Elastic scaling of virtual clusters in cloud data center networks

Data Center Networks (DCNs) have become more extensively applied in cloud computing in recent years. One important mission for DCNs is to satisfy the fluctuation of on-demand resources for tenants. Existing works fail to fully consider the placement techniques and the elasticity of the physical resource in the DCN at the same time during the scaling of virtual clusters (VCs). To address this, we use elasticity to measure the scaling potential of VCs in terms of both computation and communication resources. In this paper, we consider elastic scaling for existing VCs to maximize the elasticity with the constraint of communication cost in the DCN. We achieve this through a resource allocation scheme, VCS, which comes with provable optimality guarantees for single VC scaling. After that, we extend our scheme for multiple VCs scaling, and we prove that scaling multiple VCs for the over-time elasticity maximization problem is NP-hard. We propose heuristic algorithms MVCS and OMVCS for both offline and online conditions for the multiple VCs scaling. Extensive simulations demonstrate that our elastic VC scaling placement schemes outperform existing state-of-the-art methods in terms of flexibility in the DCN.