Work place: Bonn-Rhein-Sieg University of Applied Sciences, Dept. of Computer Science, Sankt Augustin, 53757, Germany
E-mail: mleischner@h-brs.de
Website:
Research Interests: Computer Architecture and Organization, Network Security, Database Management System, Data Structures and Algorithms
Biography
Martin Leischner studied Mathematics and Computer Science in Ludwig Maximilian University of Munich and Technical University of Munich, Germany, respectively; and received his Ph.D. degree in Mathematics in the year 1987 from Ludwig Maximilian University of Munich. He is currently Professor in Department of Computer Science at Bonn-Rhein-Sieg University of Applied Sciences, Germany. His research interests include internet communication, network management and security.
By Fatih Abut Martin Leischner
DOI: https://doi.org/10.5815/ijcnis.2018.07.01, Pub. Date: 8 Jul. 2018
For many different applications, current information about the bandwidth-related metrics of the utilized connection is very useful as they directly impact the performance of throughput sensitive applications such as streaming servers, IPTV and VoIP applications. In literature, several tools have been proposed to estimate major bandwidth-related metrics such as capacity, available bandwidth and achievable throughput. The vast majority of these tools fall into one of Packet Pair (PP), Variable Packet Size (VPS), Self-Loading of Periodic Streams (SLoPS) or Throughput approaches. In this study, seven popular bandwidth estimation tools including nettimer, pathrate, pathchar, pchar, clink, pathload and iperf belonging to these four well-known estimation techniques are presented and experimentally evaluated in a controlled testbed environment. Differently from the rest of studies in literature, all tools have been uniformly classified and evaluated according to an objective and sophisticated classification and evaluation scheme. The performance comparison of the tools incorporates not only the estimation accuracy but also the probing time and overhead caused.
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