Toward Virtual Machine Packing Optimization Based on Genetic Algorithm

被引：0

作者：

Nakada, Hidemoto ^{[1
]}

Hirofuchi, Takahiro ^{[1
]}

Ogawa, Hirotaka ^{[1
]}

Itoh, Satoshi ^{[1
]}

机构：

[1] Natl Inst Adv Ind Sci & Technol, Tsukuba, Ibaraki 3058568, Japan

来源：

DISTRIBUTED COMPUTING, ARTIFICIAL INTELLIGENCE, BIOINFORMATICS, SOFT COMPUTING, AND AMBIENT ASSISTED LIVING, PT II, PROCEEDINGS | 2009年 / 5518卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

To enable efficient resource provisioning in HaaS (Hardware as a Service) cloud systems, virtual machine packing, which migrate virtual machines to minimize running real node, is essential. The virtual machine packing problem is a multi-objective optimization problem with several parameters and weights on parameters change dynamically subject to cloud provider preference. We propose to employ Genetic Algorithm (GA) method, that is one of the meta-heuristics. We implemented a prototype Virtual Machine packing optimization mechanism on Grivon, which is a virtual cluster management; system we have been developing. The preliminary evaluation implied the GA method is promising for the problem.

引用

页码：651 / 654

页数：4