{"title":"Coverage of Targets in Mobile Sensor Networks With Limited Mobility","authors":"Saumya Jaipuria, R. Das","doi":"10.1109/OCIT56763.2022.00089","DOIUrl":null,"url":null,"abstract":"In Mobile Sensor Networks (MSN), covering targets with minimum movement is an important issue. We consider two related problems but with a limited mobility model where no sensor can move beyond a certain distance. In the first problem, we minimize the sum of the movements of all sensors. And in the other, we minimize their maximum. We solve the first problem by relaxing the equivalent Integer Linear Program (ILP) where the maximum allowable distance is a parameter. Experimental results show that our algorithm gives the solution very close to the optimal. For the second problem, we apply binary search and repeatedly execute the relaxed LP until we find the smallest value of the maximum distance that gives a feasible solution. We could find movements of sensors that satisfy the above limit in all our experiments with different random placements of sensors and targets.","PeriodicalId":425541,"journal":{"name":"2022 OITS International Conference on Information Technology (OCIT)","volume":"14 2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 OITS International Conference on Information Technology (OCIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/OCIT56763.2022.00089","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
In Mobile Sensor Networks (MSN), covering targets with minimum movement is an important issue. We consider two related problems but with a limited mobility model where no sensor can move beyond a certain distance. In the first problem, we minimize the sum of the movements of all sensors. And in the other, we minimize their maximum. We solve the first problem by relaxing the equivalent Integer Linear Program (ILP) where the maximum allowable distance is a parameter. Experimental results show that our algorithm gives the solution very close to the optimal. For the second problem, we apply binary search and repeatedly execute the relaxed LP until we find the smallest value of the maximum distance that gives a feasible solution. We could find movements of sensors that satisfy the above limit in all our experiments with different random placements of sensors and targets.