{"title":"A broadcast path choice algorithm based on simulated annealing for Wireless Sensor Network","authors":"Haitao Zhang, Ge Bai, Cuiping Liu","doi":"10.1109/ICAL.2012.6308217","DOIUrl":null,"url":null,"abstract":"According to solid annealing physics phenomenon and based on simulated annealing applying in combinational optimization problem, this paper puts forward a method that could use simulated annealing algorithm (SABA) to solve broadcast path in wireless sensor network. The broadcast transmission link formed by this algorithm not only can absorb local optimum solution, but also can jump out of the wrong local optimum. Furthermore, at first it absorbs the inferior solution, with temperature decreased, it will get rid of the inferior solution step by step to get global optimal solution. The simulation shows that comparing to 2-opt algorithm, this algorithm can decrease the length of transmission, and save energy consumption.","PeriodicalId":373152,"journal":{"name":"2012 IEEE International Conference on Automation and Logistics","volume":"81 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE International Conference on Automation and Logistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAL.2012.6308217","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
According to solid annealing physics phenomenon and based on simulated annealing applying in combinational optimization problem, this paper puts forward a method that could use simulated annealing algorithm (SABA) to solve broadcast path in wireless sensor network. The broadcast transmission link formed by this algorithm not only can absorb local optimum solution, but also can jump out of the wrong local optimum. Furthermore, at first it absorbs the inferior solution, with temperature decreased, it will get rid of the inferior solution step by step to get global optimal solution. The simulation shows that comparing to 2-opt algorithm, this algorithm can decrease the length of transmission, and save energy consumption.