Shinji Sakamoto, Tetsuya Oda, Elis Kulla, Makoto Ikeda, L. Barolli, F. Xhafa
{"title":"Performance Analysis of WMNs Using Simulated Annealing Algorithm for Different Temperature Values","authors":"Shinji Sakamoto, Tetsuya Oda, Elis Kulla, Makoto Ikeda, L. Barolli, F. Xhafa","doi":"10.1109/CISIS.2013.34","DOIUrl":null,"url":null,"abstract":"On of the key advantages of Wireless Mesh Networks (WMNs) is their importance for providing cost-efficient broadband connectivity. There are issues for achieving the network connectivity and user coverage, which are related with the node placement problem. In this work, we consider the router node placement problem in WMNs and find the optimal distribution of router nodes in order to provide the best network connectivity among themselves and provide the best client coverage in a set of uniformly distributed clients. We use Simulated Annealing (SA) algorithm in our WMN-SA simulation system to calculate the size of Giant Component (GC) and number of covered users with different temperature values of SA.","PeriodicalId":155467,"journal":{"name":"2013 Seventh International Conference on Complex, Intelligent, and Software Intensive Systems","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Seventh International Conference on Complex, Intelligent, and Software Intensive Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISIS.2013.34","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
On of the key advantages of Wireless Mesh Networks (WMNs) is their importance for providing cost-efficient broadband connectivity. There are issues for achieving the network connectivity and user coverage, which are related with the node placement problem. In this work, we consider the router node placement problem in WMNs and find the optimal distribution of router nodes in order to provide the best network connectivity among themselves and provide the best client coverage in a set of uniformly distributed clients. We use Simulated Annealing (SA) algorithm in our WMN-SA simulation system to calculate the size of Giant Component (GC) and number of covered users with different temperature values of SA.