{"title":"Assignment of Cells to Switches in a Cellular Mobile Environment Using Swarm Intelligence","authors":"S. Udgata, U. Anuradha, G. Kumar, Gauri K. Udgata","doi":"10.1109/ICIT.2008.31","DOIUrl":null,"url":null,"abstract":"The problem of assigning cells to switches in a mobile cellular network is a NP-Hard problem. It is therefore necessary to use a heuristic method to solve it in a reasonable amount of time with acceptable accuracy particularly for large sized problems. The assignment of cells to switches problem is characterized by minimization of the cabling cost, hand-off cost and switching costs in the whole network. We propose a swarm intelligence based technique to solve this problem. Ant colony optimization (ACO) and Particle swarm optimization (PSO) are typical swarm intelligence techniques. ACO technique was used for cell assignment problem in the recent past and shown to be better in comparison to the other schemes. In this paper, we propose a modified binary Particle Swarm Optimization (MBPSO) technique for this cell assignment problem. Our experimental results reveal better results in terms of accuracy and execution time compared to ACO for a large combination of parameters.","PeriodicalId":184201,"journal":{"name":"2008 International Conference on Information Technology","volume":"2018 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 International Conference on Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIT.2008.31","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
The problem of assigning cells to switches in a mobile cellular network is a NP-Hard problem. It is therefore necessary to use a heuristic method to solve it in a reasonable amount of time with acceptable accuracy particularly for large sized problems. The assignment of cells to switches problem is characterized by minimization of the cabling cost, hand-off cost and switching costs in the whole network. We propose a swarm intelligence based technique to solve this problem. Ant colony optimization (ACO) and Particle swarm optimization (PSO) are typical swarm intelligence techniques. ACO technique was used for cell assignment problem in the recent past and shown to be better in comparison to the other schemes. In this paper, we propose a modified binary Particle Swarm Optimization (MBPSO) technique for this cell assignment problem. Our experimental results reveal better results in terms of accuracy and execution time compared to ACO for a large combination of parameters.