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Adaptive Learning Based Scheduling in Multichannel Protocol for Energy-Efficient Data-Gathering Wireless Sensor Networks This publication appears in: International Journal of Distributed Sensor Networks Authors: K. Ha Phung, B. Lemmens, M. Emilov Mihaylov, L. Tran and K. Steenhaut Issue: vol. 2013, Article ID 345821, doi:10.1155/2013/34 Number of Pages: 11 Publication Date: Feb. 2013
Abstract: Multi-channel 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 multi-channel 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. External Link.
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