Poster Abstract: A benchmark for low-power wireless networking
Paper in proceeding, 2016
Experimental research in low-power wireless networking lacks a reference benchmark. While other communities such as databases or machine learning have standardized bench-marks, our community still uses ad-hoc setups for its exper-iments and struggles to provide a fair comparison between communication protocols. Reasons for this include the di-versity of network scenarios and the stochastic nature of wireless experiments. Leveraging on the excellent testbeds and tools that have been built to support experimental val-idation, we make the case for a reference benchmark to pro-mote a fair comparison and reproducibility of results. This abstract describes early design elements and a benchmark-ing methodology with the goal to gather feedback from the community rather than propose a definite solution.
Network scenario
Reference benchmarks
Stochastic systems
Wireless networks Early designs
Experimental research
Engineering controlled terms: Embedded systems
Learning systems
Stochastic nature
Reproducibilities
Low power wireless networkings
Author
Simon Duquennoy
Institut National de Recherche en Informatique et en Automatique (INRIA)
SICS Swedish ICT AB
Olaf Landsiedel
Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)
C. A. Boano
Technische Universität Graz
Marco Zimmerling
Technische Universität Dresden
J. Beutel
Swiss Federal Institute of Technology in Zürich (ETH)
M. C. Chan
National University of Singapore (NUS)
O. Gnawali
University of Houston
M. Mohammad
National University of Singapore (NUS)
L. Mottola
Polytechnic University of Milan
SICS Swedish ICT AB
L. Thiele
Swiss Federal Institute of Technology in Zürich (ETH)
X. Vilajosana
Open University of Catalonia (UOC)
Thiemo Voigt
SICS Swedish ICT AB
Uppsala University
T. Watteyne
Institut National de Recherche en Informatique et en Automatique (INRIA)
Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems
Vol. 14 November 2016 332-333
978-145034263-6 (ISBN)
4th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016
Stanford, USA,
Stanford, USA,
Driving Forces
Sustainable development
Subject Categories
Other Electrical Engineering, Electronic Engineering, Information Engineering
DOI
10.1145/2994551.2996692