A learning-based adaptive routing tree for wireless sensor networks

• Journal of Communications

One of the most common communication patterns in sensor networks is routing data to a base station, while the base station can be either static or mobile. Even in static cases, a static spanning tree may not survive for a long time due to failures of sensor nodes. In this paper, we present an adaptive spanning tree routing mechanism, using real-time reinforcement learning strategies. We demonstrate via simulation that without additional control packets for tree maintenance, adaptive spanning trees can maintain the ``best" connectivity to the base station, in spite of node failures or mobility of the base station. And by using a general constraint-based routing specification, one can apply the same strategy to achieve load balancing and to control network congestion effectively in real time.

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citation

Zhang, Y. ; Huang, Q. A learning-based adaptive routing tree for wireless sensor networks. Journal of Communications. 2006 May; 1 (2): 12-21.