An efficient load balancing scheduling strategy for cloud computing based on hybrid approach
by Md Oqail Ahmad; Rafiqul Zaman Khan
International Journal of Cloud Computing (IJCC), Vol. 9, No. 4, 2020

Abstract: Cloud computing is a promising paradigm that is widely used in both academia and industry. Dynamic demand for resources by users is one of the prime goals of scheduling process of task in cloud computing. Task scheduling is NP-hard problem which is responsible for allocating the task to VMs and maximising their utilisation while minimising the total task execution time. In this paper, the authors propose a load balancing scheduling strategy, hybridisation of RALB method using the PSO technique inspired by the honeybee behaviour proposed named as (PSO-RALB). This strategy optimises the results and perform scheduling based on resource aware load balancing scheme. The foraging behaviour of the honey bee optimisation algorithm is utilised to balance load across VM and resource aware is used to manage the resources. The computational results show that proposed scheme minimise the makespan time, total processing time, total processing cost and the degree of imbalance factor when compared with existing techniques PSO standard and PSO-based load balancing (PSO-LB) algorithm.

Online publication date: Fri, 08-Jan-2021

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Cloud Computing (IJCC):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com