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IoT 24(1):

Editorial

DPSO: A Hybrid Approach for Load Balancing using Dragonfly and PSO Algorithm in Cloud Computing Environment

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  • @ARTICLE{10.4108/eetiot.4826,
        author={Subasish Mohapatra and Subhadarshini Mohanty and Hriteek Kumar Nayak and Millan Kumar Mallick and Janjhyam Venkata Naga Ramesh and Khasim Vali Dudekula},
        title={DPSO: A Hybrid Approach for Load Balancing using Dragonfly and PSO Algorithm in Cloud Computing Environment},
        journal={EAI Endorsed Transactions on Internet of Things},
        volume={10},
        number={1},
        publisher={EAI},
        journal_a={IOT},
        year={2024},
        month={1},
        keywords={Resource allocation, Load Balancing, Cloud Computing, Dragonfly Algorithm, PSO, Hybrid model},
        doi={10.4108/eetiot.4826}
    }
    
  • Subasish Mohapatra
    Subhadarshini Mohanty
    Hriteek Kumar Nayak
    Millan Kumar Mallick
    Janjhyam Venkata Naga Ramesh
    Khasim Vali Dudekula
    Year: 2024
    DPSO: A Hybrid Approach for Load Balancing using Dragonfly and PSO Algorithm in Cloud Computing Environment
    IOT
    EAI
    DOI: 10.4108/eetiot.4826
Subasish Mohapatra1,*, Subhadarshini Mohanty1, Hriteek Kumar Nayak1, Millan Kumar Mallick1, Janjhyam Venkata Naga Ramesh2, Khasim Vali Dudekula3
  • 1: Odisha University of Technology and Research
  • 2: Koneru Lakshmaiah Education Foundation
  • 3: Vellore Institute of Technology University
*Contact email: smohapatra@outr.ac.in

Abstract

Load balancing is one of the promising challenges in cloud computing system. For solving the issues, many heuristic, meta heuristic, evolutionary and hybrid algorithms have been proposed by the researchers. Still, it is under way of research for finding optimal solution in dynamic change in behaviour of task as well as computing environments. Attempts have been made to develop a hybrid framework to balance the load in cloud environment by obtain the best fitness value. To achieve an optimal resource for load balancing, the proposed framework integrates Dragonfly (DF) and Particle Swarm Optimization (PSO) algorithm. The performance of the proposed method is compared with PSO and Dragonfly algorithm. The performance is evaluated in different measures such as best fitness value, response time by varying the user base and response time. The user bases are varied from 50, 100, 500, and 1000. Similarly, the population size has been varied to observe the performance of the algorithm. It is observed that the proposed method outperforms the other approached for load balancing. The statistical analysis and standard testing also validate the relative superiority of PSO a considerable Dragonfly Algorithm. The hybrid approach provides better response time.

Keywords
Resource allocation, Load Balancing, Cloud Computing, Dragonfly Algorithm, PSO, Hybrid model
Received
2023-10-21
Accepted
2024-01-03
Published
2024-01-11
Publisher
EAI
http://dx.doi.org/10.4108/eetiot.4826

Copyright © 2024 S. Mohapatra 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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