{"title":"基于改进遗传算法的无线传感器网络移动代理路由算法","authors":"Xiangli Wang, La-yuan Li","doi":"10.1109/URKE.2012.6319547","DOIUrl":null,"url":null,"abstract":"For the energy consumption problem of wireless sensor networks, a mobile agent routing based on improved genetic algorithm (MARIGA) is proposed in this paper. This algorithm introduces a new crossover strategy and mutation operator to effectively control the premature stagnation in the convergence process. The simulation results indicate that the MARIGA algorithm can effectively improve the routing quality of mobile agent and the energy consumption of network.","PeriodicalId":277189,"journal":{"name":"2012 2nd International Conference on Uncertainty Reasoning and Knowledge Engineering","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A mobile agent routing algorithm based on improved genetic algorithm for wireless sensor networks\",\"authors\":\"Xiangli Wang, La-yuan Li\",\"doi\":\"10.1109/URKE.2012.6319547\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For the energy consumption problem of wireless sensor networks, a mobile agent routing based on improved genetic algorithm (MARIGA) is proposed in this paper. This algorithm introduces a new crossover strategy and mutation operator to effectively control the premature stagnation in the convergence process. The simulation results indicate that the MARIGA algorithm can effectively improve the routing quality of mobile agent and the energy consumption of network.\",\"PeriodicalId\":277189,\"journal\":{\"name\":\"2012 2nd International Conference on Uncertainty Reasoning and Knowledge Engineering\",\"volume\":\"42 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-10-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 2nd International Conference on Uncertainty Reasoning and Knowledge Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/URKE.2012.6319547\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 2nd International Conference on Uncertainty Reasoning and Knowledge Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/URKE.2012.6319547","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A mobile agent routing algorithm based on improved genetic algorithm for wireless sensor networks
For the energy consumption problem of wireless sensor networks, a mobile agent routing based on improved genetic algorithm (MARIGA) is proposed in this paper. This algorithm introduces a new crossover strategy and mutation operator to effectively control the premature stagnation in the convergence process. The simulation results indicate that the MARIGA algorithm can effectively improve the routing quality of mobile agent and the energy consumption of network.