{"title":"异构分布式环境下工作流调度的协同进化遗传算法","authors":"N. Butakov, D. Nasonov","doi":"10.1109/ICAICT.2014.7035936","DOIUrl":null,"url":null,"abstract":"Flexible and efficient workflow scheduling is a key feature for modern distributed heterogeneous computational environments to satisfy requirements of scientific community. In this paper, we propose novel co-evolutional scheduling algorithm which demonstrates with conducted experiments how nature-inspired concept can improve existing schedulers and help to generate better schedules oriented on makespan minimization.","PeriodicalId":103329,"journal":{"name":"2014 IEEE 8th International Conference on Application of Information and Communication Technologies (AICT)","volume":" 7","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Co-evolutional genetic algorithm for workflow scheduling in heterogeneous distributed environment\",\"authors\":\"N. Butakov, D. Nasonov\",\"doi\":\"10.1109/ICAICT.2014.7035936\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Flexible and efficient workflow scheduling is a key feature for modern distributed heterogeneous computational environments to satisfy requirements of scientific community. In this paper, we propose novel co-evolutional scheduling algorithm which demonstrates with conducted experiments how nature-inspired concept can improve existing schedulers and help to generate better schedules oriented on makespan minimization.\",\"PeriodicalId\":103329,\"journal\":{\"name\":\"2014 IEEE 8th International Conference on Application of Information and Communication Technologies (AICT)\",\"volume\":\" 7\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE 8th International Conference on Application of Information and Communication Technologies (AICT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAICT.2014.7035936\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE 8th International Conference on Application of Information and Communication Technologies (AICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAICT.2014.7035936","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Co-evolutional genetic algorithm for workflow scheduling in heterogeneous distributed environment
Flexible and efficient workflow scheduling is a key feature for modern distributed heterogeneous computational environments to satisfy requirements of scientific community. In this paper, we propose novel co-evolutional scheduling algorithm which demonstrates with conducted experiments how nature-inspired concept can improve existing schedulers and help to generate better schedules oriented on makespan minimization.
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