A Comparative Assessment of Load Balancing Techniques in Cloud Computing: A Review

Abstract

Cloud computing is a resilient framework that enables users and organizations to procure services tailored to their needs. This model encompasses many services, including storage, deployment platforms, seamless access to web services, and more. However, load balancing poses a common challenge in the cloud, impacting the ability to uphold application performance aligned with the required quality of service (QoS) expected by enterprises from cloud providers. Achieving an equitable distribution of workloads among servers proves challenging for cloud providers. An effective load-balancing technique should optimize resource utilization in virtual machines, ensuring high user satisfaction. This paper presents a comprehensive review of various load balancing techniques in terms of static and dynamic and the overall performance of these algorithms using some popular performance metrics. Based on the performance measures, Cuckoo Search and Firefly was the most effective algorithm. This research makes a contribution by describing current methodologies and by helping researchers identify research issues connected to load balancing, to decrease response times and prevent server failures.

Keywords: Algorithms, Cloud computing, Load balancing, Performance metrics, Resource management, Virtual machine.

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