Open Access

ARTICLE

Intelligent Cloud Based Load Balancing System Empowered with Fuzzy Logic

Atif Ishaq Khan¹, Syed Asad Raza Kazmi¹, Ayesha Atta^1,*, Muhammad Faheem Mushtaq², Muhammad Idrees³, Ilyas Fakir¹, Muhammad Safyan¹, Muhammad Adnan Khan⁴, Awais Qasim¹

1 Department of Computer Science, Government College University, Lahore, 54000, Pakistan
2 Department of Information Technology, Khwaja Fareed University of Engineering and Information Technology, Rahim Yar Khan, 64200, Pakistan
3 Department of Computer Science and Engineering, University of Engineering and Technology Lahore, Narowal Campus, 51600, Pakistan
4 Department of Computer Science, Riphah International University Lahore Campus, Lahore, 54000, Pakistan

* Corresponding Author: Ayesha Atta. Email:

(This article belongs to the Special Issue: Machine Learning-based Intelligent Systems: Theories, Algorithms, and Applications)

Computers, Materials & Continua 2021, 67(1), 519-528. https://doi.org/10.32604/cmc.2021.013865

Received 25 August 2020; Accepted 01 November 2020; Issue published 12 January 2021

Abstract

Cloud computing is seeking attention as a new computing paradigm to handle operations more efficiently and cost-effectively. Cloud computing uses dynamic resource provisioning and de-provisioning in a virtualized environment. The load on the cloud data centers is growing day by day due to the rapid growth in cloud computing demand. Elasticity in cloud computing is one of the fundamental properties, and elastic load balancing automatically distributes incoming load to multiple virtual machines. This work is aimed to introduce efficient resource provisioning and de-provisioning for better load balancing. In this article, a model is proposed in which the fuzzy logic approach is used for load balancing to avoid underload and overload of resources. A Simulator in Matlab is used to test the effectiveness and correctness of the proposed model. The simulation results have shown that our proposed intelligent cloud-based load balancing system empowered with fuzzy logic is better than previously published approaches.

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Citations