Paper Details
The Combined Method for Load Distribution in Cloud Computing
Authors
Sakshi Singh, Pradeep Tripathi
Abstract
Cloud registration enables the flow of information and provides users with valuable resources. Customers are only billed for the use of resources. Cloud computing is a technology that saves data and ensures that information remains accessible. When situations are transparent, the propensity for information hoarding increases rapidly. Stack adjustment serves as a test specifically designed for cloudy weather conditions. Load adjustment is a process that evenly distributes the dynamic workload across hubs in order to avoid overloading. It facilitates the process of legalising assets. Additionally, it enhances system performance. The bulk of the presently available calculations enable stack modification and enhanced asset utilisation. Cloud computing utilises memory, central processing unit (CPU), and system stacks. The load adjustment system identifies hubs that are carrying excessive load and redistributes the additional burden to hubs that are carrying less load. Load balancing distributes workloads around the cloud data centres of a shared system to ensure that none of them are overwhelmed or underutilised. This study presents a proposed approach that combines Honey Bee (HB) with Particle Swarm Optimisation (PSO) to achieve an acceptable response time and implement a load balancing strategy. The hybrid method was evaluated using the CloudSim simulator. The load balancing approaches of Honey Bee (HB) and Particle Swarm Optimisation (PSO) outperform the hybrid approach. The hybrid algorithm's enhanced responsiveness is seen in its accelerated response time. This study examines the response time, request processing, data centre utilisation, and cost of virtual machines via the use of a simulator.
Keywords
CPU, CC, Load sharing, SaaS, PaaS, IaaS, PSO, HB.
Citation
The Combined Method for Load Distribution in Cloud Computing. Sakshi Singh, Pradeep Tripathi. 2024. IJIRCT, Volume 10, Issue 2. Pages 1-17. https://www.ijirct.org/viewPaper.php?paperId=2404026