{"title":"Towards Optimal Scheduling for Global Computing under Probabilistic, Interval, and Fuzzy Uncertainty, with Potential Applications to Bioinformatics","authors":"R. Araiza, M. Taufer, M. Leung","doi":"10.1109/NAFIPS.2007.383894","DOIUrl":null,"url":null,"abstract":"In many practical situations, in particular in many bioinformatics problems, the amount of required computations is so huge that the only way to perform these computations in reasonable time is to distribute them between multiple processors. The more processors we engage, the faster the resulting computations; thus, in addition to processor exclusively dedicated to this job, systems often use idle time on other processors. The use of these otherwise engaged processors adds additional uncertainty to computations. How should we schedule the computational tasks so as to achieve the best utilization of the computational resources? Because of the presence of uncertainty, this scheduling problem is very difficult not only to solve but even to formalize (i.e., to describe in precise terms). In this paper, we provide the first steps towards formalizing and solving this scheduling problem.","PeriodicalId":292853,"journal":{"name":"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAFIPS.2007.383894","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In many practical situations, in particular in many bioinformatics problems, the amount of required computations is so huge that the only way to perform these computations in reasonable time is to distribute them between multiple processors. The more processors we engage, the faster the resulting computations; thus, in addition to processor exclusively dedicated to this job, systems often use idle time on other processors. The use of these otherwise engaged processors adds additional uncertainty to computations. How should we schedule the computational tasks so as to achieve the best utilization of the computational resources? Because of the presence of uncertainty, this scheduling problem is very difficult not only to solve but even to formalize (i.e., to describe in precise terms). In this paper, we provide the first steps towards formalizing and solving this scheduling problem.