P. Papazoglou, Dimitrios Alexios Karras, R. C. Papademetriou
{"title":"On the implementation of ant colony optimization scheme for improved channel allocation in wireless communications","authors":"P. Papazoglou, Dimitrios Alexios Karras, R. C. Papademetriou","doi":"10.1109/IS.2008.4670437","DOIUrl":null,"url":null,"abstract":"Channel allocation in wireless communication systems is one of the fundamental issues. The corresponding allocation schemes can not be static due to the dynamically changing traffic conditions and network performance. Thus, more sophisticated strategies adapted to current network conditions must be investigated and applied. Recently, various approaches have been proposed for channel allocation based on intelligent techniques such as multi-agent technology and genetic algorithms. These approaches constitute heuristic solutions to resource management problem. On the other hand, the ant colony optimization approach has been proposed for solving optimization problems but this approach has not been proposed so far for solving the channel allocation problem in wireless communication systems. In this paper, a comprehensive heuristic approach for solving the channel allocation problem based on intelligent techniques such as multi-agents and ant colony optimization is proposed. Moreover, important implementation issues such as thread execution sequence are also presented. Finally, the simulation results show the performance improvement of the proposed ant colony optimization algorithm as well as the multi-agent modeling approach.","PeriodicalId":305750,"journal":{"name":"2008 4th International IEEE Conference Intelligent Systems","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 4th International IEEE Conference Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IS.2008.4670437","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
Channel allocation in wireless communication systems is one of the fundamental issues. The corresponding allocation schemes can not be static due to the dynamically changing traffic conditions and network performance. Thus, more sophisticated strategies adapted to current network conditions must be investigated and applied. Recently, various approaches have been proposed for channel allocation based on intelligent techniques such as multi-agent technology and genetic algorithms. These approaches constitute heuristic solutions to resource management problem. On the other hand, the ant colony optimization approach has been proposed for solving optimization problems but this approach has not been proposed so far for solving the channel allocation problem in wireless communication systems. In this paper, a comprehensive heuristic approach for solving the channel allocation problem based on intelligent techniques such as multi-agents and ant colony optimization is proposed. Moreover, important implementation issues such as thread execution sequence are also presented. Finally, the simulation results show the performance improvement of the proposed ant colony optimization algorithm as well as the multi-agent modeling approach.