{"title":"A Flexible Grid Task Scheduling Algorithm Based on QoS Similarity","authors":"Kunfang Song, Shufen Ruan, Minghua Jiang","doi":"10.4156/JCIT.VOL5.ISSUE7.21","DOIUrl":null,"url":null,"abstract":"s In grid computing, the goals of task scheduling is to achieve high system optimization performance while matching multi-dimension Quiality of Service(QoS) requirement of applications. Considering of the autonomous, heterogeneous and distributed feature of the grid system, in this paper, we propose a flexible task scheduling algorithm for grid computing after researching on the existing QoS Guide Min-min scheduling algorithm intensively, which is called distance-weighted measurement methodology (DWMM). We evaluate our algorithm within a simulated Gridsim environment. Experimental results once again proved that this flexible algorithm improve the system performance and load balancing.","PeriodicalId":360193,"journal":{"name":"J. Convergence Inf. Technol.","volume":"99 3","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"J. Convergence Inf. Technol.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4156/JCIT.VOL5.ISSUE7.21","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
s In grid computing, the goals of task scheduling is to achieve high system optimization performance while matching multi-dimension Quiality of Service(QoS) requirement of applications. Considering of the autonomous, heterogeneous and distributed feature of the grid system, in this paper, we propose a flexible task scheduling algorithm for grid computing after researching on the existing QoS Guide Min-min scheduling algorithm intensively, which is called distance-weighted measurement methodology (DWMM). We evaluate our algorithm within a simulated Gridsim environment. Experimental results once again proved that this flexible algorithm improve the system performance and load balancing.