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Efficient Resource Utilization by Reducing Broker Cost Using Multi-objective Optimization

  • B. K. Dhanalakshmi
  • K. C. Srikantaiah
  • K. R. Venugopal
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 771)

Abstract

Cloud computing is largely concerned with effective resource utilization and cost optimization. In the existing system, however, resources are under-utilized due to high cost. To overcome with this problem, in this chapter a new classification and merging model for reducing broker cost (CMRBC) is introduced to enable effective resource utilization and cost optimization in the cloud. CMRBC has enormous benefits. First, it has a cost-effective solution for service providers and customers. Second, for every job, virtual machine (VM) creation is avoided to reduce broker cost. Because of allocation, the creation or selection of VM resources is done based on the broker. Thus, CMRBC implements an efficient system of resource allocation that reduces resource usage cost. Our experimental results show that CMRBC achieves greater than 40% reduction in broker cost and 10% in response time.

Keywords

Broker cost Cloud computing Classification Cost effectiveness Merging Multi-objective optimization Resource utilization Scheduling 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • B. K. Dhanalakshmi
    • 1
  • K. C. Srikantaiah
    • 1
  • K. R. Venugopal
    • 2
  1. 1.Department of Computer Science and EngineeringSJB Institute of TechnologyBangaloreIndia
  2. 2.Department of Computer Science and EngineeringUniversity Visvesvaraya College of EngineeringBangaloreIndia

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