{"title":"一种解决多约束QoS多路由问题的新方法","authors":"Ling Qin, Yixin Chen, Jianli Luo, Jing Guo, Ling Chen","doi":"10.1109/IMSCCS.2006.18","DOIUrl":null,"url":null,"abstract":"A new way of solving the bandwidth, delay, delay jitter and packet loss constrained least-cost quality of service (QoS) multi-routing problem is presented. It harmonizes the intrinsic attributes of each constraint of QoS and in different stage, the algorithm updates pheromone according to different constraints, optimizes its control parameters to simplify the parameter selection process and to speed up the convergent process. In one iteration, crossover and mutation operations are implemented on the solutions constructed, and the mutation probability was determined by the solution distribution. Experimental results show that our algorithm can obtain high quality solutions, get high convergence speed, and meet the quality of service requirement in real network","PeriodicalId":202629,"journal":{"name":"First International Multi-Symposiums on Computer and Computational Sciences (IMSCCS'06)","volume":"189 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A New Way of Solving Multiple Constrained QoS Multi-routing Problems\",\"authors\":\"Ling Qin, Yixin Chen, Jianli Luo, Jing Guo, Ling Chen\",\"doi\":\"10.1109/IMSCCS.2006.18\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new way of solving the bandwidth, delay, delay jitter and packet loss constrained least-cost quality of service (QoS) multi-routing problem is presented. It harmonizes the intrinsic attributes of each constraint of QoS and in different stage, the algorithm updates pheromone according to different constraints, optimizes its control parameters to simplify the parameter selection process and to speed up the convergent process. In one iteration, crossover and mutation operations are implemented on the solutions constructed, and the mutation probability was determined by the solution distribution. Experimental results show that our algorithm can obtain high quality solutions, get high convergence speed, and meet the quality of service requirement in real network\",\"PeriodicalId\":202629,\"journal\":{\"name\":\"First International Multi-Symposiums on Computer and Computational Sciences (IMSCCS'06)\",\"volume\":\"189 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-06-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"First International Multi-Symposiums on Computer and Computational Sciences (IMSCCS'06)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IMSCCS.2006.18\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"First International Multi-Symposiums on Computer and Computational Sciences (IMSCCS'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMSCCS.2006.18","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A New Way of Solving Multiple Constrained QoS Multi-routing Problems
A new way of solving the bandwidth, delay, delay jitter and packet loss constrained least-cost quality of service (QoS) multi-routing problem is presented. It harmonizes the intrinsic attributes of each constraint of QoS and in different stage, the algorithm updates pheromone according to different constraints, optimizes its control parameters to simplify the parameter selection process and to speed up the convergent process. In one iteration, crossover and mutation operations are implemented on the solutions constructed, and the mutation probability was determined by the solution distribution. Experimental results show that our algorithm can obtain high quality solutions, get high convergence speed, and meet the quality of service requirement in real network