School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu 611731, China

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Abstract—Cloud data centers (CDCs) provide key infrastructure for Cloud computing. Accurately allocating computing resources is very important for the CDCs to function efficiently. Current allocation of resources in CDCs is mostly dedicated and static. However, workloads for Cloud applications are highly variable which cause poor application performance, poor resource utilization or both. In this paper, considering both blocking and delay probability by applying queuing theories to model different scenarios, systematic adaptive dimensioning methods for CDCs are developed so that right amount of computing resources are allocated for variable workloads to meet quality of service requirements in different situations. Both single CDC and multiple CDCs with and without delay are considered. The proposed methods can be applied to dimension data centers efficiently and dynamically.

Index Terms—Cloud computing; Cloud Data Centers (CDCs); Adaptive Dimensioning Methods

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Cite: Wenhong Tian, "A Systematic Approach to Adaptive Dimensioning of Data Centers," Journal of Computers vol. 9, no. 2, pp. 266-274, 2014.