MaxMAC: a Maximally Traffic-Adaptive MAC Protocol for Wireless Sensor Networks

Hurni, Philipp; Braun, Torsten (2010). MaxMAC: a Maximally Traffic-Adaptive MAC Protocol for Wireless Sensor Networks. In: Silva, Jorge Sá; Krishnamachari, Bhaskar; Boavida, Fernando (eds.) 7th European Conference on Wireless Sensor Networks. Lecture Notes in Computer Science: Vol. 5970 (pp. 289-305). Heidelberg: Springer Verlag 10.1007/978-3-642-11917-0_19

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Energy efficiency is a major concern in the design of Wireless Sensor Networks (WSNs) and their communication protocols. As the radio transceiver typically accounts for a major portion of a WSN node’s power consumption, researchers have proposed Energy-Efficient Medium Access (E2-MAC) protocols that switch the radio transceiver off for a major part of the time. Such protocols typically trade off energy-efficiency versus classical quality of service parameters (throughput, latency, reliability). Today’s E2-MAC protocols are able to deliver little amounts of data with a low energy footprint, but introduce severe restrictions with respect to throughput and latency. Regrettably, they yet fail to adapt to varying traffic load at run-time. This paper presents MaxMAC, an E2-MAC protocol that targets at achieving maximal adaptivity with respect to throughput and latency. By adaptively tuning essential parameters at run-time, the protocol reaches the throughput and latency of energy-unconstrained CSMA in high-traffic phases, while still exhibiting a high energy-efficiency in periods of sparse traffic. The paper compares the protocol against a selection of today’s E2-MAC protocols and evaluates its advantages and drawbacks.

Item Type: Conference or Workshop Item (Paper)
Division/Institute: 08 Faculty of Science > Institute of Computer Science (INF) > Communication and Distributed Systems (CDS)
08 Faculty of Science > Institute of Computer Science (INF)
UniBE Contributor: Hurni, Philipp and Braun, Torsten
ISBN: 978-3-642-11916-3
Series: Lecture Notes in Computer Science
Publisher: Springer Verlag
Language: English
Submitter: Factscience Import
Date Deposited: 04 Oct 2013 14:17
Last Modified: 13 Jan 2015 16:49
Publisher DOI: 10.1007/978-3-642-11917-0_19
Web of Science ID: 000279325200019
URI: http://boris.unibe.ch/id/eprint/4938 (FactScience: 209593)

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