Consensus Achievement of Decentralized Sensors Using Adapted Particle Swarm Optimization Algorithm - Hyunseok Kim; Seongju Chang; Jinsul Kim (International Journal of Distributed Sensor Networks)
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.