Consensus Achievement of Decentralized Sensors Using Adapted Particle Swarm Optimization Algorithm

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 sensi...

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Bibliographic Details
Main Authors: Hyunseok Kim, Seongju Chang, Jinsul Kim
Format: Article
Language:English
Published: Hindawi - SAGE Publishing 2014-04-01
Series:International Journal of Distributed Sensor Networks
Online Access:https://doi.org/10.1155/2014/950683
Description
Summary: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.
ISSN:1550-1477