IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

An Ant-Colony-Based Meta-Heuristic Approach for Load Balancing in Cloud Computing

An Ant-Colony-Based Meta-Heuristic Approach for Load Balancing in Cloud Computing
View Sample PDF
Author(s): Santanu Dam (Future Institute of Engineering and Management, India), Gopa Mandal (Kalyani Government Engineering College, India), Kousik Dasgupta (Kalyani Government Engineering College, India)and Parmartha Dutta (Visva-Bharati University, India)
Copyright: 2021
Pages: 31
Source title: Research Anthology on Architectures, Frameworks, and Integration Strategies for Distributed and Cloud Computing
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-7998-5339-8.ch041

Purchase

View An Ant-Colony-Based Meta-Heuristic Approach for Load Balancing in Cloud Computing on the publisher's website for pricing and purchasing information.

Abstract

This book chapter proposes use of Ant Colony Optimization (ACO), a novel computational intelligence technique for balancing loads of virtual machine in cloud computing. Computational intelligence(CI), includes study of designing bio-inspired artificial agents for finding out probable optimal solution. So the central goal of CI can be said as, basic understanding of the principal, which helps to mimic intelligent behavior from the nature for artifact systems. Basic strands of ACO is to design an intelligent multi-agent systems imputed by the collective behavior of ants. From the perspective of operation research, it's a meta-heuristic. Cloud computing is a one of the emerging technology. It's enables applications to run on virtualized resources over the distributed environment. Despite these still some problems need to be take care, which includes load balancing. The proposed algorithm tries to balance loads and optimize the response time by distributing dynamic workload in to the entire system evenly.

Related Content

Sushruta Mishra, Sunil Kumar Mohapatra, Brojo Kishore Mishra, Soumya Sahoo. © 2021. 24 pages.
Carlos Santos, Helena InĂ¡cio, Rui Pedro Marques. © 2021. 16 pages.
Akash Chowdhury, Swastik Mukherjee, Sourav Banerjee. © 2021. 26 pages.
Stojan Kitanov, Toni Janevski. © 2021. 28 pages.
Ramesh C. Poonia, Linesh Raja. © 2021. 27 pages.
Jens Kohler, Thomas Specht. © 2021. 27 pages.
Jagdish Chandra Patni. © 2021. 15 pages.
Body Bottom