A Virtual Machine Deployment Approach Using Knowledge Curves in Cloud Simulation

摘要：

Optimal deployment of simulation virtual machines is an important issue in Cloud Simulation. Challenges involve resource cost prediction for simulation tasks as well as host physical machine selection for simulation virtual machines. In this paper we propose a novel approach using knowledge curves (i.e., curves as knowledge base) to solve this problem. First we present a resource cost estimation algorithm using empirical load curves synthesis, and then discuss a deployment target host selection algorithm by curves matching. This approach can provide a promising solution for intelligent deployment of virtual machines in Cloud Simulation. In addition, the proposed approach will be increasingly precise and effective as curve knowledge base increases.

关键词： cloud simulation collaborative simulation knowledge curve random factor virtualization

作者: Zhiyun Ren Xiao Song Lei Ren Lin Zhang Shaoyun Zhang

作者单位: School of Automation Science and Electrical EngineeringBeihang University, BUAABeijing 100191, China School of Automation Science and Electrical Engineering Beihang University, BUAA Beijing 100191, Chi

会议类型: 国际会议

会议名称: IEEE 10th International Conference on Industrial Informatics(第十届IEEE工业信息学国际学术会议 INDIN2012)

会议地点: 北京

会议语种:英文

页码: 342-346

在线出版日期: 2012-07-25（万方平台首次上网日期，不代表论文的发表时间）