{"title":"A proactive approach for coping with uncertain resource availabilities on desktop grids","authors":"Louis-Claude Canon, Adel Essafi, D. Trystram","doi":"10.1109/HiPC.2014.7116890","DOIUrl":null,"url":null,"abstract":"Uncertainties stemming from multiple sources affect distributed systems and jeopardize their efficient utilization. Desktop grids are especially concerned by this issue as volunteers lending their resources may have irregular and unpredictable behaviors. Efficiently exploiting the power of such systems raises theoretical issues that received little attention in the literature. In this paper, we assume that there exist predictions on the intervals during which machines are available. When these predictions have a limited estimation, it is possible to schedule a set of jobs such that the effective total execution time will not be higher than the predicted one. We formally prove that it is the case when scheduling jobs only in large intervals and when provisioning sufficient slacks to absorb uncertainties. We present multiple heuristics with various efficiencies and costs that are empirically assessed through simulations based on actual traces.","PeriodicalId":337777,"journal":{"name":"2014 21st International Conference on High Performance Computing (HiPC)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 21st International Conference on High Performance Computing (HiPC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HiPC.2014.7116890","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
Uncertainties stemming from multiple sources affect distributed systems and jeopardize their efficient utilization. Desktop grids are especially concerned by this issue as volunteers lending their resources may have irregular and unpredictable behaviors. Efficiently exploiting the power of such systems raises theoretical issues that received little attention in the literature. In this paper, we assume that there exist predictions on the intervals during which machines are available. When these predictions have a limited estimation, it is possible to schedule a set of jobs such that the effective total execution time will not be higher than the predicted one. We formally prove that it is the case when scheduling jobs only in large intervals and when provisioning sufficient slacks to absorb uncertainties. We present multiple heuristics with various efficiencies and costs that are empirically assessed through simulations based on actual traces.