A Multi-objective Hybrid Cloud Resource scheduling Method Based on Deadline and Cost Constraints

被引：49

作者：

Zuo, Liyun ^{[1
,2
]}

Shu, Lei ^{[1
,3
]}

Dong, Shoubin ^{[2
]}

Chen, Yuanfang ^{[1
]}

Yan, Li ^{[1
]}

机构：

[1] Guangdong Univ Petrochem Technol, Guangdong Prov Key Lab Petrochem Equipment Fault, Maoming 525000, Peoples R China

[2] South China Univ Technol, Sch Comp Sci & Engn, Guangdong Key Lab Commun & Comp Network, Guangzhou 510640, Guangdong, Peoples R China

[3] Univ Lincoln, Sch Engn, Lincoln LN6 7TS, England

来源：

IEEE ACCESS | 2017年 / 5卷

关键词：

Hybrid cloud; resource utilization; task scheduling; deadline; cost constraint; MANAGEMENT;

D O I：

10.1109/ACCESS.2016.2633288

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We propose a task-oriented multi-objective scheduling method based on ant colony optimization (MOSACO) to optimize the finite pool of public and private computing resources in a hybrid cloud computing environment according to deadline and cost constraints. MOSACO is employed to minimize task completion times and costs using time-first and cost-first single-objective optimization strategies, respectively, and to maximize user quality of service and the profit of resource providers using an entropy optimization model. The effectiveness of the MOSACO algorithm based on multiple considerations of task completion time, cost, number of deadline violations, and degree of private resource utilization is verified using simulation and three application examples. Comparisons with similar scheduling methods demonstrate that MOSACO provides the highest optimality, and that the time-first and cost-first strategies provide definite advantages for minimizing completion time and cost, respectively.

引用

页码：22067 / 22080

页数：14

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