Power Efficient Server Consolidation for Cloud Data Center

Somnath Mazumdar, Marco Pranzo*

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review


Cloud computing has become an essential part of the global digital economy due to its extensibility, flexibility and reduced costs of operations. Nowadays, data centers (DCs) contain thousands of different machines running a huge number of diverse applications over an extended period. Resource management in Cloud is an open issue since an efficient resource allocation can reduce the infrastructure running cost. In this paper, we propose a snapshot-based solution for server consolidation problem from Cloud infrastructure provider (CIP) perspective. Our proposed mathematical formulation aims at reducing power cost by employing efficient server consolidation, and also considering the issues such as (i) mapping incoming and failing virtual machines (VMs), (ii) reducing a total number of VM migrations and (iii) consolidating running server workloads. We also compare the performance of our proposed model to the well-known Best Fit heuristics and its extension to include server consolidation via VM migration denoted as Best Fit with Consolidation (BFC). Our proposed mathematical formulation allows us to measure the solution quality in absolute terms, and it can also be applicable in practice. In our simulations, we show that relevant improvements (from 6% to 15%) over the widely adopted Best Fit algorithm achieved in a reasonable computing time.
Original languageEnglish
JournalFuture Generation Computer Systems
Pages (from-to)4-16
Number of pages13
Publication statusPublished - May 2017
Externally publishedYes


  • Cloud
  • Optimisation
  • Server consolidation
  • Virtual Machine allocation
  • Integer linear programming

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