{"title":"网格工作流中经济驱动的资源分配中间件","authors":"Pengcheng Xiong, Yushun Fan","doi":"10.1109/EDOCW.2007.2","DOIUrl":null,"url":null,"abstract":"In order to accomplish high performance on grid workflow, grid resource management system needs a smart and swift resource allocation middleware. In this paper, we study the economy driven resource allocation problem based on market model of grid resource management architectures. We model the problem as the multiple choice knapsack problem (MCKP) and design the resource allocation optimization algorithm to minimize the average turnaround time of the grid workflow. The complexity analysis shows that the optimization algorithm leads to more efficient resource allocation than many current algorithms. The algorithm is also proved to be especially appropriate since the problem's own characteristics can accelerate the algorithm implementation process.","PeriodicalId":181454,"journal":{"name":"2007 Eleventh International IEEE EDOC Conference Workshop","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Economy Driven Resource Allocation Middleware for Grid Workflow\",\"authors\":\"Pengcheng Xiong, Yushun Fan\",\"doi\":\"10.1109/EDOCW.2007.2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to accomplish high performance on grid workflow, grid resource management system needs a smart and swift resource allocation middleware. In this paper, we study the economy driven resource allocation problem based on market model of grid resource management architectures. We model the problem as the multiple choice knapsack problem (MCKP) and design the resource allocation optimization algorithm to minimize the average turnaround time of the grid workflow. The complexity analysis shows that the optimization algorithm leads to more efficient resource allocation than many current algorithms. The algorithm is also proved to be especially appropriate since the problem's own characteristics can accelerate the algorithm implementation process.\",\"PeriodicalId\":181454,\"journal\":{\"name\":\"2007 Eleventh International IEEE EDOC Conference Workshop\",\"volume\":\"43 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-10-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 Eleventh International IEEE EDOC Conference Workshop\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EDOCW.2007.2\",\"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 Eleventh International IEEE EDOC Conference Workshop","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EDOCW.2007.2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Economy Driven Resource Allocation Middleware for Grid Workflow
In order to accomplish high performance on grid workflow, grid resource management system needs a smart and swift resource allocation middleware. In this paper, we study the economy driven resource allocation problem based on market model of grid resource management architectures. We model the problem as the multiple choice knapsack problem (MCKP) and design the resource allocation optimization algorithm to minimize the average turnaround time of the grid workflow. The complexity analysis shows that the optimization algorithm leads to more efficient resource allocation than many current algorithms. The algorithm is also proved to be especially appropriate since the problem's own characteristics can accelerate the algorithm implementation process.