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

Published: 03 July 2006 Publication History

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.

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cover image ACM Conferences
IWCMC '06: Proceedings of the 2006 international conference on Wireless communications and mobile computing
July 2006
2006 pages
ISBN:1595933069
DOI:10.1145/1143549
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 03 July 2006

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Author Tags

  1. honeycomb structure
  2. point-distribution index
  3. sensor coverage
  4. sensor grouping
  5. wireless sensor networks

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