research-article

Game Theory Framework for MAC Parameter Optimization in Energy-Delay Constrained Sensor Networks

Authors:

Messaoud Doudou,

Jose M. Barcelo-Ordinas,

Djamel Djenouri,

Jorge Garcia-Vidal,

Abdelmadjid Bouabdallah,

Nadjib BadacheAuthors Info & Claims

ACM Transactions on Sensor Networks (TOSN), Volume 12, Issue 2

Article No.: 10, Pages 1 - 35

https://doi.org/10.1145/2883615

Published: 03 May 2016 Publication History

Abstract

Optimizing energy consumption and end-to-end (e2e) packet delay in energy-constrained, delay-sensitive wireless sensor networks is a conflicting multiobjective optimization problem. We investigate the problem from a game theory perspective, where the two optimization objectives are considered as game players. The cost model of each player is mapped through a generalized optimization framework onto protocol-specific MAC parameters. From the optimization framework, a game is first defined by the Nash bargaining solution (NBS) to assure energy consumption and e2e delay balancing. Secondy, the Kalai-Smorodinsky bargaining solution (KSBS) is used to find an equal proportion of gain between players. Both methods offer a bargaining solution to the duty-cycle MAC protocol under different axioms. As a result, given the two performance requirements (i.e., the maximum latency tolerated by the application and the initial energy budget of nodes), the proposed framework allows to set tunable system parameters to reach a fair equilibrium point that dually minimizes the system latency and energy consumption. For illustration, this formulation is applied to six state-of-the-art wireless sensor network (WSN) MAC protocols: B-MAC, X-MAC, RI-MAC, SMAC, DMAC, and LMAC. The article shows the effectiveness and scalability of such a framework in optimizing protocol parameters that achieve a fair energy-delay performance trade-off under the application requirements.

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Game Theory Framework for MAC Parameter Optimization in Energy-Delay Constrained Sensor Networks

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cover image ACM Transactions on Sensor Networks

ACM Transactions on Sensor Networks Volume 12, Issue 2

May 2016

323 pages

ISSN:1550-4859

EISSN:1550-4867

DOI:10.1145/2925994

Editor:
Chenyang Lu
Department of Computer Science and Engineering / School of Engineering and Applied Sciences / Washington University / 1 Brookings Drive / St. Louis, MO 63130

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Publication History

Published: 03 May 2016

Accepted: 01 January 2016

Revised: 01 October 2015

Received: 01 April 2015

Published in TOSN Volume 12, Issue 2

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