An emerging method of digital computing known as "cloud computing" has recently gained immense popularity. While
there are many benefits to using the cloud over the internet, there are also serious challenges that must be addressed in order to boost
the efficiency of this method. Challenges to cloud computing via the internet include load balancing, work scheduling, fault tolerance,
and several security concerns. The effectiveness of the cloud may be enhanced by fixing a number of problems, one of the most
pressing being load balancing. To prevent any one node from being too overburdened or underused, a system employs a technique
known as load balancing. In order to increase utilization and minimize overall task execution time, load balancing algorithms are
developed to distribute work fairly across available resources. In this article, a review and comparison of different load-balancing
algorithms is provided. This paper provides a basis of the application of different load-balancing techniques, which utilize the
approach of soft computing within the cloud computing environment.
Keywords
Stochastic Hill Climbing (SHC), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Load Balance Improved
Min-Min Scheduling Algorithm (LBIMM).
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Arulmurugan Ramu
Arulmurugan Ramu
Department of Computer Science, Mattu University, Metu, Ethiopia.
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Cite this article
Arulmurugan Ramu, “Soft Computing Techniques to Analyze the Load Balancing in Cloud Environment”, Journal of Computing and Natural Science, vol.3, no.1, pp. 001-011, January 2023. doi: 10.53759/181X/JCNS202303001.
