{"title":"基于模拟退火的移动网状客户端无线网状网络中网状路由器的优化配置","authors":"Lamri Sayad","doi":"10.1109/ISCBI.2017.8053542","DOIUrl":null,"url":null,"abstract":"A wireless mesh network (WMN) is a set of three kinds of nodes: clients, routers and gateways. One of the most challenging issues when dealing with a WMN is how to deploy mesh routers when the positions of mesh clients are known. In this paper, we consider a dynamic router node placement problem where, in addition, mesh clients are mobile. To solve this issue, we apply the simulated annealing metaheuristic (SA). At every iteration, clients are moving from their positions to new positions engendering new network topologies. To serve these clients, routers should update their positions by moving according to the new topology. Therefore, SA algorithm is applied to determine the positions of mesh routers every time it is needed. Simulation results demonstrate that the proposed approach is promising in determining optimal positions of mesh routers.","PeriodicalId":128441,"journal":{"name":"2017 5th International Symposium on Computational and Business Intelligence (ISCBI)","volume":"262 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Optimal placement of mesh routers in a wireless mesh network with mobile mesh clients using simulated annealing\",\"authors\":\"Lamri Sayad\",\"doi\":\"10.1109/ISCBI.2017.8053542\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A wireless mesh network (WMN) is a set of three kinds of nodes: clients, routers and gateways. One of the most challenging issues when dealing with a WMN is how to deploy mesh routers when the positions of mesh clients are known. In this paper, we consider a dynamic router node placement problem where, in addition, mesh clients are mobile. To solve this issue, we apply the simulated annealing metaheuristic (SA). At every iteration, clients are moving from their positions to new positions engendering new network topologies. To serve these clients, routers should update their positions by moving according to the new topology. Therefore, SA algorithm is applied to determine the positions of mesh routers every time it is needed. Simulation results demonstrate that the proposed approach is promising in determining optimal positions of mesh routers.\",\"PeriodicalId\":128441,\"journal\":{\"name\":\"2017 5th International Symposium on Computational and Business Intelligence (ISCBI)\",\"volume\":\"262 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 5th International Symposium on Computational and Business Intelligence (ISCBI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISCBI.2017.8053542\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 5th International Symposium on Computational and Business Intelligence (ISCBI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCBI.2017.8053542","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimal placement of mesh routers in a wireless mesh network with mobile mesh clients using simulated annealing
A wireless mesh network (WMN) is a set of three kinds of nodes: clients, routers and gateways. One of the most challenging issues when dealing with a WMN is how to deploy mesh routers when the positions of mesh clients are known. In this paper, we consider a dynamic router node placement problem where, in addition, mesh clients are mobile. To solve this issue, we apply the simulated annealing metaheuristic (SA). At every iteration, clients are moving from their positions to new positions engendering new network topologies. To serve these clients, routers should update their positions by moving according to the new topology. Therefore, SA algorithm is applied to determine the positions of mesh routers every time it is needed. Simulation results demonstrate that the proposed approach is promising in determining optimal positions of mesh routers.