{"title":"具有障碍和偏好的无线传感器网络中传感器最优放置的遗传算法","authors":"Yong Xu, Xingting Yao","doi":"10.1109/CCNC.2006.1593001","DOIUrl":null,"url":null,"abstract":"The wireless sensor network (WSN) has recently become an intensive research focus due to its potential applications in many areas. In this paper, we propose a new and efficient genetic algorithm (GA) to the optimal placement of sensors in a grid area with obstacles and preferences to minimize the number of sensors. A new sensor detection model is also introduced in this paper. Experiments show that our algorithm is able to achieve better results than previous heuristic algorithms.","PeriodicalId":194551,"journal":{"name":"CCNC 2006. 2006 3rd IEEE Consumer Communications and Networking Conference, 2006.","volume":"204 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"55","resultStr":"{\"title\":\"A GA approach to the optimal placement of sensors in wireless sensor networks with obstacles and preferences\",\"authors\":\"Yong Xu, Xingting Yao\",\"doi\":\"10.1109/CCNC.2006.1593001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The wireless sensor network (WSN) has recently become an intensive research focus due to its potential applications in many areas. In this paper, we propose a new and efficient genetic algorithm (GA) to the optimal placement of sensors in a grid area with obstacles and preferences to minimize the number of sensors. A new sensor detection model is also introduced in this paper. Experiments show that our algorithm is able to achieve better results than previous heuristic algorithms.\",\"PeriodicalId\":194551,\"journal\":{\"name\":\"CCNC 2006. 2006 3rd IEEE Consumer Communications and Networking Conference, 2006.\",\"volume\":\"204 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-02-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"55\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"CCNC 2006. 2006 3rd IEEE Consumer Communications and Networking Conference, 2006.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCNC.2006.1593001\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"CCNC 2006. 2006 3rd IEEE Consumer Communications and Networking Conference, 2006.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCNC.2006.1593001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A GA approach to the optimal placement of sensors in wireless sensor networks with obstacles and preferences
The wireless sensor network (WSN) has recently become an intensive research focus due to its potential applications in many areas. In this paper, we propose a new and efficient genetic algorithm (GA) to the optimal placement of sensors in a grid area with obstacles and preferences to minimize the number of sensors. A new sensor detection model is also introduced in this paper. Experiments show that our algorithm is able to achieve better results than previous heuristic algorithms.