Typical Virtual Appliances: An optimized mechanism for virtual appliances provisioning and management

Authors:
Tianle Zhang;Zhihui Du;Yinong Chen;Xiang Ji;Xiaoying Wang
Affiliations:
Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China;Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China;Computer Science and Engineering, Arizona State University, Tempe, AZ 85287, USA;School of Computer Science and Engineering, Beihang University, Beijing 100191, China;Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China and Department of Computer Technology ...
Venue:
Journal of Systems and Software
Year:
2011

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Abstract

A computing infrastructure requirement in the cloud computing environment can be specified and composed using virtual appliances, which forms the infrastructure-as-a-service (IaaS). Due to the diversity of user requirements, a large number of virtual appliances may be needed. We propose a mechanism called Typical Virtual Appliances (TVAs), an efficient method for providing virtual appliances. In this paper, we present the concept of TVAs and formulate it as an optimization problem with given constraints. With analysis of the software download logs of real web sites, we discover that the number of user requirements follows a quadratic polynomial distribution, and the user requirements are clustered in nature. According to this finding, we develop a clustering-based TVAs generation algorithm, and we show that this algorithm can achieve the optimal result. The clustering algorithm can generate TVAs, which can be transformed to other virtual appliances easily and efficiently. We further design a TVA Management System (TVAMS) to support this mechanism. The simulation results show that our method can meet most of the user requirements efficiently with low storage overhead.