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Title: A biologically inspired sensor wakeup control method for wireless sensor networks
Authors: Liang, Y
Cao, J 
Zhang, L 
Wang, R
Pan, Q
Keywords: Ant colony
Sleep/wakeup control
Target tracking
Wireless sensor networks (WSN)
Issue Date: 2010
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on systems, man, and cybernetics. Part C, Applications and reviews, 2010, v. 40, no. 5, 5451121, p. 525-538 How to cite?
Journal: IEEE transactions on systems, man, and cybernetics. Part C, Applications and reviews 
Abstract: This paper presents an artificial ant colony approach to distributed sensor wakeup control (SWC) in wireless sensor networks (WSN) to accomplish the joint task of surveillance and target tracking. Each sensor node is modeled as an ant, and the problem of target detection is modeled as the food locating by ants. Once the food is found, the ant will release pheromone. The communication, invalidation, and fusion of target information are modeled as the processes of pheromone diffusion, loss, and accumulation. Since the accumulated pheromone can measure the existence of a target, it is used to determine the probability of ant-searching activity in the next round. To the best of our knowledge, this is the first biologically inspired SWC method in the WSN. Such a biologically inspired method has multiple desirable advantages. First, it is distributive and does not require a centralized control or cluster leaders. Therefore, it is free of the problems caused by leader failures and can save the communication cost for leader selection. Second, it is robust to false alarms because the pheromone is accumulated temporally and spatially and thus is more reliable for wakeup control. Third, the proposed method does not need the knowledge of node position. Two theorems are presented to analytically determine the key parameters in the method: the minimum and maximum pheromone. Simulations are carried out to evaluate the performance of the proposed method in comparison with representative methods.
ISSN: 1094-6977
DOI: 10.1109/TSMCC.2010.2046411
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