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IoT 24(1):

Editorial

Dynamic Load Balancing in Cloud Computing: A Review and a Novel Approach

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  • @ARTICLE{10.4108/eetiot.5387,
        author={Jasobanta Laha and Sabyasachi Pattnaik and Kumar Surjeet Chaudhury},
        title={Dynamic Load Balancing in Cloud Computing: A Review and a Novel Approach},
        journal={EAI Endorsed Transactions on Internet of Things},
        volume={10},
        number={1},
        publisher={EAI},
        journal_a={IOT},
        year={2024},
        month={3},
        keywords={Cloud computing, Load balancing, Responsive time, execution time, system stability},
        doi={10.4108/eetiot.5387}
    }
    
  • Jasobanta Laha
    Sabyasachi Pattnaik
    Kumar Surjeet Chaudhury
    Year: 2024
    Dynamic Load Balancing in Cloud Computing: A Review and a Novel Approach
    IOT
    EAI
    DOI: 10.4108/eetiot.5387
Jasobanta Laha1,*, Sabyasachi Pattnaik1, Kumar Surjeet Chaudhury2
  • 1: Fakir Mohan University
  • 2: KIIT University
*Contact email: yeshmcp@gmail.com

Abstract

In cloud computing, load balancing is essential since it guarantees effective resource utilisation and reduces response times. It effectively distributes incoming workload across available servers. Load balancing involves dividing tasks among multiple systems or resources over the internet. By distributing traffic and workloads, load balancing ensures that no server or computer is overloaded, underutilized, or idle in a cloud computing environment. To enhance overall performance in the cloud, it optimises a number of variables, including execution time, response time, and system stability. To increase the effectiveness and reliability of cloud services, load balancing evenly distributes traffic, workloads, and computing resources across the environment. The proposed method, Enhanced Dynamic Load Balancing for Cloud Computing, adjusts load distribution and maintains a balanced system by considering variables like server capacity, workload distribution, and system load. By incorporating these factors and employing adaptive threshold adjustment, this approach optimizes resource allocation and enhances system performance. Experimental research shows that the proposed new novel approach is more effective and efficient than current load balancing techniques. In this context of cloud computing, this ground-breaking method offers a workable substitute for dynamic load balancing.

Keywords
Cloud computing, Load balancing, Responsive time, execution time, system stability
Received
2023-12-17
Accepted
2024-03-07
Published
2024-03-12
Publisher
EAI
http://dx.doi.org/10.4108/eetiot.5387

Copyright © 2024 J. Lata et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.

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