Efficiently Consolidating Virtual Data Centers for Time-Varying Resource Demands

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

1 Scopus Citations
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Author(s)

  • Yongcheng Li
  • Yonghu Yan
  • Wei Chen
  • Sanjay Kumar Bose
  • Gangxiang Shen

Related Research Unit(s)

Detail(s)

Original languageEnglish
Number of pages15
Journal / PublicationIEEE Transactions on Cloud Computing
Publication statusOnline published - 25 May 2020

Abstract

Virtual data center (VDC) embedding is a vital problem to be carefully addressed. However, existing studies on VDC embedding mostly assume that the capacity of each VDC is fixed, but do not consider the time-varying feature of resource demands. To overcome this inefficiency, we propose a new VDC consolidation scheme that considers the time-varying feature of resource demands when embedding VDCs. We first develop a resource demand prediction model for each VDC using the Long Short-Term Memory (LSTM) neural network. Based on the predicted resource demands, we then embed VDCs whose peaks and valleys of resource demands stagger each other onto common physical servers and links, such that the required physical resources can be minimized under the condition that all the resource demands of different VDCs are satisfied at all the different moments. An integer linear programming (ILP) model and a resource demand correlation-based heuristic algorithm are also developed for the proposed scheme. Simulation results show that the proposed scheme can significantly improve resource utilization in a DC, which saves up to 25% of physical servers and 29% of physical links used for accommodating the same requests as compared to a scheme assigning resources based on the fixed capacity assumption.

Research Area(s)

  • Virtual data center consolidation, Time-varying resource demands, Correlation, LSTM

Citation Format(s)

Efficiently Consolidating Virtual Data Centers for Time-Varying Resource Demands. / Guo, Chao; Li, Yongcheng; Yan, Yonghu; Chen, Wei; Bose, Sanjay Kumar; Shen, Gangxiang.

In: IEEE Transactions on Cloud Computing, 25.05.2020.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review