{"title":"水下无线传感器网络的多Sink放置策略","authors":"Faiza Al-Salti, K. Day, N. Alzeidi, A. Touzene","doi":"10.1109/ISNCC.2018.8531063","DOIUrl":null,"url":null,"abstract":"We propose a mathematical model for multiple sink placement in Underwater Wireless Sensor Networks (UWSNs). The model is constructed for a 3D mesh topology. Our objective is to minimize the overall number of hops of every source-closest sink pair of cells. We analyze the constructed model, and prove its hardness by reducing the k-median problem, a well-known NP-hard problem to our problem. We then use the Partitioning Around Medoid (PAM) approximation algorithm to find a near optimal solution to our sink placement problem. We test the solutions obtained by this approximation algorithm by comparing them with the optimal solutions obtained using a brute force method. We also compare the approximate solutions with solutions obtained using a random-based heuristic. Results show that the proposed PAM-based approximation achieves remarkably near-optimal solutions.","PeriodicalId":313846,"journal":{"name":"2018 International Symposium on Networks, Computers and Communications (ISNCC)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Multiple Sink Placement Strategy for Underwater Wireless Sensor Networks\",\"authors\":\"Faiza Al-Salti, K. Day, N. Alzeidi, A. Touzene\",\"doi\":\"10.1109/ISNCC.2018.8531063\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose a mathematical model for multiple sink placement in Underwater Wireless Sensor Networks (UWSNs). The model is constructed for a 3D mesh topology. Our objective is to minimize the overall number of hops of every source-closest sink pair of cells. We analyze the constructed model, and prove its hardness by reducing the k-median problem, a well-known NP-hard problem to our problem. We then use the Partitioning Around Medoid (PAM) approximation algorithm to find a near optimal solution to our sink placement problem. We test the solutions obtained by this approximation algorithm by comparing them with the optimal solutions obtained using a brute force method. We also compare the approximate solutions with solutions obtained using a random-based heuristic. Results show that the proposed PAM-based approximation achieves remarkably near-optimal solutions.\",\"PeriodicalId\":313846,\"journal\":{\"name\":\"2018 International Symposium on Networks, Computers and Communications (ISNCC)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Symposium on Networks, Computers and Communications (ISNCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISNCC.2018.8531063\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Symposium on Networks, Computers and Communications (ISNCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISNCC.2018.8531063","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multiple Sink Placement Strategy for Underwater Wireless Sensor Networks
We propose a mathematical model for multiple sink placement in Underwater Wireless Sensor Networks (UWSNs). The model is constructed for a 3D mesh topology. Our objective is to minimize the overall number of hops of every source-closest sink pair of cells. We analyze the constructed model, and prove its hardness by reducing the k-median problem, a well-known NP-hard problem to our problem. We then use the Partitioning Around Medoid (PAM) approximation algorithm to find a near optimal solution to our sink placement problem. We test the solutions obtained by this approximation algorithm by comparing them with the optimal solutions obtained using a brute force method. We also compare the approximate solutions with solutions obtained using a random-based heuristic. Results show that the proposed PAM-based approximation achieves remarkably near-optimal solutions.