustable parameters are shown and the influence on network coverage and collision probability is discussed. At the end of this demonstration, it is possible for the audience to place their own gateways and evaluate own placements by means of collision probability and the coverage.

  @article{info3-article-2021-11, abstract = {Long Range Wide Area Network (LoRaWAN) is one of the fastest growing Internet of Things (IoT) access network solutions. One major challenge in current LoRaWAN planning is message collision due to the random channel access. To study the collision behavior in LoRaWAN, we present LoRaPlan in this demonstration. LoRaPlan is a software to evaluate gateway placement decisions by studying the collision probability. Therefore, sensor and gateway locations can be imported to create a LoRaWAN. Furthermore, existing networks can be extended by additional gateways. Based on this setup, network coverage, network quality with regard to the number of sensors a single gateway has to manage, and also transmission quality and collision probabilities can be studied. In this demonstration, first the process of network creation with gateway and sensor import and additional manual gateway placement in LoRaPlan is presented. Different adjustable parameters are shown and the influence on network coverage and collision probability is discussed. At the end of this demonstration, it is possible for the audience to place their own gateways and evaluate own placements by means of collision probability and the coverage.}, author = {Loh, Frank and Mehling, Noah and Metzger, Florian and Hoßfeld, Tobias}, journal = {17th International Conference on Network and Service Management}, keywords = {sys:hidden:article}, month = 10, title = {LoRaPlan: A Software to Evaluate Gateway Placement in LoRaWAN}, year = 2021 }

  %0 Journal Article %1 info3-article-2021-11 %A Loh, Frank %A Mehling, Noah %A Metzger, Florian %A Hoßfeld, Tobias %D 2021 %J 17th International Conference on Network and Service Management %T LoRaPlan: A Software to Evaluate Gateway Placement in LoRaWAN %X Long Range Wide Area Network (LoRaWAN) is one of the fastest growing Internet of Things (IoT) access network solutions. One major challenge in current LoRaWAN planning is message collision due to the random channel access. To study the collision behavior in LoRaWAN, we present LoRaPlan in this demonstration. LoRaPlan is a software to evaluate gateway placement decisions by studying the collision probability. Therefore, sensor and gateway locations can be imported to create a LoRaWAN. Furthermore, existing networks can be extended by additional gateways. Based on this setup, network coverage, network quality with regard to the number of sensors a single gateway has to manage, and also transmission quality and collision probabilities can be studied. In this demonstration, first the process of network creation with gateway and sensor import and additional manual gateway placement in LoRaPlan is presented. Different adjustable parameters are shown and the influence on network coverage and collision probability is discussed. At the end of this demonstration, it is possible for the audience to place their own gateways and evaluate own placements by means of collision probability and the coverage.

• Is the Uplink Enough? Estimating Video Stalls from Encrypted Network Traffic Loh, Frank; Wamser, Florian; Moldovan, Christian; Zeidler, Bernd; Tsilimantos, Dimitrios; Valentin, Stefan; Hoßfeld, Tobias in 32th IEEE/IFIP Network Operations and Management Symposium (2020).
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  Today’s traffic projections speak of almost 58 % video traffic across the Internet. Nearly all video traffic is encrypted, accounting for more than 50 % encrypted traffic worldwide. To analyze video traffic today, or even estimate its quality in the network, a deep look into the traffic characteristics has to be done. But then, important quality metrics from the traffic behavior can be derived. Based on extensive measurements we show in this work how to measure and estimate video stalls for mobile adaptive streaming. The underlying dataset includes more than 900 hours of video footage from the native YouTube app, measured over 18 different videos in 56 network scenarios in two cities in Europe. We outline a possible approach to estimate the video playback buffer size based on uplink video chunk requests in real-time to break down the video stalls. This work is intended as a tool for network operators to receive further knowledge of the characteristics of video streaming traffic to quantify the most important QoE degradation factors of one of the most important applications today.

  @inproceedings{info3-inproceedings-2020-2, abstract = {Today’s traffic projections speak of almost 58 % video traffic across the Internet. Nearly all video traffic is encrypted, accounting for more than 50 % encrypted traffic worldwide. To analyze video traffic today, or even estimate its quality in the network, a deep look into the traffic characteristics has to be done. But then, important quality metrics from the traffic behavior can be derived. Based on extensive measurements we show in this work how to measure and estimate video stalls for mobile adaptive streaming. The underlying dataset includes more than 900 hours of video footage from the native YouTube app, measured over 18 different videos in 56 network scenarios in two cities in Europe. We outline a possible approach to estimate the video playback buffer size based on uplink video chunk requests in real-time to break down the video stalls. This work is intended as a tool for network operators to receive further knowledge of the characteristics of video streaming traffic to quantify the most important QoE degradation factors of one of the most important applications today.}, address = {Budapest, Hungary}, author = {Loh, Frank and Wamser, Florian and Moldovan, Christian and Zeidler, Bernd and Tsilimantos, Dimitrios and Valentin, Stefan and Hoßfeld, Tobias}, booktitle = {32th IEEE/IFIP Network Operations and Management Symposium}, keywords = {can}, month = 4, title = {Is the Uplink Enough? Estimating Video Stalls from Encrypted Network Traffic}, year = 2020 }

  %0 Conference Paper %1 info3-inproceedings-2020-2 %A Loh, Frank %A Wamser, Florian %A Moldovan, Christian %A Zeidler, Bernd %A Tsilimantos, Dimitrios %A Valentin, Stefan %A Hoßfeld, Tobias %B 32th IEEE/IFIP Network Operations and Management Symposium %C Budapest, Hungary %D 2020 %T Is the Uplink Enough? Estimating Video Stalls from Encrypted Network Traffic %X Today’s traffic projections speak of almost 58 % video traffic across the Internet. Nearly all video traffic is encrypted, accounting for more than 50 % encrypted traffic worldwide. To analyze video traffic today, or even estimate its quality in the network, a deep look into the traffic characteristics has to be done. But then, important quality metrics from the traffic behavior can be derived. Based on extensive measurements we show in this work how to measure and estimate video stalls for mobile adaptive streaming. The underlying dataset includes more than 900 hours of video footage from the native YouTube app, measured over 18 different videos in 56 network scenarios in two cities in Europe. We outline a possible approach to estimate the video playback buffer size based on uplink video chunk requests in real-time to break down the video stalls. This work is intended as a tool for network operators to receive further knowledge of the characteristics of video streaming traffic to quantify the most important QoE degradation factors of one of the most important applications today.
• Optimizing HAS for 360-Degree Videos Moldovan, Christian; Loh, Frank; Seufert, Michael; Hoßfeld, Tobias in 5th IEEE/IFIP International Workshop on Analytics for Network and Service Management (AnNet) (2020).
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  @inproceedings{info3-inproceedings-2020-1, address = {Budapest, Hungary}, author = {Moldovan, Christian and Loh, Frank and Seufert, Michael and Hoßfeld, Tobias}, booktitle = {5th IEEE/IFIP International Workshop on Analytics for Network and Service Management (AnNet)}, keywords = {net-man}, month = 4, title = {Optimizing HAS for 360-Degree Videos}, year = 2020 }

  %0 Conference Paper %1 info3-inproceedings-2020-1 %A Moldovan, Christian %A Loh, Frank %A Seufert, Michael %A Hoßfeld, Tobias %B 5th IEEE/IFIP International Workshop on Analytics for Network and Service Management (AnNet) %C Budapest, Hungary %D 2020 %T Optimizing HAS for 360-Degree Videos

• Traffic Measurement Study on Video Streaming with the Amazon Echo Show Loh, Frank; Vomhoff, Viktoria; Wamser, Florian; Metzger, Florian; Hoßfeld, Tobias in 4th Internet-QoE Workshop: QoE-based Analysis and Management of Data Communication Networks (2019).
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  The Amazon Echo Show is one of the most widely used smart speakers with the ability to stream video. Due to its popularity, the traffc profiles of such devices are of interest to network operators and providers. This work presents a measurement study of the Amazon Echo Show in terms of network traffc and streaming behavior. More than 470 hours of streaming data are collected and analyzed at network layer. Based on this, streaming quality is derived at application layer. The study quantifies the traffc and shows that streaming with the Amazon Echo Show is comparable to streaming with a native web browser, but in a more conservative way.

  @inproceedings{info3-inproceedings-2019-26, abstract = {The Amazon Echo Show is one of the most widely used smart speakers with the ability to stream video. Due to its popularity, the traffc profiles of such devices are of interest to network operators and providers. This work presents a measurement study of the Amazon Echo Show in terms of network traffc and streaming behavior. More than 470 hours of streaming data are collected and analyzed at network layer. Based on this, streaming quality is derived at application layer. The study quantifies the traffc and shows that streaming with the Amazon Echo Show is comparable to streaming with a native web browser, but in a more conservative way.}, author = {Loh, Frank and Vomhoff, Viktoria and Wamser, Florian and Metzger, Florian and Hoßfeld, Tobias}, booktitle = {4th Internet-QoE Workshop: QoE-based Analysis and Management of Data Communication Networks}, keywords = {can}, month = 10, title = {Traffic Measurement Study on Video Streaming with the Amazon Echo Show}, year = 2019 }

  %0 Conference Paper %1 info3-inproceedings-2019-26 %A Loh, Frank %A Vomhoff, Viktoria %A Wamser, Florian %A Metzger, Florian %A Hoßfeld, Tobias %B 4th Internet-QoE Workshop: QoE-based Analysis and Management of Data Communication Networks %D 2019 %T Traffic Measurement Study on Video Streaming with the Amazon Echo Show %X The Amazon Echo Show is one of the most widely used smart speakers with the ability to stream video. Due to its popularity, the traffc profiles of such devices are of interest to network operators and providers. This work presents a measurement study of the Amazon Echo Show in terms of network traffc and streaming behavior. More than 470 hours of streaming data are collected and analyzed at network layer. Based on this, streaming quality is derived at application layer. The study quantifies the traffc and shows that streaming with the Amazon Echo Show is comparable to streaming with a native web browser, but in a more conservative way.
• From click to playback: a dataset to study the response time of mobile YouTube Loh, Frank; Wamser, Florian; Moldovan, Christian; Zeidler, Bernd; Hoßfeld, Tobias; Tsilimantos, Dimitrios; Valentin, Stefan in Proceedings of the 10th ACM Multimedia Systems Conference (2019). 267–272.
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  Responding fluently to user requests is important to keep them immersed. In this paper, we are presenting an extensive dataset to study the response time of YouTube's mobile video streaming service on Android. We illustrate the application of our dataset by studying YouTube's initial delay for a subset of 9 videos in 75 network scenarios. We find that in 41% of the cases, YouTube exceeds the attention span of a typical user, while deep immersion is only reached in 15% of the cases. Our factor analysis implies that the allocation of the initial CDN node is the critical link in this delay chain. Since our dataset includes a large variety of factors, we are describing setup, methodology, and data structure in detail. Our dataset and measurement tools are publicly available.

  @inproceedings{info3-inproceedings-2019-25, abstract = {Responding fluently to user requests is important to keep them immersed. In this paper, we are presenting an extensive dataset to study the response time of YouTube's mobile video streaming service on Android. We illustrate the application of our dataset by studying YouTube's initial delay for a subset of 9 videos in 75 network scenarios. We find that in 41% of the cases, YouTube exceeds the attention span of a typical user, while deep immersion is only reached in 15% of the cases. Our factor analysis implies that the allocation of the initial CDN node is the critical link in this delay chain. Since our dataset includes a large variety of factors, we are describing setup, methodology, and data structure in detail. Our dataset and measurement tools are publicly available.}, author = {Loh, Frank and Wamser, Florian and Moldovan, Christian and Zeidler, Bernd and Hoßfeld, Tobias and Tsilimantos, Dimitrios and Valentin, Stefan}, booktitle = {Proceedings of the 10th ACM Multimedia Systems Conference}, keywords = {can}, month = 6, pages = {267-272}, title = {From click to playback: a dataset to study the response time of mobile YouTube}, year = 2019 }

  %0 Conference Paper %1 info3-inproceedings-2019-25 %A Loh, Frank %A Wamser, Florian %A Moldovan, Christian %A Zeidler, Bernd %A Hoßfeld, Tobias %A Tsilimantos, Dimitrios %A Valentin, Stefan %B Proceedings of the 10th ACM Multimedia Systems Conference %D 2019 %P 267-272 %T From click to playback: a dataset to study the response time of mobile YouTube %X Responding fluently to user requests is important to keep them immersed. In this paper, we are presenting an extensive dataset to study the response time of YouTube's mobile video streaming service on Android. We illustrate the application of our dataset by studying YouTube's initial delay for a subset of 9 videos in 75 network scenarios. We find that in 41% of the cases, YouTube exceeds the attention span of a typical user, while deep immersion is only reached in 15% of the cases. Our factor analysis implies that the allocation of the initial CDN node is the critical link in this delay chain. Since our dataset includes a large variety of factors, we are describing setup, methodology, and data structure in detail. Our dataset and measurement tools are publicly available.

• A Public Dataset for YouTube’s Mobile Streaming Client Karagkioules, Theodoros; Tsilimantos, Dimitrios; Valentin, Stefan; Wamser, Florian; Zeidler, Bernd; Seufert, Michael; Loh, Frank; Tran-Gia, Phuoc in Network Traffic Measurement and Analysis Conference (TMA) (2018).
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  @inproceedings{info3-inproceedings-2018-41, address = {Vienna, Austria}, author = {Karagkioules, Theodoros and Tsilimantos, Dimitrios and Valentin, Stefan and Wamser, Florian and Zeidler, Bernd and Seufert, Michael and Loh, Frank and Tran-Gia, Phuoc}, booktitle = {Network Traffic Measurement and Analysis Conference (TMA)}, keywords = {can}, title = {A Public Dataset for YouTube’s Mobile Streaming Client}, year = 2018 }

  %0 Conference Paper %1 info3-inproceedings-2018-41 %A Karagkioules, Theodoros %A Tsilimantos, Dimitrios %A Valentin, Stefan %A Wamser, Florian %A Zeidler, Bernd %A Seufert, Michael %A Loh, Frank %A Tran-Gia, Phuoc %B Network Traffic Measurement and Analysis Conference (TMA) %C Vienna, Austria %D 2018 %T A Public Dataset for YouTube’s Mobile Streaming Client
• Quality of Service Assessment of Live Video Streaming with a Remote-Controlled Drone Loh, Frank; Wamser, Florian; Hoßfeld, Tobias; Tran-Gia, Phuoc in IEEE Conference on Network Softwarization (2018).
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  Today's networks require a deep understanding of applications to optimize networks, efficiently design networks, and meet traffic demands, application heterogeneity, and application requirements. Current application areas include live video streaming and real-time applications, such as those that are named in 5G use cases with automation, disaster recovery, gaming, and Industry 4.0. In this work, we examine an application scenario with live video streaming and parallel real-time requirements in the uplink for disaster recovery. We study the quality of service (QoS) features of a remote-controlled drone. The drone is controlled via a tablet or smartphone while the video from the camera is transmitted from the drone to the user. There are high demands in both the uplink and downlink direction. The contribution of the work is the measurement of the QoS and application parameters for this scenario and the definition of influencing parameters for the application-layer.

  @inproceedings{info3-inproceedings-2018-31, abstract = {Today's networks require a deep understanding of applications to optimize networks, efficiently design networks, and meet traffic demands, application heterogeneity, and application requirements. Current application areas include live video streaming and real-time applications, such as those that are named in 5G use cases with automation, disaster recovery, gaming, and Industry 4.0. In this work, we examine an application scenario with live video streaming and parallel real-time requirements in the uplink for disaster recovery. We study the quality of service (QoS) features of a remote-controlled drone. The drone is controlled via a tablet or smartphone while the video from the camera is transmitted from the drone to the user. There are high demands in both the uplink and downlink direction. The contribution of the work is the measurement of the QoS and application parameters for this scenario and the definition of influencing parameters for the application-layer.}, address = {Montreal, Canada}, author = {Loh, Frank and Wamser, Florian and Hoßfeld, Tobias and Tran-Gia, Phuoc}, booktitle = {IEEE Conference on Network Softwarization}, keywords = {can}, month = 7, title = {Quality of Service Assessment of Live Video Streaming with a Remote-Controlled Drone}, year = 2018 }

  %0 Conference Paper %1 info3-inproceedings-2018-31 %A Loh, Frank %A Wamser, Florian %A Hoßfeld, Tobias %A Tran-Gia, Phuoc %B IEEE Conference on Network Softwarization %C Montreal, Canada %D 2018 %T Quality of Service Assessment of Live Video Streaming with a Remote-Controlled Drone %X Today's networks require a deep understanding of applications to optimize networks, efficiently design networks, and meet traffic demands, application heterogeneity, and application requirements. Current application areas include live video streaming and real-time applications, such as those that are named in 5G use cases with automation, disaster recovery, gaming, and Industry 4.0. In this work, we examine an application scenario with live video streaming and parallel real-time requirements in the uplink for disaster recovery. We study the quality of service (QoS) features of a remote-controlled drone. The drone is controlled via a tablet or smartphone while the video from the camera is transmitted from the drone to the user. There are high demands in both the uplink and downlink direction. The contribution of the work is the measurement of the QoS and application parameters for this scenario and the definition of influencing parameters for the application-layer.
• A Wrapper for Automatic Measurements with YouTube’s Native Android App Seufert, Michael; Zeidler, Bernd; Wamser, Florian; Karagkioules, Theodoros; Tsilimantos, Dimitrios; Loh, Frank; Tran-Gia, Phuoc; Valentin, Stefan in Network Traffic Measurement and Analysis Conference (TMA) (2018).
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  YouTube is one of the most popular and demanding services in the Internet today. Thereby, a large portion of this traffic is generated by YouTube's mobile app. While past studies have shown how to monitor browser-based streaming on desktop PCs (e.g., YoMo) or mobile devices (e.g., YoMoApp), streaming in the native app has not been monitored yet. This paper presents an automated framework for monitoring the streaming in YouTube's native app for Android. The concept is based on a wrapper application and the Android Debug Bridge (adb), and can be also extended to automatic measurements with other apps. For YouTube, it allows to collect application-layer streaming data, such as current playtime, buffered playtime, video encoding, and quality switches. These data can be complemented with network measurements on the mobile access link to obtain a holistic view on mobile YouTube streaming on Android devices. In addition to describing the software design and testbed setup, this paper discusses an experimental measurement. This study analyzes the streaming in the native YouTube app and compares it to the streaming from the mobile YouTube website via YoMoApp.

  @inproceedings{info3-article-2018-4, abstract = {YouTube is one of the most popular and demanding services in the Internet today. Thereby, a large portion of this traffic is generated by YouTube's mobile app. While past studies have shown how to monitor browser-based streaming on desktop PCs (e.g., YoMo) or mobile devices (e.g., YoMoApp), streaming in the native app has not been monitored yet. This paper presents an automated framework for monitoring the streaming in YouTube's native app for Android. The concept is based on a wrapper application and the Android Debug Bridge (adb), and can be also extended to automatic measurements with other apps. For YouTube, it allows to collect application-layer streaming data, such as current playtime, buffered playtime, video encoding, and quality switches. These data can be complemented with network measurements on the mobile access link to obtain a holistic view on mobile YouTube streaming on Android devices. In addition to describing the software design and testbed setup, this paper discusses an experimental measurement. This study analyzes the streaming in the native YouTube app and compares it to the streaming from the mobile YouTube website via YoMoApp.}, address = {Vienna, Austria}, author = {Seufert, Michael and Zeidler, Bernd and Wamser, Florian and Karagkioules, Theodoros and Tsilimantos, Dimitrios and Loh, Frank and Tran-Gia, Phuoc and Valentin, Stefan}, booktitle = {Network Traffic Measurement and Analysis Conference (TMA)}, keywords = {can}, month = 4, title = {A Wrapper for Automatic Measurements with YouTube's Native Android App}, year = 2018 }

  %0 Conference Paper %1 info3-article-2018-4 %A Seufert, Michael %A Zeidler, Bernd %A Wamser, Florian %A Karagkioules, Theodoros %A Tsilimantos, Dimitrios %A Loh, Frank %A Tran-Gia, Phuoc %A Valentin, Stefan %B Network Traffic Measurement and Analysis Conference (TMA) %C Vienna, Austria %D 2018 %T A Wrapper for Automatic Measurements with YouTube's Native Android App %X YouTube is one of the most popular and demanding services in the Internet today. Thereby, a large portion of this traffic is generated by YouTube's mobile app. While past studies have shown how to monitor browser-based streaming on desktop PCs (e.g., YoMo) or mobile devices (e.g., YoMoApp), streaming in the native app has not been monitored yet. This paper presents an automated framework for monitoring the streaming in YouTube's native app for Android. The concept is based on a wrapper application and the Android Debug Bridge (adb), and can be also extended to automatic measurements with other apps. For YouTube, it allows to collect application-layer streaming data, such as current playtime, buffered playtime, video encoding, and quality switches. These data can be complemented with network measurements on the mobile access link to obtain a holistic view on mobile YouTube streaming on Android devices. In addition to describing the software design and testbed setup, this paper discusses an experimental measurement. This study analyzes the streaming in the native YouTube app and compares it to the streaming from the mobile YouTube website via YoMoApp.
• A Wrapper for Automated Measurements with YouTube’s Native App Loh, Frank; Karagkioules, Theodoros; Seufert, Michael; Zeidler, Bernd; Tsilimantos, Dimitrios; Tran-Gia, Phuoc; Valentin, Stefan; Wamser, Florian (2018, April).
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  This demo introduces a wrapper used for automated measurements of mobile video streaming in the Android YouTube app. The difference to traditional measurement techniques is that the measurement is done with the native YouTube app as it is provided in the Google Play Store. In addition to bandwidth or packet loss detection, the QoE of the video stream can be measured and quantified. For this, the amount of quality changes, the current playtime, the buffer level, and statistics like video and audio format are captured. Thus, detailed relationships between network parameters and streaming behavior based on many factors can be detected within the native app available in the Play Store.

  @misc{info3-demo-2018-1, abstract = {This demo introduces a wrapper used for automated measurements of mobile video streaming in the Android YouTube app. The difference to traditional measurement techniques is that the measurement is done with the native YouTube app as it is provided in the Google Play Store. In addition to bandwidth or packet loss detection, the QoE of the video stream can be measured and quantified. For this, the amount of quality changes, the current playtime, the buffer level, and statistics like video and audio format are captured. Thus, detailed relationships between network parameters and streaming behavior based on many factors can be detected within the native app available in the Play Store.}, address = {Taipei, Taiwan}, author = {Loh, Frank and Karagkioules, Theodoros and Seufert, Michael and Zeidler, Bernd and Tsilimantos, Dimitrios and Tran-Gia, Phuoc and Valentin, Stefan and Wamser, Florian}, booktitle = {IEEE/IFIP NOMS 2018}, keywords = {can}, month = 4, title = {A Wrapper for Automated Measurements with YouTube’s Native App}, year = 2018 }

  %0 Generic %1 info3-demo-2018-1 %A Loh, Frank %A Karagkioules, Theodoros %A Seufert, Michael %A Zeidler, Bernd %A Tsilimantos, Dimitrios %A Tran-Gia, Phuoc %A Valentin, Stefan %A Wamser, Florian %B IEEE/IFIP NOMS 2018 %C Taipei, Taiwan %D 2018 %T A Wrapper for Automated Measurements with YouTube’s Native App %X This demo introduces a wrapper used for automated measurements of mobile video streaming in the Android YouTube app. The difference to traditional measurement techniques is that the measurement is done with the native YouTube app as it is provided in the Google Play Store. In addition to bandwidth or packet loss detection, the QoE of the video stream can be measured and quantified. For this, the amount of quality changes, the current playtime, the buffer level, and statistics like video and audio format are captured. Thus, detailed relationships between network parameters and streaming behavior based on many factors can be detected within the native app available in the Play Store.

• Performance Evaluation of Video Streaming Service Chains in Softwarized 5G Networks with Task Graph Reduction Loh, Frank; Burger, Valentin; Wamser, Florian; Tran-Gia, Phuoc; Schembra, Giovanni; Rametta, Corrado in 29th International Teletraffic Congress (ITC) (2017).
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  @inproceedings{info3-inproceedings-2017-18, author = {Loh, Frank and Burger, Valentin and Wamser, Florian and Tran-Gia, Phuoc and Schembra, Giovanni and Rametta, Corrado}, booktitle = {29th International Teletraffic Congress (ITC)}, keywords = {can}, month = 9, title = {Performance Evaluation of Video Streaming Service Chains in Softwarized 5G Networks with Task Graph Reduction}, year = 2017 }

  %0 Conference Paper %1 info3-inproceedings-2017-18 %A Loh, Frank %A Burger, Valentin %A Wamser, Florian %A Tran-Gia, Phuoc %A Schembra, Giovanni %A Rametta, Corrado %B 29th International Teletraffic Congress (ITC) %D 2017 %T Performance Evaluation of Video Streaming Service Chains in Softwarized 5G Networks with Task Graph Reduction
• Dynamic Cloud Service Placement for Live Video Streaming with a Remote-Controlled Drone Wamser, Florian; Loh, Frank; Bruschi, Roberto; Lago, Paolo; Seufert, Michael; Tran-Gia, Phuoc (2017, May).
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  The continuous growth of Internet content, applications and services has led to ever more demanding requirements in the networks. To meet this, there have been significant developments in the migration of applications and services towards the cloud. The cloud not only provides applications, but also offers dynamic adaptability, scalability, and optimization with respect to the location of the application by migrating storage and application containers. In particular, cloud services can typically be placed and orchestrated at a variety of locations in the cloud. This demonstration shows a dynamic placement of a cloud service with video streaming and real-time control commands for a remote-controlled drone. We control a drone with the help of a cloud service which, in addition to the control commands, also returns a camera image to the operator. The requirements of this cloud application are groundbreaking. The camera requires high data rates from the drone to the cloud and from the cloud to the operator, so that the image can be transmitted in acceptable quality. For the control of the drone, a short delay must also be given in the direction of the drone so that the control can be carried out in real time.

  @misc{info3-demo-2017-1, abstract = {The continuous growth of Internet content, applications and services has led to ever more demanding requirements in the networks. To meet this, there have been significant developments in the migration of applications and services towards the cloud. The cloud not only provides applications, but also offers dynamic adaptability, scalability, and optimization with respect to the location of the application by migrating storage and application containers. In particular, cloud services can typically be placed and orchestrated at a variety of locations in the cloud. This demonstration shows a dynamic placement of a cloud service with video streaming and real-time control commands for a remote-controlled drone. We control a drone with the help of a cloud service which, in addition to the control commands, also returns a camera image to the operator. The requirements of this cloud application are groundbreaking. The camera requires high data rates from the drone to the cloud and from the cloud to the operator, so that the image can be transmitted in acceptable quality. For the control of the drone, a short delay must also be given in the direction of the drone so that the control can be carried out in real time.}, address = {Best Demo Award, Lisbon, Portugal}, author = {Wamser, Florian and Loh, Frank and Bruschi, Roberto and Lago, Paolo and Seufert, Michael and Tran-Gia, Phuoc}, booktitle = {15th IFIP/IEEE International Symposium on Integrated Network Management (IM)}, keywords = {can}, month = 5, title = {Dynamic Cloud Service Placement for Live Video Streaming with a Remote-Controlled Drone}, year = 2017 }

  %0 Generic %1 info3-demo-2017-1 %A Wamser, Florian %A Loh, Frank %A Bruschi, Roberto %A Lago, Paolo %A Seufert, Michael %A Tran-Gia, Phuoc %B 15th IFIP/IEEE International Symposium on Integrated Network Management (IM) %C Best Demo Award, Lisbon, Portugal %D 2017 %T Dynamic Cloud Service Placement for Live Video Streaming with a Remote-Controlled Drone %X The continuous growth of Internet content, applications and services has led to ever more demanding requirements in the networks. To meet this, there have been significant developments in the migration of applications and services towards the cloud. The cloud not only provides applications, but also offers dynamic adaptability, scalability, and optimization with respect to the location of the application by migrating storage and application containers. In particular, cloud services can typically be placed and orchestrated at a variety of locations in the cloud. This demonstration shows a dynamic placement of a cloud service with video streaming and real-time control commands for a remote-controlled drone. We control a drone with the help of a cloud service which, in addition to the control commands, also returns a camera image to the operator. The requirements of this cloud application are groundbreaking. The camera requires high data rates from the drone to the cloud and from the cloud to the operator, so that the image can be transmitted in acceptable quality. For the control of the drone, a short delay must also be given in the direction of the drone so that the control can be carried out in real time.

• Assessment of Subjective Influence and Trust with an Online Social Network Game Seufert, Michael; Burger, Valentin; Lorey, Karl; Seith, Alexander; Loh, Frank; Tran-Gia, Phuoc in Computers in Human Behavior (2016). 64 233–246.
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  The deduction of influence and trust between two individuals only from objective data in online social networks (OSNs) is a rather vague approach. Subjective assessments via surveys produce better results, but are harder to conduct considering the vast amount of friendships of OSN users. This work presents a framework for personalized surveys on relationships in OSNs, which follows a gamification approach. A Facebook game was developed, which was used to subjectively assess social influence and interpersonal trust based on models from psychology. The results show that it is possible to obtain subjective opinions and (limited) objective data about relationships with an OSN game. Also an implicit assessment of influence and trust with subcategory questions is feasible in this case.

  @article{info3-article-2016-7, abstract = {The deduction of influence and trust between two individuals only from objective data in online social networks (OSNs) is a rather vague approach. Subjective assessments via surveys produce better results, but are harder to conduct considering the vast amount of friendships of OSN users. This work presents a framework for personalized surveys on relationships in OSNs, which follows a gamification approach. A Facebook game was developed, which was used to subjectively assess social influence and interpersonal trust based on models from psychology. The results show that it is possible to obtain subjective opinions and (limited) objective data about relationships with an OSN game. Also an implicit assessment of influence and trust with subcategory questions is feasible in this case.}, author = {Seufert, Michael and Burger, Valentin and Lorey, Karl and Seith, Alexander and Loh, Frank and Tran-Gia, Phuoc}, journal = {Computers in Human Behavior}, keywords = {can}, month = 11, pages = {233-246}, title = {Assessment of Subjective Influence and Trust with an Online Social Network Game}, volume = 64, year = 2016 }

  %0 Journal Article %1 info3-article-2016-7 %A Seufert, Michael %A Burger, Valentin %A Lorey, Karl %A Seith, Alexander %A Loh, Frank %A Tran-Gia, Phuoc %D 2016 %J Computers in Human Behavior %P 233-246 %T Assessment of Subjective Influence and Trust with an Online Social Network Game %V 64 %X The deduction of influence and trust between two individuals only from objective data in online social networks (OSNs) is a rather vague approach. Subjective assessments via surveys produce better results, but are harder to conduct considering the vast amount of friendships of OSN users. This work presents a framework for personalized surveys on relationships in OSNs, which follows a gamification approach. A Facebook game was developed, which was used to subjectively assess social influence and interpersonal trust based on models from psychology. The results show that it is possible to obtain subjective opinions and (limited) objective data about relationships with an OSN game. Also an implicit assessment of influence and trust with subcategory questions is feasible in this case.