{"title":"基于遗传算法的无线音频传感器网络覆盖与定位优化方法","authors":"Sami Mnasri, Adel Thaljaoui, N. Nasri, T. Val","doi":"10.1109/ISNCC.2015.7238591","DOIUrl":null,"url":null,"abstract":"Coverage is one of the most important performance metrics for sensor networks that reflects how well a sensor field is monitored. In this paper, we are interested in studying the positioning and placement of sensor nodes in a WSN in order to maximize the coverage area and to optimize the audio localization in wireless sensor networks. First, we introduce the problem of deployment. Then we propose a mathematical formulation and a genetic based approach to solve this problem. Finally, we present the results of experimentations. This paper presents a genetic algorithm which aims at searching for an optimal or near optimal solution to the coverage holes problem. Compared with random deployment as well as existing methods, our genetic algorithm shows significant performance improvement in terms of quality.","PeriodicalId":430315,"journal":{"name":"2015 International Symposium on Networks, Computers and Communications (ISNCC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":"{\"title\":\"A genetic algorithm-based approach to optimize the coverage and the localization in the wireless audio-sensors networks\",\"authors\":\"Sami Mnasri, Adel Thaljaoui, N. Nasri, T. Val\",\"doi\":\"10.1109/ISNCC.2015.7238591\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Coverage is one of the most important performance metrics for sensor networks that reflects how well a sensor field is monitored. In this paper, we are interested in studying the positioning and placement of sensor nodes in a WSN in order to maximize the coverage area and to optimize the audio localization in wireless sensor networks. First, we introduce the problem of deployment. Then we propose a mathematical formulation and a genetic based approach to solve this problem. Finally, we present the results of experimentations. This paper presents a genetic algorithm which aims at searching for an optimal or near optimal solution to the coverage holes problem. Compared with random deployment as well as existing methods, our genetic algorithm shows significant performance improvement in terms of quality.\",\"PeriodicalId\":430315,\"journal\":{\"name\":\"2015 International Symposium on Networks, Computers and Communications (ISNCC)\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-05-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"21\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Symposium on Networks, Computers and Communications (ISNCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISNCC.2015.7238591\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Symposium on Networks, Computers and Communications (ISNCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISNCC.2015.7238591","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A genetic algorithm-based approach to optimize the coverage and the localization in the wireless audio-sensors networks
Coverage is one of the most important performance metrics for sensor networks that reflects how well a sensor field is monitored. In this paper, we are interested in studying the positioning and placement of sensor nodes in a WSN in order to maximize the coverage area and to optimize the audio localization in wireless sensor networks. First, we introduce the problem of deployment. Then we propose a mathematical formulation and a genetic based approach to solve this problem. Finally, we present the results of experimentations. This paper presents a genetic algorithm which aims at searching for an optimal or near optimal solution to the coverage holes problem. Compared with random deployment as well as existing methods, our genetic algorithm shows significant performance improvement in terms of quality.