Sameer Shivle, H. Siegel, A. A. Maciejewski, Tarun Banka, Kiran Chindam, S. Dussinger, Andrew Kutruff, Prashanth Penumarthy, Prakash Pichumani, Praveen Satyasekaran, David Sendek, J. Sousa, J. Sridharan, Prasanna Sugavanam, J. Velazco
{"title":"在异构临时网格环境中具有多个版本的子任务的映射","authors":"Sameer Shivle, H. Siegel, A. A. Maciejewski, Tarun Banka, Kiran Chindam, S. Dussinger, Andrew Kutruff, Prashanth Penumarthy, Prakash Pichumani, Praveen Satyasekaran, David Sendek, J. Sousa, J. Sridharan, Prasanna Sugavanam, J. Velazco","doi":"10.1109/ISPDC.2004.34","DOIUrl":null,"url":null,"abstract":"An ad hoc grid is a heterogeneous computing system composed of mobile devices. The problem studied here is to statically assign resources to the subtasks of an application, which has an execution time constraint, when the resources are oversubscribed. Each subtask has a preferred version, and a secondary version that uses fewer resources. The goal is to assign resources so that the application meets its execution time constraint while minimizing the number of secondary versions used. Five resource allocation heuristics to derive near-optimal solutions to this problem are presented and evaluated.","PeriodicalId":62714,"journal":{"name":"骈文研究","volume":"174 1","pages":"380-387"},"PeriodicalIF":0.0000,"publicationDate":"2004-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"Mapping of subtasks with multiple versions in a heterogeneous ad hoc grid environment\",\"authors\":\"Sameer Shivle, H. Siegel, A. A. Maciejewski, Tarun Banka, Kiran Chindam, S. Dussinger, Andrew Kutruff, Prashanth Penumarthy, Prakash Pichumani, Praveen Satyasekaran, David Sendek, J. Sousa, J. Sridharan, Prasanna Sugavanam, J. Velazco\",\"doi\":\"10.1109/ISPDC.2004.34\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An ad hoc grid is a heterogeneous computing system composed of mobile devices. The problem studied here is to statically assign resources to the subtasks of an application, which has an execution time constraint, when the resources are oversubscribed. Each subtask has a preferred version, and a secondary version that uses fewer resources. The goal is to assign resources so that the application meets its execution time constraint while minimizing the number of secondary versions used. Five resource allocation heuristics to derive near-optimal solutions to this problem are presented and evaluated.\",\"PeriodicalId\":62714,\"journal\":{\"name\":\"骈文研究\",\"volume\":\"174 1\",\"pages\":\"380-387\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-07-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"骈文研究\",\"FirstCategoryId\":\"1092\",\"ListUrlMain\":\"https://doi.org/10.1109/ISPDC.2004.34\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"骈文研究","FirstCategoryId":"1092","ListUrlMain":"https://doi.org/10.1109/ISPDC.2004.34","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Mapping of subtasks with multiple versions in a heterogeneous ad hoc grid environment
An ad hoc grid is a heterogeneous computing system composed of mobile devices. The problem studied here is to statically assign resources to the subtasks of an application, which has an execution time constraint, when the resources are oversubscribed. Each subtask has a preferred version, and a secondary version that uses fewer resources. The goal is to assign resources so that the application meets its execution time constraint while minimizing the number of secondary versions used. Five resource allocation heuristics to derive near-optimal solutions to this problem are presented and evaluated.