Genetic Algorithm Based Node Placement Methodology For Wireless Sensor Networks
作者： Amol P. Bhondekar , Madan Lal Singla , Renu Vig , Pawan Kapur , C Ghanshyam
DOI:
关键词: Mobile wireless sensor network 、 Electronic engineering 、 Node (networking) 、 Genetic algorithm 、 Brooks–Iyengar algorithm 、 Wireless sensor network 、 Energy consumption 、 Distributed computing 、 Fitness function 、 Key distribution in wireless sensor networks 、 Engineering
摘要: Abstract — A Genetic Algorithm based multi-objective methodology was implemented for a self-organizing wireless sensor network. Design parameters such as network density, connectivity and energy consumption are taken into account developing the fitness function. The genetic algorithm optimizes operational modes of nodes along with clustering schemes transmission signal strengths. has been in MATLAB using its toolbox custom codes. optimal designs so achieved by conform to all design parameters. Index Terms – Algorithms, Network Configuration , Sensor Placement, Wireless Networks. I. I NTRODUCTION dvancements technologies Sensing, Electronics Computing have attracted tremendous research interest field Networks (WSNs), apart from their enormous potential both commercial military applications. WSN generally consists large number low-cost, low-power, multifunctional, constrained limited computational communication capabilities [1]. In WSNs sensors may be deployed either randomly or deterministically depending upon application [2]. Deployment battlefield hazardous areas is random, whereas deterministic deployment preferred amicable environments. general placement requires fewer than random perform same task. lifetime one important optimize resources due operation on battery. Replacing recharging battery infeasible. Though overall function
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