Optimization of Composite Cloud Service Processing with Virtual Machines

被引：18

作者：

Di, Sheng ^{[1
]}

Kondo, Derrick ^{[2
]}

Wang, Cho-Li ^{[3
]}

机构：

[1] Argonne Natl Lab, MCS Div, Argonne, IL 60439 USA

[2] INRIA, Grenoble, France

[3] Univ Hong Kong, Dept Comp Sci, Hong Kong, Hong Kong, Peoples R China

来源：

IEEE TRANSACTIONS ON COMPUTERS | 2015年 / 64卷 / 06期

关键词：

Cloud resource allocation; task scheduling; resource allocation; virtual machine; minimization of overhead;

D O I：

10.1109/TC.2014.2329685

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

By leveraging virtual machine (VM) technology, we optimize cloud system performance based on refined resource allocation, in processing user requests with composite services. Our contribution is three-fold. (1) We devise a VM resource allocation scheme with a minimized processing overhead for task execution. (2) We comprehensively investigate the best-suited task scheduling policy with different design parameters. (3) We also explore the best-suited resource sharing scheme with adjusted divisible resource fractions on running tasks in terms of Proportional-share model (PSM), which can be split into absolute mode (called AAPSM) and relative mode (RAPSM). We implement a prototype system over a cluster environment deployed with 56 real VM instances, and summarized valuable experience from our evaluation. As the system runs in short supply, lightest workload first (LWF) is mostly recommended because it can minimize the overall response extension ratio (RER) for both sequential-mode tasks and parallel-mode tasks. In a competitive situation with over-commitment of resources, the best one is combining LWF with both AAPSM and RAPSM. It outperforms other solutions in the competitive situation, by 16 + % w.r.t. the worst-case response time and by 7.4 + % w.r.t. the fairness.

引用

页码：1755 / 1768

页数：14

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