Abstract

Primary target of cloud provider is to provide the maximum resource utilization and increase the revenue by reducing energy consumption and operative cost. In the service providers point of view, resource allocation, resource sharing, migration of resources on demand, memory management, storage management, load balancing, energy efficient resource usage, computational complexity handling in virtualization are some of the major tasks that has to be dealt with. The major issue focused in this paper is to reduce the energy consumption problem and management of computation capacity utilization. For the same, an energy efficient resource management method is proposed to grip the resource scheduling and to minimize the energy utilized by the cloud datacenters for the computational work. Here a novel resource allocation mechanism is proposed, based on the optimization techniques. Also a novel dynamic virtual machine (VM) allocation method is suggested to help dynamic virtual machine allocation and job rescheduling to improve the consolidation of resources to execute the jobs. Experimental results indicated that proposed strategy outperforms as compared to the existing systems.

Highlights

  • As in cloud computing, pay-per-use services are used which avoids the huge capital investment of deploying the hardware, software and other resources at home

  • The major issue focused in this paper is to reduce the energy consumption problem and management of computation capacity utilization

  • Based on the research gap, here we have proposed a system to design and analyze energy efficient resource management method by allocation of various resources to virtual machines for higher utilization of resources and to reduce energy consumption

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Summary

Introduction

Pay-per-use services are used which avoids the huge capital investment of deploying the hardware, software and other resources at home. It has some critical issues of being over-charged, privacy leak and intervention of unauthorized service providers [1,2,3]. The major issue focused in this research work is to reduce the energy consumption problem and management of computation capacity utilization [15,16]. To overcome the above mention issues, a novel energy efficient resource management system is proposed to handle the resource scheduling and for the minimization of the energy utilized by the cloud data centers for the computational work.

Related Work
Contribution
System Model
System Workflow
VMs Creation
Cloudlet or Job Creation
Energy Consumption
Job Allocation
Algorithm
Performance Analysis
Findings
Conclusion
Full Text
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