Provisioning Virtual Resources Adaptively in Elastic Compute Cloud Platforms

Author:

Zhang Fan1,Cao Junwei1,Cai Hong2,Wu Cheng1

Affiliation:

1. Tsinghua University, China

2. IBM China Software Development Lab, China

Abstract

Provisioning Virtual machines on demand is significant in elastic compute cloud for reliable service delivery. The importance and major difficulty lies in satisfying the conflicting objectives of satisfying contracted service level agreement while lowering used resource costs. In this paper, the authors propose a mathematical multi-tier framework for adaptive virtual resource allocation problem. The framework captures the performance of the virtualized cloud platform gracefully. The authors first use simulations to derive virtual resource allocation policies, and later use real benchmarking applications, to verify the effectiveness of this framework. Experimental results show that the model can be simply and effectively used to satisfy the response time requirement as well as lowering the cost of using the virtual machine resources.

Publisher

IGI Global

Subject

Computer Networks and Communications,Information Systems,Software

Reference25 articles.

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