{"title":"可变切换时间任务的智能多机调度","authors":"Fei Lei, Y. Zou, Feng Zeng","doi":"10.1109/WCICA.2004.1343058","DOIUrl":null,"url":null,"abstract":"To find an optimal multi-machine schedule for a set of tasks with variable switch time, an optimal model was proposed, and a new intelligent algorithm with an adaptive structure was designed for less delay time and higher quality of service. If the server is under low average load, it used genetic algorithm and advanced greedy algorithm jointly to achieve a minimum task abandon ratio and a maximum task value, or else only advanced greedy algorithm was used to minimize delay time. The scheduler adopted runtime incremental parallel scheduling (RIPS) strategy, which combines the advantages of static and dynamic scheduling. The several simulation experiments show that the proposed schedule algorithm is valid and feasible.","PeriodicalId":331407,"journal":{"name":"Fifth World Congress on Intelligent Control and Automation (IEEE Cat. No.04EX788)","volume":"111 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Intelligent multi-machine scheduling on tasks with variable switch time\",\"authors\":\"Fei Lei, Y. Zou, Feng Zeng\",\"doi\":\"10.1109/WCICA.2004.1343058\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To find an optimal multi-machine schedule for a set of tasks with variable switch time, an optimal model was proposed, and a new intelligent algorithm with an adaptive structure was designed for less delay time and higher quality of service. If the server is under low average load, it used genetic algorithm and advanced greedy algorithm jointly to achieve a minimum task abandon ratio and a maximum task value, or else only advanced greedy algorithm was used to minimize delay time. The scheduler adopted runtime incremental parallel scheduling (RIPS) strategy, which combines the advantages of static and dynamic scheduling. The several simulation experiments show that the proposed schedule algorithm is valid and feasible.\",\"PeriodicalId\":331407,\"journal\":{\"name\":\"Fifth World Congress on Intelligent Control and Automation (IEEE Cat. No.04EX788)\",\"volume\":\"111 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-06-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Fifth World Congress on Intelligent Control and Automation (IEEE Cat. No.04EX788)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WCICA.2004.1343058\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fifth World Congress on Intelligent Control and Automation (IEEE Cat. No.04EX788)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCICA.2004.1343058","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Intelligent multi-machine scheduling on tasks with variable switch time
To find an optimal multi-machine schedule for a set of tasks with variable switch time, an optimal model was proposed, and a new intelligent algorithm with an adaptive structure was designed for less delay time and higher quality of service. If the server is under low average load, it used genetic algorithm and advanced greedy algorithm jointly to achieve a minimum task abandon ratio and a maximum task value, or else only advanced greedy algorithm was used to minimize delay time. The scheduler adopted runtime incremental parallel scheduling (RIPS) strategy, which combines the advantages of static and dynamic scheduling. The several simulation experiments show that the proposed schedule algorithm is valid and feasible.