{"title":"基于改进差分进化蚁群算法的云计算资源调度","authors":"X. Xie, Ke Xu, Xiangwei Wang","doi":"10.1145/3335656.3335706","DOIUrl":null,"url":null,"abstract":"Due to the uneven distribution of cloud computing resources and the long processing time of resource scheduling, a cloud computing resource scheduling strategy based on improved differential evolution ant colony algorithm is proposed. By changing the size of the mutation operator F in the differential evolution algorithm, the differential evolution algorithm is controlled not to fall into the local search state and the convergence premature phenomenon. Then the improved differential evolution algorithm is combined with the ant colony algorithm to preserve the ant colony. The algorithm local search optimal characteristics, and has the characteristics of improved global evolution of differential evolution algorithm. The combination of the two can well optimize the problem of unbalanced load and long processing time in the cloud computing resource scheduling process.","PeriodicalId":396772,"journal":{"name":"Proceedings of the 2019 International Conference on Data Mining and Machine Learning","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Cloud computing resource scheduling based on improved differential evolution ant colony algorithm\",\"authors\":\"X. Xie, Ke Xu, Xiangwei Wang\",\"doi\":\"10.1145/3335656.3335706\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Due to the uneven distribution of cloud computing resources and the long processing time of resource scheduling, a cloud computing resource scheduling strategy based on improved differential evolution ant colony algorithm is proposed. By changing the size of the mutation operator F in the differential evolution algorithm, the differential evolution algorithm is controlled not to fall into the local search state and the convergence premature phenomenon. Then the improved differential evolution algorithm is combined with the ant colony algorithm to preserve the ant colony. The algorithm local search optimal characteristics, and has the characteristics of improved global evolution of differential evolution algorithm. The combination of the two can well optimize the problem of unbalanced load and long processing time in the cloud computing resource scheduling process.\",\"PeriodicalId\":396772,\"journal\":{\"name\":\"Proceedings of the 2019 International Conference on Data Mining and Machine Learning\",\"volume\":\"39 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-04-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2019 International Conference on Data Mining and Machine Learning\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3335656.3335706\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2019 International Conference on Data Mining and Machine Learning","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3335656.3335706","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Cloud computing resource scheduling based on improved differential evolution ant colony algorithm
Due to the uneven distribution of cloud computing resources and the long processing time of resource scheduling, a cloud computing resource scheduling strategy based on improved differential evolution ant colony algorithm is proposed. By changing the size of the mutation operator F in the differential evolution algorithm, the differential evolution algorithm is controlled not to fall into the local search state and the convergence premature phenomenon. Then the improved differential evolution algorithm is combined with the ant colony algorithm to preserve the ant colony. The algorithm local search optimal characteristics, and has the characteristics of improved global evolution of differential evolution algorithm. The combination of the two can well optimize the problem of unbalanced load and long processing time in the cloud computing resource scheduling process.