TY - RPRT A1 - Funda, Christoph A1 - Konheiser, Tobias A1 - German, Reinhard A1 - Hielscher, Kai-Steffen T1 - How to Model and Predict the Scalability of a Hardware-In-The-Loop Test Bench for Data Re-Injection? T2 - KuVS Fachgespräch - Würzburg Workshop on Modeling, Analysis and Simulation of Next-Generation Communication Networks 2023 (WueWoWAS’23) N2 - This paper describes a novel application of an empirical network calculus model based on measurements of a hardware-in-the-loop (HIL) test system. The aim is to predict the performance of a HIL test bench for open-loop re-injection in the context of scalability. HIL test benches are distributed computer systems including software, hardware, and networking devices. They are used to validate complex technical systems, but have not yet been system under study themselves. Our approach is to use measurements from the HIL system to create an empirical model for arrival and service curves. We predict the performance and design the previously unknown parameters of the HIL simulator with network calculus (NC), namely the buffer sizes and the minimum needed pre-buffer time for the playback buffer. We furthermore show, that it is possible to estimate the CPU load from arrival and service-curves based on the utilization theorem, and hence estimate the scalability of the HIL system in the context of the number of sensor streams. KW - hardware-in-the-loop simulation KW - computer performance evaluation KW - network calculus KW - scalability evaluation Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-322150 ER - TY - RPRT A1 - Elsayed, Karim A1 - Rizk, Amr T1 - Response Times in Time-to-Live Caching Hierarchies under Random Network Delays T2 - Würzburg Workshop on Next-Generation Communication Networks (WueWoWas'22) N2 - Time-to-Live (TTL) caches decouple the occupancy of objects in cache through object-specific validity timers. Stateof- the art techniques provide exact methods for the calculation of object-specific hit probabilities given entire cache hierarchies with random inter-cache network delays. The system hit probability is a provider-centric metric as it relates to the origin offload, i.e., the decrease in the number of requests that are served by the content origin server. In this paper we consider a user-centric metric, i.e., the response time, which is shown to be structurally different from the system hit probability. Equipped with the state-of-theart exact modeling technique using Markov-arrival processes we derive expressions for the expected object response time and pave a way for its optimization under network delays. KW - Datennetz KW - TTL Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-280843 ER - TY - RPRT A1 - Dworzak, Manuel A1 - Großmann, Marcel A1 - Le, Duy Thanh T1 - Federated Learning for Service Placement in Fog and Edge Computing T2 - KuVS Fachgespräch - Würzburg Workshop on Modeling, Analysis and Simulation of Next-Generation Communication Networks 2023 (WueWoWAS’23) N2 - Service orchestration requires enormous attention and is a struggle nowadays. Of course, virtualization provides a base level of abstraction for services to be deployable on a lot of infrastructures. With container virtualization, the trend to migrate applications to a micro-services level in order to be executable in Fog and Edge Computing environments increases manageability and maintenance efforts rapidly. Similarly, network virtualization adds effort to calibrate IP flows for Software-Defined Networks and eventually route it by means of Network Function Virtualization. Nevertheless, there are concepts like MAPE-K to support micro-service distribution in next-generation cloud and network environments. We want to explore, how a service distribution can be improved by adopting machine learning concepts for infrastructure or service changes. Therefore, we show how federated machine learning is integrated into a cloud-to-fog-continuum without burdening single nodes. KW - fog computing KW - SDN KW - orchestration KW - federated learning Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-322193 ER - TY - RPRT A1 - Deutschmann, Jörg A1 - Hielscher, Kai-Steffen A1 - German, Reinhard T1 - Next-Generation Satellite Communication Networks T2 - Würzburg Workshop on Next-Generation Communication Networks (WueWoWas'22) N2 - This paper gives an overview of our recent activities in the field of satellite communication networks, including an introduction to geostationary satellite systems and Low Earth Orbit megaconstellations. To mitigate the high latencies of geostationary satellite networks, TCP-splitting Performance Enhancing Proxies are deployed. However, these cannot be applied in the case of encrypted transport headers as it is the case for VPNs or QUIC. We summarize performance evaluation results from multiple measurement campaigns. In a recently concluded project, multipath communication was used to combine the advantages of very heterogeneous communication paths: low data rate, low latency (e.g., DSL light) and high data rate, high latency (e.g., geostationary satellite). KW - Datennetz KW - satellite communication KW - Performance Enhancing Proxies KW - transport protocols KW - VPN KW - QUIC KW - multipath communication KW - hybrid access Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-280732 ER - TY - RPRT A1 - Brisch, Fabian A1 - Kassler, Andreas A1 - Vestin, Jonathan A1 - Pieska, Marcus A1 - Amend, Markus T1 - Accelerating Transport Layer Multipath Packet Scheduling for 5G-ATSSS T2 - KuVS Fachgespräch - Würzburg Workshop on Modeling, Analysis and Simulation of Next-Generation Communication Networks 2023 (WueWoWAS’23) N2 - Utilizing multiple access networks such as 5G, 4G, and Wi-Fi simultaneously can lead to increased robustness, resiliency, and capacity for mobile users. However, transparently implementing packet distribution over multiple paths within the core of the network faces multiple challenges including scalability to a large number of customers, low latency, and high-capacity packet processing requirements. In this paper, we offload congestion-aware multipath packet scheduling to a smartNIC. However, such hardware acceleration faces multiple challenges due to programming language and platform limitations. We implement different multipath schedulers in P4 with different complexity in order to cope with dynamically changing path capacities. Using testbed measurements, we show that our CMon scheduler, which monitors path congestion in the data plane and dynamically adjusts scheduling weights for the different paths based on path state information, can process more than 3.5 Mpps packets 25 μs latency. KW - multipath packet scheduling KW - P4 KW - MP-DCCP KW - 5G KW - ATSSSS Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-322052 ER - TY - RPRT A1 - Alfredsson, Rebecka A1 - Kassler, Andreas A1 - Vestin, Jonathan A1 - Pieska, Marcus A1 - Amend, Markus T1 - Accelerating a Transport Layer based 5G Multi-Access Proxy on SmartNIC T2 - Würzburg Workshop on Next-Generation Communication Networks (WueWoWas'22) N2 - Utilizing multiple access technologies such as 5G, 4G, and Wi-Fi within a coherent framework is currently standardized by 3GPP within 5G ATSSS. Indeed, distributing packets over multiple networks can lead to increased robustness, resiliency and capacity. A key part of such a framework is the multi-access proxy, which transparently distributes packets over multiple paths. As the proxy needs to serve thousands of customers, scalability and performance are crucial for operator deployments. In this paper, we leverage recent advancements in data plane programming, implement a multi-access proxy based on the MP-DCCP tunneling approach in P4 and hardware accelerate it by deploying the pipeline on a smartNIC. This is challenging due to the complex scheduling and congestion control operations involved. We present our pipeline and data structures design for congestion control and packet scheduling state management. Initial measurements in our testbed show that packet latency is in the range of 25 μs demonstrating the feasibility of our approach. KW - Datennetz KW - multipath KW - MP-DCCP KW - 5G-ATSSS KW - networking KW - dataplane programming KW - P4 Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-280798 ER - TY - RPRT ED - Hoßfeld, Tobias ED - Wunderer, Stefan T1 - White Paper on Crowdsourced Network and QoE Measurements – Definitions, Use Cases and Challenges N2 - The goal of the white paper at hand is as follows. The definitions of the terms build a framework for discussions around the hype topic ‘crowdsourcing’. This serves as a basis for differentiation and a consistent view from different perspectives on crowdsourced network measurements, with the goal to provide a commonly accepted definition in the community. The focus is on the context of mobile and fixed network operators, but also on measurements of different layers (network, application, user layer). In addition, the white paper shows the value of crowdsourcing for selected use cases, e.g., to improve QoE or regulatory issues. Finally, the major challenges and issues for researchers and practitioners are highlighted. This white paper is the outcome of the Würzburg seminar on “Crowdsourced Network and QoE Measurements” which took place from 25-26 September 2019 in Würzburg, Germany. International experts were invited from industry and academia. They are well known in their communities, having different backgrounds in crowdsourcing, mobile networks, network measurements, network performance, Quality of Service (QoS), and Quality of Experience (QoE). The discussions in the seminar focused on how crowdsourcing will support vendors, operators, and regulators to determine the Quality of Experience in new 5G networks that enable various new applications and network architectures. As a result of the discussions, the need for a white paper manifested, with the goal of providing a scientific discussion of the terms “crowdsourced network measurements” and “crowdsourced QoE measurements”, describing relevant use cases for such crowdsourced data, and its underlying challenges. During the seminar, those main topics were identified, intensively discussed in break-out groups, and brought back into the plenum several times. The outcome of the seminar is this white paper at hand which is – to our knowledge – the first one covering the topic of crowdsourced network and QoE measurements. KW - Crowdsourcing KW - Network Measurements KW - Quality of Service (QoS) KW - Quality of Experience (QoE) KW - crowdsourced network measurements KW - crowdsourced QoE measurements Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-202327 ER -