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International Journal of Distributed Sensor Networks
Volume 2013 (2013), Article ID 345821, 11 pages
http://dx.doi.org/10.1155/2013/345821
Research Article

Adaptive Learning Based Scheduling in Multichannel Protocol for Energy-Efficient Data-Gathering Wireless Sensor Networks

1Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussel, Belgium
2School of Electronics and Telecommunications, Hanoi University of Science and Technology, Dai Co Viet 01, Hanoi, Vietnam
3Department IWT, Erasmushogeschool Brussel, Nijverheidskaai 170, 1070 Brussel, Belgium
4Faculty of Science and Bio-Engineering Sciences (DINF), Vrije Universiteit Brussel, Pleinlaan 02, 1050 Brussel, Belgium

Received 26 October 2012; Accepted 8 January 2013

Academic Editor: Jiman Hong

Copyright © 2013 Kieu-Ha Phung et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Multichannel communication protocols have been developed to alleviate the effects of interference and consequently improve the network performance in wireless sensor networks requiring high bandwidth. In this paper, we propose a contention-free multichannel protocol to maximize network throughput while ensuring energy-efficient operation. Arguing that routing decisions influence to a large extent the network throughput, we formulate route selection and transmission scheduling as a joint problem and propose a Reinforcement Learning based scheduling algorithm to solve it in a distributed manner. The results of extensive simulation experiments show that the proposed solution not only provides a collision-free transmission schedule but also minimizes energy waste, which makes it appropriate for energy-constrained wireless sensor networks.