{"title":"基于人工神经网络的传感器网络节点调度算法","authors":"Yang Wanggong, Chen Mingzhi","doi":"10.1504/ijaacs.2021.117804","DOIUrl":null,"url":null,"abstract":"In order to solve the problem that the traditional scheduling algorithm of sensor network node is constrained by the energy of the node itself, this paper proposes a new scheduling algorithm of sensor network node based on artificial neural network (ANN). Aiming at the sensor network of ANN, a multi-objective task scheduling model is established. The optimal solution of task scheduling is obtained by particle swarm optimisation algorithm. The energy balance degree is set as the final decision-making index, and the energy consumption of the optimal solution centralised node is chosen as the final task scheduling strategy to complete the scheduling of sensor network nodes. The experimental results show that the proposed algorithm has higher coverage and lower energy consumption in the scheduling process, which has certain advantages.","PeriodicalId":38798,"journal":{"name":"International Journal of Autonomous and Adaptive Communications Systems","volume":null,"pages":null},"PeriodicalIF":0.4000,"publicationDate":"2021-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Scheduling algorithm of sensor network node based on artificial neural network\",\"authors\":\"Yang Wanggong, Chen Mingzhi\",\"doi\":\"10.1504/ijaacs.2021.117804\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to solve the problem that the traditional scheduling algorithm of sensor network node is constrained by the energy of the node itself, this paper proposes a new scheduling algorithm of sensor network node based on artificial neural network (ANN). Aiming at the sensor network of ANN, a multi-objective task scheduling model is established. The optimal solution of task scheduling is obtained by particle swarm optimisation algorithm. The energy balance degree is set as the final decision-making index, and the energy consumption of the optimal solution centralised node is chosen as the final task scheduling strategy to complete the scheduling of sensor network nodes. The experimental results show that the proposed algorithm has higher coverage and lower energy consumption in the scheduling process, which has certain advantages.\",\"PeriodicalId\":38798,\"journal\":{\"name\":\"International Journal of Autonomous and Adaptive Communications Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.4000,\"publicationDate\":\"2021-09-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Autonomous and Adaptive Communications Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/ijaacs.2021.117804\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Autonomous and Adaptive Communications Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/ijaacs.2021.117804","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Scheduling algorithm of sensor network node based on artificial neural network
In order to solve the problem that the traditional scheduling algorithm of sensor network node is constrained by the energy of the node itself, this paper proposes a new scheduling algorithm of sensor network node based on artificial neural network (ANN). Aiming at the sensor network of ANN, a multi-objective task scheduling model is established. The optimal solution of task scheduling is obtained by particle swarm optimisation algorithm. The energy balance degree is set as the final decision-making index, and the energy consumption of the optimal solution centralised node is chosen as the final task scheduling strategy to complete the scheduling of sensor network nodes. The experimental results show that the proposed algorithm has higher coverage and lower energy consumption in the scheduling process, which has certain advantages.