{"title":"Design of candidate schedules for applying iterative ordinal optimisation for scheduling technique on cloud computing platform","authors":"Monika Yadav, A. Mishra, B. Balusamy","doi":"10.1504/ijims.2020.105027","DOIUrl":null,"url":null,"abstract":"In cloud computing, distributed resources are used on demand basis without having the physical infrastructure at the client end. Cloud has a large number of users and to deal with large number of task, so scheduling in cloud plays a vital role for task execution. Scheduling of various multitask jobs on clouds is considered as an NP-hard problem (Horng and Lin, 2017). In order to reduce the large scheduling search space, an iterative ordinal optimisation (IOO) method has already proposed. In this paper, a set of 30 candidate schedules denoted by set U are created. The set U is used in the exhaustive search of the best schedule. After analysing the set U, an ordered schedule vs. makespan graph is plotted. So in this work, set U is defined and created a base for applying IOO method to get optimal schedules. In this work, CloudSim version 3.0 has been used to test and analyse policies.","PeriodicalId":39293,"journal":{"name":"International Journal of Internet Manufacturing and Services","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/ijims.2020.105027","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Internet Manufacturing and Services","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/ijims.2020.105027","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 2
Abstract
In cloud computing, distributed resources are used on demand basis without having the physical infrastructure at the client end. Cloud has a large number of users and to deal with large number of task, so scheduling in cloud plays a vital role for task execution. Scheduling of various multitask jobs on clouds is considered as an NP-hard problem (Horng and Lin, 2017). In order to reduce the large scheduling search space, an iterative ordinal optimisation (IOO) method has already proposed. In this paper, a set of 30 candidate schedules denoted by set U are created. The set U is used in the exhaustive search of the best schedule. After analysing the set U, an ordered schedule vs. makespan graph is plotted. So in this work, set U is defined and created a base for applying IOO method to get optimal schedules. In this work, CloudSim version 3.0 has been used to test and analyse policies.
在云计算中,分布式资源按需使用,客户端不需要物理基础设施。云拥有大量的用户和处理大量的任务,因此云中的调度对任务的执行起着至关重要的作用。云上各种多任务作业的调度被认为是NP-hard问题(hong and Lin, 2017)。为了减小调度搜索空间,提出了一种迭代有序优化方法。本文创建了一个30个候选调度的集合,用集合U表示。集合U用于穷举搜索最优调度。在分析了集合U之后,绘制了有序的进度与完工时间图。因此,本文定义了集合U,并为应用IOO方法获得最优调度创建了基础。在这项工作中,使用了CloudSim 3.0版本来测试和分析策略。