基于烟花算法的WSN按需充电与数据收集策略  

WSN on-demand charging and data collection strategy based on firework algorithm

作　　者：牟青 冯琳[1] 魏振春[1,2] MOU Qing;FENG Lin;WEI Zhenchun(School of Computer Science and Information Engineering,Hefei University of Technology,Hefei 230601,China;Engineering Research Center of Safety Critical Industrial Measurement and Control Technology of Ministry of Education,Hefei 230601,China)

机构地区：[1]合肥工业大学计算机与信息学院,安徽合肥230601 [2]安全关键工业测控技术教育部工程研究中心,安徽合肥230601

出　　处：《合肥工业大学学报（自然科学版）》2021年第11期1476-1482,共7页Journal of Hefei University of Technology：Natural Science

基　　金：中央高校基本科研业务费专项资金资助项目(PA2021GDGP0061);合肥工业大学智能制造技术研究院科技成果培育专项资助项目(IMIPY2021003)。

摘　　要：传感器节点的能量与存储空间受限会影响无线传感器网络(wireless sensor network,WSN)的性能和生命周期。文章采用移动小车(mobile car,MC)对WSN进行能量补充和数据收集,提出基于能量需求和数据收集(energy requirement and data collection)的节点选择(select)S-ERDC算法来选择部分需要充电和数据收集的节点,并通过提出的差分进化烟花(differential evolution fireworks,DEFW)算法对MC访问需求节点的移动路径进行调度,从而在保证网络永续运行的同时最小化网络能耗。仿真实验表明,使用了S-ERDC算法和DEFW算法的WSN在运行40个充电轮后,WSN中的能耗比原始烟花降低4.73%,比遗传算法降低22.49%。The limited energy and storage of sensor nodes will affect the performance and life of the wireless sensor network(WSN).This paper uses a mobile car(MC)to supplement energy and collect data for WSN.The S-ERDC algorithm based on energy requirement and data collection is proposed to select some nodes that need charging and data collection,and then the order of MC access to demand nodes is scheduled through the proposed differential evolution fireworks(DEFW)algorithm.The goal is to minimize the network energy consumption while ensuring the sustainable operation of the network.Simulation experiments show that using S-ERDC algorithm and DEFW algorithm,the energy consumption in WSN is reduced by 4.73%compared with the original firework and 22.49%lower than the genetic algorithm after 40 rounds of charging.

关 键 词：无线传感器网络(WSN) 移动充电 数据收集 烟花算法 差分进化算法 

分 类 号：TP393.1[自动化与计算机技术—计算机应用技术]