{"title":"一种通用的计算网格资源调度算法","authors":"I. Ahmad, S. Faheem, G. Qasim","doi":"10.1109/ICET.2007.4516332","DOIUrl":null,"url":null,"abstract":"Task scheduling is a vital and challenging task in distributed computing specially in grid computing. The computational grid focuses on large-scale resource sharing. Because of heterogeneous resources in widely distributed autonomous domains, which makes task scheduling even more challenging. In this paper, a hybrid and general resource algorithm for computational grid, MMOD is presented. MMOD, a general resource scheduling algorithm for computational grid is proposed for task scheduling with time-cost minimization and with maximum resource utilization. The experiments show the performance improvement for applications and better resource utilization by this algorithm, raises the user satisfaction and minimizes time as well as cost.","PeriodicalId":346773,"journal":{"name":"2007 International Conference on Emerging Technologies","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"MMOD: A General Resource Scheduling Algorithm for Computational Grid\",\"authors\":\"I. Ahmad, S. Faheem, G. Qasim\",\"doi\":\"10.1109/ICET.2007.4516332\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Task scheduling is a vital and challenging task in distributed computing specially in grid computing. The computational grid focuses on large-scale resource sharing. Because of heterogeneous resources in widely distributed autonomous domains, which makes task scheduling even more challenging. In this paper, a hybrid and general resource algorithm for computational grid, MMOD is presented. MMOD, a general resource scheduling algorithm for computational grid is proposed for task scheduling with time-cost minimization and with maximum resource utilization. The experiments show the performance improvement for applications and better resource utilization by this algorithm, raises the user satisfaction and minimizes time as well as cost.\",\"PeriodicalId\":346773,\"journal\":{\"name\":\"2007 International Conference on Emerging Technologies\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 International Conference on Emerging Technologies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICET.2007.4516332\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 International Conference on Emerging Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICET.2007.4516332","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
MMOD: A General Resource Scheduling Algorithm for Computational Grid
Task scheduling is a vital and challenging task in distributed computing specially in grid computing. The computational grid focuses on large-scale resource sharing. Because of heterogeneous resources in widely distributed autonomous domains, which makes task scheduling even more challenging. In this paper, a hybrid and general resource algorithm for computational grid, MMOD is presented. MMOD, a general resource scheduling algorithm for computational grid is proposed for task scheduling with time-cost minimization and with maximum resource utilization. The experiments show the performance improvement for applications and better resource utilization by this algorithm, raises the user satisfaction and minimizes time as well as cost.