Work

Review on the Load Balancing in Cloud Computing using Particle Swarm Optimization

Year: 2024
Type: conference-paper
Abstract: This paper objective to investigate the application of PSO for load balancing in cloud computing, optimize to solve the load balancing challenges in cloud environment and focus to distribute the workload across different virtual machines [1]. PSO is a metaheuristic optimization technique inspired by collective behavior of fish schooling and bird flocking., is used to explore the resource utilization and increase the system performance by redistribute the load across nodes. This study focuses to solve the challenges occurred during dynamic nature of cloud environment. Every node has its own capacity to handle the workload so various task scheduling algorithm applied to manage the workload. By using the load balancing approach maximize the global convergence with various parameter. In this research develops a robust load-balancing model that adopt to changing conditions and improves the responsiveness and efficiency of cloud services. Cloudsim simulator is also used to compare using PSO with various traditional algorithms.
Authors: Santosh Gupta, Deepika Saxena, Arif M. Khan
Institution: Poornima University
Language: English
Open Access status: hybrid
OpenAlex ID: W4413911508
FWCI: 0.401
Cites: 17
Cited by: 1
Related to: 10