期刊文献+
共找到1篇文章
< 1 >
每页显示 20 50 100
On Layout Optimization of Wireless Sensor Network Using Meta-Heuristic Approach
1
作者 Abeeda Akram Kashif Zafar +4 位作者 Adnan Noor Mian Abdul Rauf Baig Riyad Almakki lulwah alsuwaidan Shakir Khan 《Computer Systems Science & Engineering》 SCIE EI 2023年第9期3685-3701,共17页
One of the important research issues in wireless sensor networks(WSNs)is the optimal layout designing for the deployment of sensor nodes.It directly affects the quality of monitoring,cost,and detection capability of W... One of the important research issues in wireless sensor networks(WSNs)is the optimal layout designing for the deployment of sensor nodes.It directly affects the quality of monitoring,cost,and detection capability of WSNs.Layout optimization is an NP-hard combinatorial problem,which requires optimization of multiple competing objectives like cost,coverage,connectivity,lifetime,load balancing,and energy consumption of sensor nodes.In the last decade,several meta-heuristic optimization techniques have been proposed to solve this problem,such as genetic algorithms(GA)and particle swarm optimization(PSO).However,these approaches either provided computationally expensive solutions or covered a limited number of objectives,which are combinations of area coverage,the number of sensor nodes,energy consumption,and lifetime.In this study,a meta-heuristic multi-objective firefly algorithm(MOFA)is presented to solve the layout optimization problem.Here,the main goal is to cover a number of objectives related to optimal layouts of homogeneous WSNs,which includes coverage,connectivity,lifetime,energy consumption and the number of sensor nodes.Simulation results showed that MOFA created optimal Pareto front of non-dominated solutions with better hyper-volumes and spread of solutions,in comparison to multi-objective genetic algorithms(IBEA,NSGA-II)and particle swarm optimizers(OMOPSO,SMOPSO).Therefore,MOFA can be used in real-time deployment applications of large-scale WSNs to enhance their detection capability and quality of monitoring. 展开更多
关键词 Wireless sensor networks OPTIMIZATION COVERAGE genetic algorithms particle swarm optimization
下载PDF
上一页 1 下一页 到第
使用帮助 返回顶部