Consensus Achievement of Decentralized Sensors Using Adapted Particle Swarm Optimization Algorithm | Zendy

Hyunseok Kim | Zendy; Seongju Chang | Zendy; Jinsul Kim | Zendy

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Consensus Achievement of Decentralized Sensors Using Adapted Particle Swarm Optimization Algorithm

Author(s) -

Hyunseok Kim,

Seongju Chang,

Jinsul Kim

Publication year - 2014

Publication title -

international journal of distributed sensor networks

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.324

H-Index - 53

eISSN - 1550-1477

pISSN - 1550-1329

DOI - 10.1155/2014/950683

Subject(s) - computer science , particle swarm optimization , decentralised system , consensus algorithm , distributed computing , control (management) , algorithm , artificial intelligence

This paper explores the possibility of enhancing consensus achievement of decentralized sensors by establishing cooperative behavior between sensor agents. To these ends, a novel particle swarm optimization framework to achieve robust consensus of decentralized sensors is devised to distribute sensing information via local fusing with neighbors rather than through centralized control; the new framework showed a 16.5 percent improvement in consensus achievement as compared to the classic majority rule method. Noteworthy enhancements in consensus achievement are also pertinent to the comparable situation of decentralized sensor systems.

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