Tapan Kumar Mohanta, Ankur Rai, Dushmanta Kumar Das
{"title":"Performance Analysis of a Particle Swarm Optimization based Localization Algorithm in Wireless Sensor Network","authors":"Tapan Kumar Mohanta, Ankur Rai, Dushmanta Kumar Das","doi":"10.1109/ASPCON49795.2020.9276719","DOIUrl":null,"url":null,"abstract":"Wireless sensor network (WSN) can be applied for sensing, collecting, processing and transmission of information. Most of the applications of WSNs are a few issues of localization problem. To minimize the drawback of basic Distance Vector-Hop algorithm, a Particle Swarm Optimization (PSO) based Distance Vector-Hop localization algorithm is presented in this paper. The validation of results are complied by simulation. Error variance, error accuracy with localization error have analyzed with the performance of implemented in Distance Vector algorithm. In this paper, error localization and variance are decreased and accuracy is increased.","PeriodicalId":193814,"journal":{"name":"2020 IEEE Applied Signal Processing Conference (ASPCON)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Applied Signal Processing Conference (ASPCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASPCON49795.2020.9276719","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Wireless sensor network (WSN) can be applied for sensing, collecting, processing and transmission of information. Most of the applications of WSNs are a few issues of localization problem. To minimize the drawback of basic Distance Vector-Hop algorithm, a Particle Swarm Optimization (PSO) based Distance Vector-Hop localization algorithm is presented in this paper. The validation of results are complied by simulation. Error variance, error accuracy with localization error have analyzed with the performance of implemented in Distance Vector algorithm. In this paper, error localization and variance are decreased and accuracy is increased.