Paper Info
Title
Distributed wireless sensor scheduling for multi-target tracking based on matrix-coded parallel genetic algorithm
Abstract
The aim of designing a sensor scheduling scheme for target tracking in wireless sensor network is to improve the tracking accuracy, balance the network energy and prolong the network lifespan. It is viewed as a multi-objective optimization problem. A modified matrix-coded parallel genetic algorithm (MPGA) is proposed in which multiple subpopulations evolve synchronously and satify the specific constraint arised from the senario of multi-target tracking that a sensor can only track just one target. Simulation results show that MPGA, compared with traditional genetic algorithm, converges to the better result with higher speed when applied in multi-target tracking in wireless sensor network. And our proposed distributed sensor scheduling scheme based on MPGA outperforms than existed schemes.
Year
DOI
Venue
2014
10.1109/CEC.2014.6900451
IEEE Congress on Evolutionary Computation
Keywords
Field
DocType
network energy,matrix-coded parallel genetic algorithm,network lifespan,multi-target tracking,distributed wireless sensor scheduling,target tracking,wireless sensor network,sensor scheduling scheme,mpga,tracking accuracy,genetic algorithms,wireless sensor networks,multiobjective optimization problem,accuracy,scheduling,energy efficiency
Key distribution in wireless sensor networks,Wireless,Computer science,Scheduling (computing),Brooks–Iyengar algorithm,Real-time computing,Mobile wireless sensor network,Wireless sensor network,Optimization problem,Genetic algorithm
Conference
Citations 
PageRank 
References 
0
0.34
6
Authors
3
Name
Order
Citations
PageRank
Zixing Cai1152566.96
Sha Wen221.76
Lijue Liu323.05