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Efficient Cloudlet Allocation to Virtual Machine to Impact Cloud System Performance

Author

Listed:
  • Lizia Sahkhar

    (National Institute of Technology Meghalaya, India)

  • Bunil Kumar Balabantaray

    (National Institute of Technology Meghalaya, India)

  • Satyendra Singh Yadav

    (National Institute of Technology Meghalaya, India)

Abstract

Performance is an essential characteristic of any cloud computing system. It can be enhance through parallel computing, scheduling and load balancing. This work evaluates the connection between the response time (RT) and virtual machine’s (VM) CPU utilization when cloudlets are allocated from the datacenter broker to VM. To accentuate the RT and VM’s CPU utilization, a set of 100 and 500 heterogeneous cloudlets are analyzed under hybridized provisioning, scheduling and allocation algorithm using CloudSim simulator. These includes space shared (SS) and time shared (TS) provisioning policy, shortest job first (SJF), first come first search (FCFS), round robin (RR) and a novel length-wise allocation (LwA) algorithm. The experimental analysis shows that the RT is the least when SJF is combined with RR allocation at 40.665 secs and VM’s CPU utilization is the least when SJF is combined with LwA policy at 12.48 in all combinations of SS and TS provisioning policy.

Suggested Citation

  • Lizia Sahkhar & Bunil Kumar Balabantaray & Satyendra Singh Yadav, 2022. "Efficient Cloudlet Allocation to Virtual Machine to Impact Cloud System Performance," International Journal of Information System Modeling and Design (IJISMD), IGI Global, vol. 13(6), pages 1-21, January.
    • Handle: RePEc:igg:jismd0:v:13:y:2022:i:6:p:1-21
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