{"title":"Genetic Algorithm Approach improved by 2D Lifting Scheme for Sensor Node Placement in Optimal Position","authors":"T. Ganesan, P. Rajarajeswari","doi":"10.1109/ISS1.2019.8908030","DOIUrl":null,"url":null,"abstract":"In this smart connected world, Sensors are scattered in the environment of interest in order to perform a surveillance monitoring activity for the target operational research. In order to cover the target, sensor node placement plays a crucial role to cover maximum target and minimum node connectivity with limited nodes. Sensor data gathering can be achieved by using important principle node connectivity. Signals in sensor network carry a large amount of data and retaining important information is often more difficult. To overcome this problem we propose a genetic algorithm based node placement the result is improved by wavelets to achieve a maximum coverage and connectivity. The experimental result is carried out to improve the quality of covered data with limited sensor in optimal positions.","PeriodicalId":111366,"journal":{"name":"2019 International Conference on Intelligent Sustainable Systems (ICISS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Intelligent Sustainable Systems (ICISS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISS1.2019.8908030","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
In this smart connected world, Sensors are scattered in the environment of interest in order to perform a surveillance monitoring activity for the target operational research. In order to cover the target, sensor node placement plays a crucial role to cover maximum target and minimum node connectivity with limited nodes. Sensor data gathering can be achieved by using important principle node connectivity. Signals in sensor network carry a large amount of data and retaining important information is often more difficult. To overcome this problem we propose a genetic algorithm based node placement the result is improved by wavelets to achieve a maximum coverage and connectivity. The experimental result is carried out to improve the quality of covered data with limited sensor in optimal positions.