A distributed heuristic solution to the target identifiability problem in directional sensor networks

Wilson M. Tan, Stephen A. Jarvis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Existing algorithms for orienting sensors in directional sensor networks have primarily concerned themselves with the problem of maximizing the number of covered targets, assuming that target identification as a non-issue. Such an assumption however, does not hold true in all situations. In this paper, a distributed heuristic algorithm for choosing active sensors and orienting them with the goal of balancing coverage and identifiability is presented. The performance of the algorithm is verified via simulations, and shown through simulations to confer increased target identifiability compared to algorithms originally designed to simply maximize the number of targets covered.

Original languageEnglish
Title of host publication2015 International Conference on Computing, Networking and Communications, ICNC 2015
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages176-182
Number of pages7
ISBN (Electronic)9781479969593
DOIs
Publication statusPublished - 26 Mar 2015
Event2015 International Conference on Computing, Networking and Communications, ICNC 2015 - Garden Grove, United States
Duration: 16 Feb 201519 Feb 2015

Publication series

Name2015 International Conference on Computing, Networking and Communications, ICNC 2015

Conference

Conference2015 International Conference on Computing, Networking and Communications, ICNC 2015
Country/TerritoryUnited States
CityGarden Grove
Period16/02/1519/02/15

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

Keywords

  • coverage quality
  • directional sensing antenna
  • heuristic algorithm
  • sensor networks

ASJC Scopus subject areas

  • Computer Networks and Communications

Fingerprint

Dive into the research topics of 'A distributed heuristic solution to the target identifiability problem in directional sensor networks'. Together they form a unique fingerprint.

Cite this