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摘要:
In this paper, four PSO based distributed algorithms are presented to attain k-coverage in the target filed. In the first algorithm named K-Coverage Particle Swarm Optimization (KPSO), each static sensor which discovers an event in its sensing range, implements Particle Swarm Optimization (PSO) algorithm in a distributed manner on its mobile sensors. The calculation time is considered as a big bottleneck in PSO, so a second algorithm named K-Coverage Virtual Force directed Particle Swarm Optimization (KVFPSO) is presented, comprised of Virtual Force and KPSO algorithms. In the first and second proposed algorithms, the best experiences of the particles were used to determine their speed. It is possible that these responses might not be the final result and cause extra movements. Another algorithm named KVFPSO-Learning Automata (KVFPSO-LA) is introduced based on which the speed of particles is corrected by using the existing knowledge and the feedback from the actual implementation of the algorithm. To improve performance of the algorithm, Improved KVFPSO-LA is introduced, in which static sensors are equipped with learning automata. Simulation results show that the proposed protocols perform well with respect to balanced energy consumption among nodes, thus maximizing network life-time.
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篇名 Improved Dynamic K-Coverage Algorithms in Mobile Sensor Networks
来源期刊 无线传感网络(英文) 学科 工学
关键词 Wireless Sensor Networks K-COVERAGE EVENT COVERAGE Particle SWARM Optimization Learning AUTOMATA
年,卷(期) 2010,(10) 所属期刊栏目
研究方向 页码范围 784-792
页数 9页 分类号 TN92
字数 语种
DOI
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研究主题发展历程
节点文献
Wireless
Sensor
Networks
K-COVERAGE
EVENT
COVERAGE
Particle
SWARM
Optimization
Learning
AUTOMATA
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研究来源
研究分支
研究去脉
引文网络交叉学科
相关学者/机构
期刊影响力
无线传感网络(英文)
月刊
1945-3078
武汉市江夏区汤逊湖北路38号光谷总部空间
出版文献量(篇)
358
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0
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