TY - GEN
T1 - Multi-objective optimization of barrier coverage with wireless sensors
AU - Zhang, Xiao
AU - Zhou, Yu
AU - Zhang, Qingfu
AU - Lee, Victor C.S.
AU - Li, Minming
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015
Y1 - 2015
N2 - Barrier coverage focuses on detecting intruders in an attempt to cross a specific region, in which limited-power sensors in these scenarios are supposed to be distributed remotely in an indeterminate way. In this paper, we consider a scenario where sensors with adjustable ranges and a few sink nodes are deployed to form a virtual sensor barrier for monitoring a belt-shaped region and gathering incidents data. The problem takes into account three relevant objectives: minimizing power consumption while meeting the barrier coverage requirement, minimizing the number of active sensors (reliability) andminimizing the transmission distances between active sensors and the nearest sink node (efficiency of data gathering). It is shown that these three objectives are conflicting in some degree. A Problem Specific MOEA/D with local search methods is proposed for finding optimal tradeoff solutions and compared with a classical algorithm. Experimental results indicate that knee regions exist, and these knee regions may provide the best possible tradeoff for decision makers.
AB - Barrier coverage focuses on detecting intruders in an attempt to cross a specific region, in which limited-power sensors in these scenarios are supposed to be distributed remotely in an indeterminate way. In this paper, we consider a scenario where sensors with adjustable ranges and a few sink nodes are deployed to form a virtual sensor barrier for monitoring a belt-shaped region and gathering incidents data. The problem takes into account three relevant objectives: minimizing power consumption while meeting the barrier coverage requirement, minimizing the number of active sensors (reliability) andminimizing the transmission distances between active sensors and the nearest sink node (efficiency of data gathering). It is shown that these three objectives are conflicting in some degree. A Problem Specific MOEA/D with local search methods is proposed for finding optimal tradeoff solutions and compared with a classical algorithm. Experimental results indicate that knee regions exist, and these knee regions may provide the best possible tradeoff for decision makers.
UR - https://www.scopus.com/pages/publications/84925303731
U2 - 10.1007/978-3-319-15892-1_38
DO - 10.1007/978-3-319-15892-1_38
M3 - 会议稿件
AN - SCOPUS:84925303731
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 557
EP - 572
BT - Evolutionary Multi-Criterion Optimization - 8th International Conference, EMO 2015, Proceedings
A2 - Gaspar-Cunha, António
A2 - Antunes, Carlos Henggeler
A2 - Coello, Carlos A. Coello
PB - Springer Verlag
T2 - 8th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2015
Y2 - 29 March 2015 through 1 April 2015
ER -