Variable Neighborhood Search-Based Symbiotic Organisms Search Algorithm for Energy-Efficient Scheduling of Virtual Machine in Cloud Data Center

  • Mohammed Abdullahi
  • Shafi’i Muhammad AbdulhamidEmail author
  • Salihu Idi Dishing
  • Mohammed Joda Usman
Part of the Green Energy and Technology book series (GREEN)


The quest for energy-efficient virtual machine placement algorithms has attracted significant attention of researchers in the cloud computing platform. This paper applied a novel symbiotic organisms search (SOS) algorithm to minimize the number of active server by consolidation VMs on few servers for energy savings. SOS algorithm was inspired by symbiotic relationship exhibit by organisms in an ecosystem to boost their chances of survival. Essentially, SOS mimics mutualism, commensalism, and parasitism forms of relationship for traversing the search space. Hybridized with variable neighborhood search, the hybrid algorithm is termed SOS-VNS. SOS-VNS algorithm is efficient in minimizing energy consumption and improving resource utilization. The SOS-VNS algorithm is applied to various workload instances with varying number of VMs in a simulated IaaS cloud. The results obtained showed that SOS-VNS outperforms the heuristics and achieved reasonable energy savings while improving resource utilization.


Energy efficiency Cloud computing Virtual machine placement Symbiotic organisms search 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Mohammed Abdullahi
    • 1
  • Shafi’i Muhammad Abdulhamid
    • 2
    Email author
  • Salihu Idi Dishing
    • 1
  • Mohammed Joda Usman
    • 3
  1. 1.Department of Computer ScienceAhmadu Bello UniversityZariaNigeria
  2. 2.Department of Cyber Security ScienceFederal University of Technology MinnaMinnaNigeria
  3. 3.Department of MathematicsBauchi State University GadauGadauNigeria

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