Traffic management genetic algorithm supporting data mining and qos in sensor networks

Authors:
Yantao Pan;Wei Peng;Xicheng Lu
Affiliations:
School of Computer, National University of Defense Technology, Changsha, P.R. China;School of Computer, National University of Defense Technology, Changsha, P.R. China;School of Computer, National University of Defense Technology, Changsha, P.R. China
Venue:
ADMA'06 Proceedings of the Second international conference on Advanced Data Mining and Applications
Year:
2006

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Abstract

Sensor networks are expected to be used for spatial cognition in harsh environments. When an event happens, there will be several sensors detect it and send their reports to a sink, but these data are neither integrated nor reliable. Therefore, it is reasonable to make use of data mining on intermediate nodes to acquire deeper knowledge on an event and cut down the total traffic at the same time. Furthermore, the QoS requests should be considered too. In this paper, we propose a centralized algorithm to achieve optimal traffic management on sensor networks with considering QoS and data fusion. Its efficiency is shown by experiments.