@article{LohPoigneeWamseretal.2021, author = {Loh, Frank and Poign{\´e}e, Fabian and Wamser, Florian and Leidinger, Ferdinand and Hoßfeld, Tobias}, title = {Uplink vs. Downlink: Machine Learning-Based Quality Prediction for HTTP Adaptive Video Streaming}, series = {Sensors}, volume = {21}, journal = {Sensors}, number = {12}, issn = {1424-8220}, doi = {10.3390/s21124172}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-241121}, year = {2021}, 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.}, language = {en} } @techreport{NguyenLohHossfeld2023, type = {Working Paper}, author = {Nguyen, Kien and Loh, Frank and Hoßfeld, Tobias}, title = {Challenges of Serverless Deployment in Edge-MEC-Cloud}, series = {KuVS Fachgespr{\"a}ch - W{\"u}rzburg Workshop on Modeling, Analysis and Simulation of Next-Generation Communication Networks 2023 (WueWoWAS'23)}, journal = {KuVS Fachgespr{\"a}ch - W{\"u}rzburg Workshop on Modeling, Analysis and Simulation of Next-Generation Communication Networks 2023 (WueWoWAS'23)}, doi = {10.25972/OPUS-32202}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-322025}, pages = {4}, year = {2023}, abstract = {The emerging serverless computing may meet Edge Cloud in a beneficial manner as the two offer flexibility and dynamicity in optimizing finite hardware resources. However, the lack of proper study of a joint platform leaves a gap in literature about consumption and performance of such integration. To this end, this paper identifies the key questions and proposes a methodology to answer them.}, language = {en} } @techreport{RaffeckGeisslerHossfeld2023, type = {Working Paper}, author = {Raffeck, Simon and Geißler, Stefan and Hoßfeld, Tobias}, title = {Towards Understanding the Signaling Traffic in 5G Core Networks}, series = {KuVS Fachgespr{\"a}ch - W{\"u}rzburg Workshop on Modeling, Analysis and Simulation of Next-Generation Communication Networks 2023 (WueWoWAS'23)}, journal = {KuVS Fachgespr{\"a}ch - W{\"u}rzburg Workshop on Modeling, Analysis and Simulation of Next-Generation Communication Networks 2023 (WueWoWAS'23)}, doi = {10.25972/OPUS-32210}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-322106}, pages = {4}, year = {2023}, abstract = {The Fifth Generation (5G) communication technology, its infrastructure and architecture, though already deployed in campus and small scale networks, is still undergoing continuous changes and research. Especially, in the light of future large scale deployments and industrial use cases, a detailed analysis of the performance and utilization with regard to latency and service times constraints is crucial. To this end, a fine granular investigation of the Network Function (NF) based core system and the duration for all the tasks performed by these services is necessary. This work presents the first steps towards analyzing the signaling traffic in 5G core networks, and introduces a tool to automatically extract sequence diagrams and service times for NF tasks from traffic traces.}, language = {en} } @article{WamserSeufertHalletal.2021, author = {Wamser, Florian and Seufert, Anika and Hall, Andrew and Wunderer, Stefan and Hoßfeld, Tobias}, title = {Valid statements by the crowd: statistical measures for precision in crowdsourced mobile measurements}, series = {Network}, volume = {1}, journal = {Network}, number = {2}, issn = {2673-8732}, doi = {10.3390/network1020013}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-284154}, pages = {215 -- 232}, year = {2021}, abstract = {Crowdsourced network measurements (CNMs) are becoming increasingly popular as they assess the performance of a mobile network from the end user's perspective on a large scale. Here, network measurements are performed directly on the end-users' devices, thus taking advantage of the real-world conditions end-users encounter. However, this type of uncontrolled measurement raises questions about its validity and reliability. The problem lies in the nature of this type of data collection. In CNMs, mobile network subscribers are involved to a large extent in the measurement process, and collect data themselves for the operator. The collection of data on user devices in arbitrary locations and at uncontrolled times requires means to ensure validity and reliability. To address this issue, our paper defines concepts and guidelines for analyzing the precision of CNMs; specifically, the number of measurements required to make valid statements. In addition to the formal definition of the aspect, we illustrate the problem and use an extensive sample data set to show possible assessment approaches. This data set consists of more than 20.4 million crowdsourced mobile measurements from across France, measured by a commercial data provider.}, language = {en} } @techreport{GrigorjewSchumannDiederichetal.2023, type = {Working Paper}, author = {Grigorjew, Alexej and Schumann, Lukas Kilian and Diederich, Philip and Hoßfeld, Tobias and Kellerer, Wolfgang}, title = {Understanding the Performance of Different Packet Reception and Timestamping Methods in Linux}, series = {KuVS Fachgespr{\"a}ch - W{\"u}rzburg Workshop on Modeling, Analysis and Simulation of Next-Generation Communication Networks 2023 (WueWoWAS'23)}, journal = {KuVS Fachgespr{\"a}ch - W{\"u}rzburg Workshop on Modeling, Analysis and Simulation of Next-Generation Communication Networks 2023 (WueWoWAS'23)}, doi = {10.25972/OPUS-32206}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-322064}, pages = {5}, year = {2023}, abstract = {This document briefly presents some renowned packet reception techniques for network packets in Linux systems. Further, it compares their performance when measuring packet timestamps with respect to throughput and accuracy. Both software and hardware timestamps are compared, and various parameters are examined, including frame size, link speed, network interface card, and CPU load. The results indicate that hardware timestamping offers significantly better accuracy with no downsides, and that packet reception techniques that avoid system calls offer superior measurement throughput.}, language = {en} } @article{HossfeldHeegaardSkrorinKapovetal.2020, author = {Hoßfeld, Tobias and Heegaard, Poul E. and Skrorin-Kapov, Lea and Varela, Mart{\´i}n}, title = {Deriving QoE in systems: from fundamental relationships to a QoE-based Service-level Quality Index}, series = {Quality and User Experience}, volume = {5}, journal = {Quality and User Experience}, issn = {2366-0139}, doi = {10.1007/s41233-020-00035-0}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-235597}, year = {2020}, abstract = {With Quality of Experience (QoE) research having made significant advances over the years, service and network providers aim at user-centric evaluation of the services provided in their system. The question arises how to derive QoE in systems. In the context of subjective user studies conducted to derive relationships between influence factors and QoE, user diversity leads to varying distributions of user rating scores for different test conditions. Such models are commonly exploited by providers to derive various QoE metrics in their system, such as expected QoE, or the percentage of users rating above a certain threshold. The question then becomes how to combine (a) user rating distributions obtained from subjective studies, and (b) system parameter distributions, so as to obtain the actual observed QoE distribution in the system? Moreover, how can various QoE metrics of interest in the system be derived? We prove fundamental relationships for the derivation of QoE in systems, thus providing an important link between the QoE community and the systems community. In our numerical examples, we focus mainly on QoE metrics. We furthermore provide a more generalized view on quantifying the quality of systems by defining a QoE-based Service-level Quality Index. This index exploits the fact that quality can be seen as a proxy measure for utility. Following the assumption that not all user sessions should be weighted equally, we aim to provide a generic framework that can be utilized to quantify the overall utility of a service delivered by a system.}, language = {en} } @techreport{LohRaffeckGeissleretal.2023, type = {Working Paper}, author = {Loh, Frank and Raffeck, Simon and Geißler, Stefan and Hoßfeld, Tobias}, title = {Paving the Way for an Energy Efficient and Sustainable Future Internet of Things}, series = {KuVS Fachgespr{\"a}ch - W{\"u}rzburg Workshop on Modeling, Analysis and Simulation of Next-Generation Communication Networks 2023 (WueWoWAS'23)}, journal = {KuVS Fachgespr{\"a}ch - W{\"u}rzburg Workshop on Modeling, Analysis and Simulation of Next-Generation Communication Networks 2023 (WueWoWAS'23)}, doi = {10.25972/OPUS-32216}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-322161}, pages = {4}, year = {2023}, abstract = {In this work, we describe the network from data collection to data processing and storage as a system based on different layers. We outline the different layers and highlight major tasks and dependencies with regard to energy consumption and energy efficiency. With this view, we can outwork challenges and questions a future system architect must answer to provide a more sustainable, green, resource friendly, and energy efficient application or system. Therefore, all system layers must be considered individually but also altogether for future IoT solutions. This requires, in particular, novel sustainability metrics in addition to current Quality of Service and Quality of Experience metrics to provide a high power, user satisfying, and sustainable network.}, language = {en} } @article{SeufertPoigneeHossfeldetal.2022, author = {Seufert, Anika and Poign{\´e}e, Fabian and Hoßfeld, Tobias and Seufert, Michael}, title = {Pandemic in the digital age: analyzing WhatsApp communication behavior before, during, and after the COVID-19 lockdown}, series = {Humanities and Social Sciences Communications}, volume = {9}, journal = {Humanities and Social Sciences Communications}, doi = {10.1057/s41599-022-01161-0}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-300261}, year = {2022}, abstract = {The strict restrictions introduced by the COVID-19 lockdowns, which started from March 2020, changed people's daily lives and habits on many different levels. In this work, we investigate the impact of the lockdown on the communication behavior in the mobile instant messaging application WhatsApp. Our evaluations are based on a large dataset of 2577 private chat histories with 25,378,093 messages from 51,973 users. The analysis of the one-to-one and group conversations confirms that the lockdown severely altered the communication in WhatsApp chats compared to pre-pandemic time ranges. In particular, we observe short-term effects, which caused an increased message frequency in the first lockdown months and a shifted communication activity during the day in March and April 2020. Moreover, we also see long-term effects of the ongoing pandemic situation until February 2021, which indicate a change of communication behavior towards more regular messaging, as well as a persisting change in activity during the day. The results of our work show that even anonymized chat histories can tell us a lot about people's behavior and especially behavioral changes during the COVID-19 pandemic and thus are of great relevance for behavioral researchers. Furthermore, looking at the pandemic from an Internet provider perspective, these insights can be used during the next pandemic, or if the current COVID-19 situation worsens, to adapt communication networks to the changed usage behavior early on and thus avoid network congestion.}, language = {en} } @article{SeufertPoigneeSeufertetal.2023, author = {Seufert, Anika and Poign{\´e}e, Fabian and Seufert, Michael and Hoßfeld, Tobias}, title = {Share and multiply: modeling communication and generated traffic in private WhatsApp groups}, series = {IEEE Access}, volume = {11}, journal = {IEEE Access}, doi = {10.1109/ACCESS.2023.3254913}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-349430}, pages = {25401-25414}, year = {2023}, abstract = {Group-based communication is a highly popular communication paradigm, which is especially prominent in mobile instant messaging (MIM) applications, such as WhatsApp. Chat groups in MIM applications facilitate the sharing of various types of messages (e.g., text, voice, image, video) among a large number of participants. As each message has to be transmitted to every other member of the group, which multiplies the traffic, this has a massive impact on the underlying communication networks. However, most chat groups are private and network operators cannot obtain deep insights into MIM communication via network measurements due to end-to-end encryption. Thus, the generation of traffic is not well understood, given that it depends on sizes of communication groups, speed of communication, and exchanged message types. In this work, we provide a huge data set of 5,956 private WhatsApp chat histories, which contains over 76 million messages from more than 117,000 users. We describe and model the properties of chat groups and users, and the communication within these chat groups, which gives unprecedented insights into private MIM communication. In addition, we conduct exemplary measurements for the most popular message types, which empower the provided models to estimate the traffic over time in a chat group.}, language = {en} } @article{LohWamserPoigneeetal.2022, author = {Loh, Frank and Wamser, Florian and Poign{\´e}e, Fabian and Geißler, Stefan and Hoßfeld, Tobias}, title = {YouTube Dataset on Mobile Streaming for Internet Traffic Modeling and Streaming Analysis}, series = {Scientific Data}, volume = {9}, journal = {Scientific Data}, number = {1}, doi = {10.1038/s41597-022-01418-y}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-300240}, year = {2022}, 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.}, language = {en} }