A point-distribution index and its application to sensor-grouping in wireless sensor networks

Authors:
Yangfan Zhou;Haixuan Yang;Michael R. Lyu;Edith C.-H. Ngai
Affiliations:
The Chinese University of Hong Kong, Hong Kong, China;The Chinese University of Hong Kong, Hong Kong, China;The Chinese University of Hong Kong, Hong Kong, China;The Chinese University of Hong Kong, Hong Kong, China
Venue:
Proceedings of the 2006 international conference on Wireless communications and mobile computing
Year:
2006

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Abstract

We propose ι a novel index for evaluation of point-distribution. ι is the minimum distance between each pair of points normalized by the average distance between each pair of points. We find that a set of points that achieve a maximum value of ι result in a honeycomb structure. We propose that ι can serve as a good index to evaluate the distribution of the points, which can be employed in coverage-related problems in wireless sensor networks (WSNs). To validate this idea, we formulate a general sensorgrouping problem for WSNs and provide a general sensing model. We show that locally maximizing ι at sensor nodes is a good approach to solve this problem with an algorithm called Maximizing-ι Node-Deduction (MIND). Simulation results verify that MIND outperforms a greedy algorithm that exploits sensor-redundancy we design. This demonstrates a good application of employing ι in coverage-related problems for WSNs.