{"title":"UFO: A United Framework for Target Localization in Wireless Sensor Networks","authors":"Jiuyang Tang, Guoming Tang, Daquan Tang, W. Xiao","doi":"10.1109/CyberC.2013.69","DOIUrl":null,"url":null,"abstract":"Recently, various range-free based target localization applications and systems are developed in Wireless Sensor Networks. Nevertheless, few of them can be reused or grafted by others, which has led to serious waste. In this paper, a Unified Framework for target lOcalization (UFO) is proposed and an adaptive grids dividing algorithm is addressed within the framework. Based on the common ground of current typical range-free localization methods, UFO is constructed by four major modules to achieve candidate area acquisition and target location determination: sensor deployment and signal process module, candidate area acquisition module, target localization module and parameter setting module. Not only can UFO construct a localization framework quickly, the computing complexity of loaded localization methods is expected to be decreased by bringing in adaptive grids dividing. In our simulations, the UFO assembled with schemes from node sequences based localization method is tested, and the results from our framework are compared with the original method's. Performance evaluation shows us both UFO and original schemes perform well at localizing accuracy, while the former has a big advantage at real-time capacity.","PeriodicalId":133756,"journal":{"name":"2013 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery","volume":"58 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CyberC.2013.69","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Recently, various range-free based target localization applications and systems are developed in Wireless Sensor Networks. Nevertheless, few of them can be reused or grafted by others, which has led to serious waste. In this paper, a Unified Framework for target lOcalization (UFO) is proposed and an adaptive grids dividing algorithm is addressed within the framework. Based on the common ground of current typical range-free localization methods, UFO is constructed by four major modules to achieve candidate area acquisition and target location determination: sensor deployment and signal process module, candidate area acquisition module, target localization module and parameter setting module. Not only can UFO construct a localization framework quickly, the computing complexity of loaded localization methods is expected to be decreased by bringing in adaptive grids dividing. In our simulations, the UFO assembled with schemes from node sequences based localization method is tested, and the results from our framework are compared with the original method's. Performance evaluation shows us both UFO and original schemes perform well at localizing accuracy, while the former has a big advantage at real-time capacity.