ISSN : 1796-2021
Volume : 1    Issue : 2    Date : May 2006

A Learning-based Adaptive Routing Tree for Wireless Sensor Networks
Ying Zhang and Qingfeng Huang
Page(s): 12-21
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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.

Index Terms
constraint-based routing, real-time reinforcement learning, routing tree, wireless sensor networks