NDLI: Self Organized Mobility in Nanosensor Network Based on Particle Swarm Optimization and Coverage Criteria

Content Provider	IEEE Xplore Digital Library
Author	Hla, K.H.S. YoungSik Choi Jong Sou Park
Copyright Year	2008
Description	Author affiliation: Dept. of Comput. Eng., Korea Aerosp. Univ., Goyang (Hla, K.H.S.; YoungSik Choi; Jong Sou Park)
Abstract	This study presents a self organized control of nano sensor's mobility based on the particle swarm optimization (PSO) algorithm. PSO models the set of potential problem solutions as a swarm of particles moving about in a virtual search space by adapting self organizing concept. The study is based on the premise that the deployment of nanosensors and used for investigating within human body. The spatially distributed nanosensors collect information about the target environment by moving throughout the body. Movement of sensors will be addressed how sensors are perimeter covered to the target environment. There may be two kinds of issues for coverage such that insufficient coverage and covered by too many sensors in certain areas without necessary. If there is not enough coverage, the required information may not get properly. If there are more sensors than necessary, there may be some redundant nodes and it may consume more energy. Therefore, the sensors should move to the next target, which has proper coverage criteria. The simulation results have approved that the proposed scheme effectively constructs a self organized mobility within the optimized coverage area.
Starting Page	636
Ending Page	641
File Size	289639
Page Count	6
File Format	PDF
ISBN	9780769533223
DOI	10.1109/NCM.2008.207
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-09-02
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Temperature measurement coverage Fluids Computational modeling nanosensor network nanorobots Sensors particle swarm optimization Particle swarm optimization Chemicals Monitoring
Content Type	Text
Resource Type	Article

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