A Novel Fusion Algorithm for Load Balancing to Maximize Response Time in Cloud Computing

Author(s)	Raghavendra Sridhar
Country	India
Abstract	In modern cloud computing environments, load balancing is a critical process for distributing immense network traffic across multiple servers to ensure high performance and efficiency. However, existing load balancing algorithms often struggle to optimally manage dynamic workloads, leading to suboptimal response times and increased operational costs. This paper addresses this gap by proposing a novel, efficient fusion algorithm designed to enhance load balancing in cloud infrastructures of varying scales. Our approach leverages a hybrid optimization method, combining Particle Swarm Optimization (PSO) with a Genetic Algorithm (GA), to dynamically route traffic and minimize latency. To validate its effectiveness, the proposed algorithm is benchmarked against established methods, including ESCE, Round Robin, and Throttled scheduling. The comparative analysis focuses on key performance metrics such as processing time and response time, demonstrating our algorithm's potential to significantly improve service efficiency and reduce overall system costs.
Keywords	Load Balancing, Cloud Computing, Fusion Algorithm, Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Response Time, Cost Optimization, Resource Scheduling.
Field	Engineering
Published In	Volume 1, Issue 2, September-October 2019
Published On	2019-09-06

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International Journal For Multidisciplinary Research