Fault Tolerance Enhancement Through Load Balancing Optimization in Cloud Computing

Authors

  • Bikash Chandra Pattnaik , Bidush Kumar Sahoo, Arabinda Pradhan , Satya Ranjan Mishra , Himadri Sekhar Tripathy , Payal Agasti

Keywords:

Resource Utilization, Fault Tolerance, PSO, Load Balancing, Makespan

Abstract

In cloud computing, a significant demand for data requests in order to deliver on-demand services at the lowest possible cost. As a result, servers are essential to handle the cloud requests that are dispersed among several geographic zones. Due to less number of servers available in datacenter, some of them are overloaded and some servers are idle or underloaded. This results in requests failing and degrade the system performance. To solve this issue this paper proposed a Particle Swarm Optimization Based Fault Tolerance Load Balancing algorithm (PSOBFTLB). This algorithm is used to provide the flexible and reliability services to each cloud user and maintain the balance of load in each machine by checking the status. To verify our work, a series of experiments over multiple datasets are done by using the CloudSim simulator. According to the simulation results, the PSOBFTLB algorithm works better while using 5% more resources, reduces 15% of the execution time, 12% of the makespan time, 9% of the average response time, and 8% of the average waiting time. Overall, it increases 12% throughput by taking 10% more task is completed as compare with other algorithms such as DLBA and ACO-VMM algorithm.

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Published

12.06.2024

How to Cite

Bikash Chandra Pattnaik. (2024). Fault Tolerance Enhancement Through Load Balancing Optimization in Cloud Computing. International Journal of Intelligent Systems and Applications in Engineering, 12(4), 172–180. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6185

Issue

Vol. 12 No. 4 (2024)

Section

Research Article

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