Resource Renting for Periodical Cloud Workflow Applications

被引:18
|
作者
Chen, Long [1 ,2 ]
Li, Xiaoping [1 ,2 ]
Ruiz, Ruben [3 ]
机构
[1] Southeast Univ, Sch Comp Sci & Engn, Nanjing 211189, Peoples R China
[2] Southeast Univ, Minist Educ, Key Lab Comp Network & Informat Integrat, Nanjing 211189, Peoples R China
[3] Acc B Univ Politecn Valencia, Grp Sistemas Optimizac Aplicada, Inst Tecnol Informat, Ciudad Politecn Innovac,Edifico 8G, Valencia 46021, Spain
基金
中国国家自然科学基金;
关键词
Cloud computing; Processor scheduling; Scheduling; Schedules; Quality of service; Minimization; Partitioning algorithms; Resource allocation; long-term resources renting; periodical multiple workflows; cloud computing; TRADE-OFF PROBLEM; TASK; OPTIMIZATION;
D O I
10.1109/TSC.2017.2677450
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Cloud computing is a new resource provisioning mechanism, which represents a convenient way for users to access different computing resources. Periodical workflow applications commonly exist in scientific and business analysis, among many other fields. One of the most challenging problems is to determine the right amount of resources for multiple periodical workflow applications. In this paper, the periodical workflow applications scheduling problem with total renting cost minimization is considered. The novelty of this work relies precisely on this objective function, which is more realistic in practice than the more commonly considered makespan minimization. An integer programming model is constructed for the problem under study. A Precedence Tree based Heuristic (PTH) is developed which considers three types of initial schedule construction methods. Based on the initial schedule, two improvement procedures are presented. The proposed methods are compared with existing algorithms for the related makespan based multiple workflow scheduling problem. Experimental and statistical results demonstrate the effectiveness and efficiency of the proposed algorithm.
引用
收藏
页码:130 / 143
页数:14
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