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Hybrid Architecture for Autonomous Load Balancing in Distributed Systems Based on Smooth Fuzzy Function

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Department of Aerospace and Software Engineering (Informatics), Gyeongsang National University, Jinju, South Korea

* Corresponding Author: Susmit Bagchi, email

Intelligent Automation & Soft Computing 2018, 24(4), . https://doi.org/10.31209/2018.100000043

Abstract

Due to the rapid advancements and developments in wide area networks and powerful computational resources, the load balancing mechanisms in distributed systems have gained pervasive applications covering wired as well as mobile distributed systems. In large-scale distributed systems, sharing of distributed resources is required for enhancing overall resource utilization. This paper presents a comprehensive study and detailed comparative analysis of different load balancing algorithms employing fuzzy logic and mobile agents. We have proposed a hybrid architecture for integrated load balancing and monitoring in distributed computing systems employing fuzzy logic and autonomous mobile agents. Furthermore, we have proposed a smooth and composite fuzzy membership function in order to model fine grained load information in a system. The simulation study and a detailed qualitative as well as quantitative analysis of algorithmic performances are presented. Lastly, a deployment environment is described.

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Cite This Article

APA Style
Ali, M., Bagchi, S. (2018). Hybrid architecture for autonomous load balancing in distributed systems based on smooth fuzzy function. Intelligent Automation & Soft Computing, 24(4). https://doi.org/10.31209/2018.100000043
Vancouver Style
Ali M, Bagchi S. Hybrid architecture for autonomous load balancing in distributed systems based on smooth fuzzy function. Intell Automat Soft Comput . 2018;24(4) https://doi.org/10.31209/2018.100000043
IEEE Style
M. Ali and S. Bagchi, “Hybrid Architecture for Autonomous Load Balancing in Distributed Systems Based on Smooth Fuzzy Function,” Intell. Automat. Soft Comput. , vol. 24, no. 4, 2018. https://doi.org/10.31209/2018.100000043



cc Copyright © 2018 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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