Enhanced Weighted Round Robin Algorithm to Balance the Load for Effective Utilization of Resource in Cloud Environment

Authors

  • Garima Sinha IIMT Engineering College
  • Deepak Kumar Sinha IIMTU

DOI:

https://doi.org/10.4108/eai.7-9-2020.166284

Keywords:

Round Robin (RR) alg orithm, virtual machine (VMs), load balancing, scalability, cloudlet, Data Center (DC), EWRR algorithm, RMCT, Throttled, Hybrid load balancing algorithm

Abstract

Cloud computing contains basically virtualization, networking, distributing computing, software and web services over the cloud. Cloud computing provide basis on demand hosting computing resources and cloud services over the cloud or internet on pay per use basis. Due of high availability, fault tolerance, scalability, management simplicity and low cost Cloud computing currently become best method of computation over large scalable network environment .Efficient load balancing make cloud computing environment more efficient and also get better user satisfaction. The idea of this paper is to propose load balancing algorithm for utilization of resource efficiently and to compare the performance of projected algorithms with well-known load balancing algorithms. The newly proposed algorithm will consider size of cloudlet, expected completion time of tasks by virtual machine and runtime properties of virtual machines to map’s the incoming request to virtual machine in impartially and efficiently. The response time of EWRR method is less in comparison of others methods. It has been found that EWRR having the better result in comparison of RR, Throttled, ACO and Hybrid response times which are 0.77, 2.20,8.31, 20.82 and 100 respectively. In this paper, by proposing a virtual machine load balancing algorithm that aims to improve the average response time and average processing time of the system in the cloud environment.

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Published

07-09-2020

How to Cite

[1]
G. Sinha and D. Kumar Sinha, “Enhanced Weighted Round Robin Algorithm to Balance the Load for Effective Utilization of Resource in Cloud Environment”, EAI Endorsed Trans Cloud Sys, vol. 6, no. 18, p. e4, Sep. 2020.