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Constrained artificial fish-swarm based area coverage optimization algorithm for directional sensor networks

  • Beijing Jiaotong University
  • Beijing University of Posts and Telecommunications

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

15 Scopus citations

Abstract

In this paper, we explore the area coverage optimization problem by directional sensors with tunable sensing orientations. We firstly introduce the concept of 'sensing centroid', which is the geometric center of a sensing sector to simplify the pending problem. Particularly, we regard 'sensing centroid' as artificial fish (AF), and search an optimal solution in the solution space by simulating fish swarm behaviors (such as prey, swarm and follow) with a tendency toward high food consistence. Fully considering that AFs have to satisfy both kinematic constraint and dynamic constraint in the process of motion, we propose a Constrained Artificial Fish-Swarm Algorithm (CAFSA), and discuss the control laws to guide the behaviors of AFs with high convergence speed. Finally, we evaluate the effect of some primary parameters on the performance of our solution through extensive simulations.

Original languageEnglish
Title of host publicationProceedings - IEEE 10th International Conference on Mobile Ad-Hoc and Sensor Systems, MASS 2013
Pages304-309
Number of pages6
DOIs
StatePublished - 2013
Event10th IEEE International Conference on Mobile Ad-Hoc and Sensor Systems, MASS 2013 - Hangzhou, China
Duration: Oct 14 2013Oct 16 2013

Publication series

NameProceedings - IEEE 10th International Conference on Mobile Ad-Hoc and Sensor Systems, MASS 2013

Conference

Conference10th IEEE International Conference on Mobile Ad-Hoc and Sensor Systems, MASS 2013
Country/TerritoryChina
CityHangzhou
Period10/14/1310/16/13

Keywords

  • Area coverage
  • Artificial fish-swarm
  • Coverage optimization
  • Directional sensor networks
  • Swarm intelligence

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