Tools and Datasets
As a result of different research projects, the chair has published several tools and datasets.
The tools are used to conduct studies, implement algorithms, simplify the analysis of problems, or visualize a task. The datasets contain measured records that serve as a basis for reproducibility and reference for scientific work.
Tools
WhatsAnalyzer is a web-based tool to collect and analyze chat histories of the mobile messaging application WhatsApp. With the help of this tool, we analyze the group communication behavior in WhatsApp and investigate possible implications of this emerging communication paradigm on networking technology.
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YoMo-Docker is a Docker container to actively measure QoE related factors of YouTube video streaming. The measurement concept is based on emulating a virtual end-user device requesting video streams, which are then monitored at the network and application layers, on the basis of QoE-relevant features.
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YomoApp (YouTube Monitoring App) is an Android app. With it you can watch YouTube videos and rate the quality of the streaming. On a map, you can see how well your own network and other networks are working in different locations. So you can easily compare different providers and can see directly where the mobile network works well and where it has to be improved. Developers can download data about the streaming performance.
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Wrapper App is a measurement application to measure the native YouTube app for smartphones from the Google Play Store. Among other things, the current quality and playing time is read from the app and written in a log file.
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EdgeNetworkCloudSim is an extension of NetworkCloudSim to simulate an edge cloud networking scenarios.
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KOMon is a tool developed to characterize and monitor the packet processing times of softwareized network functions by performing in-stack monitoring. In-stack monitoring leverages the network stack of the platform it is deployed on to monitor packets with high accuracy and low overhead.
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JTableVisor is a transparent proxy-layer for the OpenFlow control channel. It enables a flexible and scalable abstraction of multiple data plane devices into one emulated data plane switch, meeting the requirements of the control plane applications. Therefor, TableVisor registers with the SDN controller as a single switch with use-case specific capabilities. It translates instructions and rules from control applications towards the appropriate data plane device where they are executed.
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MO-VNFCP is a multi-objective heuristic and deals with the VNF chain placement problem (VNFCP). For a given network situation, the task consists of determining the number, location, and assignment of VNF instances and the routing of demands. At the same time, several metrics like CPU utilization and the delay of individual flows need to be taken into account. For applicability in networks with dynamically changing conditions, algorithms need to explore the solution space of this NP-hard problem in a timely manner.
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ERWIN is a proof of concept implementation of a web-based editor which allows the injection of latencies in arbitrary workflows. We aim at closing this gap by describing such a generalized methodology for assessing delay effects in a broad range of systems. The goal of this methodology is to i) lower the barrier for conducting delay assessment studies by avoiding the need for expert knowledge in system development and ii) to allow for reproducible studies. By this we aim at making a generalized test methodology available to a broad set of researchers to stimulate further research.
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Datasets
QoE3 (qoecube) is a dataset for YouTube's mobile streaming client, which follows the popular Dynamic Adaptive Streaming over HTTP (DASH) standard. The data was measured over 4 months, at 2 separate locations in Europe, at the network, transport and application layer for DASH.
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VideoMon-IJNM2018 Leveraging the Measuring Mobile Broadband Networks in Europe (MONROE) test bed that enables experimentation with 13 different network configurations in four countries, we collect more than 2114 measurement samples in operational mobile networks. Per sample we collected, among other things, the available bandwidth, signal strength as well as application layer video QoS data.
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Initial Delay Dataset YouTube is an extensive dataset to study the response time of YouTube's mobile video streaming service on Android. The dataset consists of time-synchronized log files from the network, transport, and application layer. The measurements were performed from November 23, 2017 to February 05, 2019 for 75 network scenarios and include 4498 runs with 783.88 hours of video playback time.
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