TY - JOUR A1 - Loh, Frank A1 - Poignée, Fabian A1 - Wamser, Florian A1 - Leidinger, Ferdinand A1 - Hoßfeld, Tobias T1 - Uplink vs. Downlink: Machine Learning-Based Quality Prediction for HTTP Adaptive Video Streaming JF - Sensors N2 - 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. KW - HTTP adaptive video streaming KW - quality of experience prediction KW - machine learning Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-241121 SN - 1424-8220 VL - 21 IS - 12 ER - TY - RPRT A1 - Loh, Frank A1 - Geißler, Stefan A1 - Hoßfeld, Tobias T1 - LoRaWAN Network Planning in Smart Environments: Towards Reliability, Scalability, and Cost Reduction T2 - Würzburg Workshop on Next-Generation Communication Networks (WueWoWas'22) N2 - 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. KW - Datennetz KW - LoRaWan Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-280829 ER - TY - JOUR A1 - Loh, Frank A1 - Mehling, Noah A1 - Hoßfeld, Tobias T1 - Towards LoRaWAN without data loss: studying the performance of different channel access approaches JF - Sensors N2 - The Long Range Wide Area Network (LoRaWAN) is one of the fastest growing Internet of Things (IoT) access protocols. It operates in the license free 868 MHz band and gives everyone the possibility to create their own small sensor networks. The drawback of this technology is often unscheduled or random channel access, which leads to message collisions and potential data loss. For that reason, recent literature studies alternative approaches for LoRaWAN channel access. In this work, state-of-the-art random channel access is compared with alternative approaches from the literature by means of collision probability. Furthermore, a time scheduled channel access methodology is presented to completely avoid collisions in LoRaWAN. For this approach, an exhaustive simulation study was conducted and the performance was evaluated with random access cross-traffic. In a general theoretical analysis the limits of the time scheduled approach are discussed to comply with duty cycle regulations in LoRaWAN. KW - LoRaWAN KW - IoT KW - channel management KW - scheduling KW - collision Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-302418 SN - 1424-8220 VL - 22 IS - 2 ER - TY - JOUR A1 - Loh, Frank A1 - Wamser, Florian A1 - Poignée, Fabian A1 - Geißler, Stefan A1 - Hoßfeld, Tobias T1 - YouTube Dataset on Mobile Streaming for Internet Traffic Modeling and Streaming Analysis JF - Scientific Data N2 - 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. KW - internet traffic KW - mobile streaming KW - YouTube Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-300240 VL - 9 IS - 1 ER - TY - RPRT A1 - Nguyen, Kien A1 - Loh, Frank A1 - Hoßfeld, Tobias T1 - Challenges of Serverless Deployment in Edge-MEC-Cloud T2 - KuVS Fachgespräch - Würzburg Workshop on Modeling, Analysis and Simulation of Next-Generation Communication Networks 2023 (WueWoWAS’23) N2 - 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. KW - Edge-MEC-Cloud Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-322025 ER - TY - RPRT A1 - Loh, Frank A1 - Raffeck, Simon A1 - Geißler, Stefan A1 - Hoßfeld, Tobias T1 - Paving the Way for an Energy Efficient and Sustainable Future Internet of Things T2 - KuVS Fachgespräch - Würzburg Workshop on Modeling, Analysis and Simulation of Next-Generation Communication Networks 2023 (WueWoWAS’23) N2 - 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. KW - Internet of Things KW - energy efficiency KW - sustainability Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-322161 ER - TY - THES A1 - Loh, Frank T1 - Monitoring the Quality of Streaming and Internet of Things Applications T1 - Monitoring der Qualität von Video Streaming und Internet der Dingen Anwendungen N2 - The ongoing and evolving usage of networks presents two critical challenges for current and future networks that require attention: (1) the task of effectively managing the vast and continually increasing data traffic and (2) the need to address the substantial number of end devices resulting from the rapid adoption of the Internet of Things. Besides these challenges, there is a mandatory need for energy consumption reduction, a more efficient resource usage, and streamlined processes without losing service quality. We comprehensively address these efforts, tackling the monitoring and quality assessment of streaming applications, a leading contributor to the total Internet traffic, as well as conducting an exhaustive analysis of the network performance within a Long Range Wide Area Network (LoRaWAN), one of the rapidly emerging LPWAN solutions. N2 - Die fortlaufende und sich weiterentwickelnde Nutzung von Netzwerken stellt zwei entscheidende Herausforderungen für aktuelle und zukünftige Netzwerke dar, die Aufmerksamkeit erfordern: (1) die Aufgabe, den enormen und kontinuierlich wachsenden Datenverkehr effektiv zu verwalten, und (2) die Notwendigkeit, die durch die Einführung des Internets der Dinge resultierende große Anzahl von Endgeräten zu bewältigen. Neben diesen Herausforderungen besteht ein zwingender Bedarf an einer Reduzierung des Energieverbrauchs, einer effizienteren Ressourcennutzung und von optimierten Prozessen ohne Einbußen bei der Servicequalität. Wir gehen diese Bemühungen umfassend an und befassen uns mit der Überwachung und Qualitätsbewertung von Streaming-Anwendungen, die einen wesentlichen Beitrag zum gesamten Internetverkehr leisten, sowie mit der Durchführung einer generellen Analyse der Netzwerkleistung innerhalb eines Long Range Wide Area Network (LoRaWAN), einer der am schnellsten wachsenden LPWAN-Lösungen. T3 - Würzburger Beiträge zur Leistungsbewertung Verteilter Systeme - 01/24 KW - Leistungsbewertung KW - Simulation KW - LoRaWAN KW - Quality of Experience KW - Streaming KW - Leistungsbewertung KW - Simulation KW - LoRaWAN KW - Quality of Experience KW - Video Streaming Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-350969 SN - 1432-8801 N1 - Formal korrigierte, inhaltlich identische Version zur Dissertation unter https://doi.org/10.25972/OPUS-34783. ET - korrigierte Version ER - TY - THES A1 - Loh, Frank T1 - Monitoring the Quality of Streaming and Internet of Things Applications T1 - Monitoring der Qualität von Video Streaming und Internet der Dingen Anwendungen N2 - The ongoing and evolving usage of networks presents two critical challenges for current and future networks that require attention: (1) the task of effectively managing the vast and continually increasing data traffic and (2) the need to address the substantial number of end devices resulting from the rapid adoption of the Internet of Things. Besides these challenges, there is a mandatory need for energy consumption reduction, a more efficient resource usage, and streamlined processes without losing service quality. We comprehensively address these efforts, tackling the monitoring and quality assessment of streaming applications, a leading contributor to the total Internet traffic, as well as conducting an exhaustive analysis of the network performance within a Long Range Wide Area Network (LoRaWAN), one of the rapidly emerging LPWAN solutions. N2 - Die fortlaufende und sich weiterentwickelnde Nutzung von Netzwerken stellt zwei entscheidende Herausforderungen für aktuelle und zukünftige Netzwerke dar, die Aufmerksamkeit erfordern: (1) die Aufgabe, den enormen und kontinuierlich wachsenden Datenverkehr effektiv zu verwalten, und (2) die Notwendigkeit, die durch die Einführung des Internets der Dinge resultierende große Anzahl von Endgeräten zu bewältigen. Neben diesen Herausforderungen besteht ein zwingender Bedarf an einer Reduzierung des Energieverbrauchs, einer effizienteren Ressourcennutzung und von optimierten Prozessen ohne Einbußen bei der Servicequalität. Wir gehen diese Bemühungen umfassend an und befassen uns mit der Überwachung und Qualitätsbewertung von Streaming-Anwendungen, die einen wesentlichen Beitrag zum gesamten Internetverkehr leisten, sowie mit der Durchführung einer generellen Analyse der Netzwerkleistung innerhalb eines Long Range Wide Area Network (LoRaWAN), einer der am schnellsten wachsenden LPWAN-Lösungen. T3 - Würzburger Beiträge zur Leistungsbewertung Verteilter Systeme - 01/24 KW - Leistungsbewertung KW - Simulation KW - LoRaWAN KW - Quality of Experience KW - Streaming KW - Video Streaming KW - Energy Efficiency Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-347831 SN - 1432-8801 N1 - Eine formal korrigierte, inhaltlich identische Version dieser Dissertation ist unter https://doi.org/10.25972/OPUS-35096 erschienen. ER -