Cuckoo search based resource optimization of datacenters

Sadiq M. Sait*, Abubakar Bala, Aiman H. El-Maleh

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

50 Scopus citations


With advancements in virtualization technology, datacenters are often faced with the challenge of managing large numbers of virtual machine (VM) requests. Due to this large amount of VM requests, it has become practically impossible to search all possible VM placements in order to find a solution that best optimizes certain design objectives. As a result, managers of datacenters have resorted to the employment of heuristic optimization algorithms for VM placement. In this paper, we employ the cuckoo search optimization (CSO) algorithm to solve the VM placement problem of datacenters. Firstly, we use the CSO to optimize the datacenter for the minimization of the number of physical machines used for placement. Secondly, we implement a multiobjective CSO algorithm to simultaneously optimize the power consumption and resource wastage of the datacenter. Simulation results show that both CSO algorithms outperform the reordered grouping genetic algorithm (RGGA), the grouping genetic algorithm (GGA), improved least-loaded (ILL) and improved FFD (IFFD) methods of VM placement.

Original languageEnglish
Pages (from-to)489-506
Number of pages18
JournalApplied Intelligence
Issue number3
StatePublished - 1 Apr 2016

Bibliographical note

Publisher Copyright:
© 2015, Springer Science+Business Media New York.


  • Cloud computing
  • Combinatorial optimization
  • Cuckoo search
  • Datacenter
  • Lévy flight
  • NP-Hard

ASJC Scopus subject areas

  • Artificial Intelligence


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