Nitin Thapliyal*

Sr. Faculty IT, Department of CSE, iNurture Education Pvt ltd., India

*Corresponding Author: Nitin Thapliyal, Sr. Faculty IT, Department of CSE, iNurture Education Pvt ltd., India.

Received: June 05, 2023; Published: June 20, 2023

Abstract

A key method for raising the efficiency and scalability of distributed systems is load balancing. In this article, we suggest a novel method for load balancing that makes use of machine learning algorithms to increase the effectiveness of load distribution. Through simulations, we assess our strategy and show how it can speed up throughput and decrease response time. To accomplish effective workload distribution and dynamic resource allocation, our method blends adaptive load balancing algorithms with machine learning approaches. Through comprehensive testing, we assess the efficacy of our strategy and contrast it with other load balancing techniques. The outcomes show that our method is superior in terms of load balancing effectiveness, system scalability, and improvement in overall performance.

Keywords: Load Balancing; Learning Algorithm; Throughput; Simulation; Cloud Computing; Green Computing

References

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Citation

Citation: Nitin Thapliyal. “A New Approach to Load Balancing in Distributed Systems".Acta Scientific Computer Sciences 5.7 (2023): 09-11.

Copyright

Copyright: © 2023 Nitin Thapliyal. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.