Navigating the Cloud: An In-Depth Exploration of HISA Load Balancing for Dynamic Task Appropriation

Abstract

In a cloud computing (CC) environs,job exhibit variations in durations, start times, and execution times when assigned to virtual machines (VMs). Therefore, achieving load balancing (LB) across these VMs becomes crucial to optimize system proficiency and presentation. The present research introduces a novel LB method leveraging two optimization algorithms to address VM load balancing challenges. The initiated Dynamic Improved HISA Load Balancing proposal integrates an augment harmony-inspired algorithm with a simulated annealing algorithm for dynamic task allocation.In the harmony-inspired algorithm, an improved strategy for calculating Harmony Memory Consideration Rate (HMCR) is employed through a linear decreasing approach, updating HMCR and Pitch Adjustment Rate (PAR) values dynamically. A threshold probability is then evaluated to determine the finest suitability of the current Harmony, choosing eachof the make better harmony-inspired algorithm or simulated annealing for task allocation across available cloud resources.Simulations are conducted using the CloudSim simulator, considering scenarios with 3 or 5 VMs and 10 to 50 cloudlets. Each scenario is tested five times under operational conditions, and only the best performance outcomes are reported. Experimental results specify such a initiated Dynamic Enhanced HISA-LB proposal outperforms the prevail LBMPSO approach, demonstrating either minimized makespan or enhanced resource utilization with increased performance.