UPM Institutional Repository

Performance evaluation of load balancing algorithm for virtual machine in data centre in cloud computing


Citation

Parmesivan, Yuganes and Hasan, Sazlinah and Muhammed, Abdullah (2018) Performance evaluation of load balancing algorithm for virtual machine in data centre in cloud computing. International Journal of Engineering and Technology, 7 (4.31). 386 - 390. ISSN 2319-8613; ESSN: 0975-4024

Abstract

Cloud computing has become biggest buzz in the computer era these days.It runs entire operating systems on the cloud and doeverything on cloud to store data off-site.Cloud computing is primarily based on grid computing, but it’s a new computational model.Cloud computing has emerged into a new opportunity to further enhance way of hosting data centre and provide services.The primary substance of cloud computing is to deal the computing power,storage,different sort of stages and services which assigned tothe external users on demand through the internet.Task scheduling in cloud computing is vital role optimisation and effective dynamic resource allocation for load balancing.In cloud, the issue focused is under utilisation and over utilisation of the resources to distribute workload of multiple network links for example,when cloud clients try to access and send request tothe same cloud server while the other cloud server remain idle at that moment, leads to the unbalanced of workload on cloud data centers.Thus, load balancing is to assign tasks to the individual cloud data centers of the shared system so that no single cloud data centers is overloaded or under loaded.A Hybrid approach of Honey Bee (HB) and Particle Swarm Optimisation (PSO) load balancing algorithm is combined in order to get effective response time.The proposed hybrid algorithm has been experimented by using CloudSim simulator.The result shows that the hybrid load balancing algorithm improves the cloud system performance by reducing the response time compared to the Honey Bee (HB) and Particle Swarm Optimisation (PSO) load balancing algorithm.


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Additional Metadata

Item Type: Article
Divisions: Faculty of Computer Science and Information Technology
Publisher: Engg Journals Publications
Keywords: Cloud computing; Honey Bee (HB); Particle Swarm Optimization (PSO); Hybrid; Response time
Depositing User: Mr. Sazali Mohamad
Date Deposited: 14 Oct 2019 05:49
Last Modified: 14 Oct 2019 05:49
URI: http://psasir.upm.edu.my/id/eprint/75262
Statistic Details: View Download Statistic

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