Levy Flight Adopted Particle Swarm Optimization-based Resource Allocation Strategy in Fog Computing

Sharmila Patil(Karpe); Brahmananda S H

doi:10.23919/cje.2022.00.212

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Article Navigation > Chinese Journal of Electronics > 2023 > Accepted Manuscript

Sharmila Patil(Karpe) and Brahmananda S H, “Levy Flight Adopted Particle Swarm Optimization-based Resource Allocation Strategy in Fog Computing,” Chinese Journal of Electronics, in press, doi: 10.23919/cje.2022.00.212, 2023.

Citation:

Sharmila Patil(Karpe) and Brahmananda S H, “Levy Flight Adopted Particle Swarm Optimization-based Resource Allocation Strategy in Fog Computing,” Chinese Journal of Electronics, in press, doi: 10.23919/cje.2022.00.212, 2023.

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Levy Flight Adopted Particle Swarm Optimization-based Resource Allocation Strategy in Fog Computing

doi: 10.23919/cje.2022.00.212

Sharmila Patil(Karpe)¹,
Brahmananda S H^{1, 2}

1.
Research scholar Department of Computer Science and Engineering GITAM School of Technology, (GITAM deemed university), Bengaluru, India
2.
Professor Department of Computer Science and Engineering GITAM, Bengaluru, India

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Author Bio:
Sharmila Patil(Karpe) is a research Scholar, pursuing PhD at Department of Computer Science & Engineering, GITAM University, Gitam School of Technology, Bangalore Campus. She has been working on Fog and Cloud computing resource allocation. She is working as an Assistant Professor at Information Technology Department, Walchand Institute of Technology, Solapur, Maharashtra, India. Her research areas of interest include Internet of Things, computer network and Sustainability

Brahmananda S H is a Professor at Department of Computer Science & Engineering, GITAM University, Gitam School of Technology, Bangalore Campus, Karnataka, India. has over eighteen years of Post Graduate teaching and research experience. He holds a Ph.D. from Dr. M.G.R. Educational & Research Institute, University, Chennai. His research areas of interest include - Wireless sensor networks security, System Analysis & Computer Applications, and Teaching-Learning process. He has over 40 research papers in national and international journals of repute. He is reviewer and editorial board member of several journals indexed in Scopus and SCI
Received Date: 2022-07-12
Accepted Date: 2022-10-31

Available Online: 2023-01-14

Abstract

Abstract

The prevalence of the Internet of Things (IoT) is unsteady in the context of cloud computing, it is difficult to identify fog and cloud resource scheduling policies that will satisfy users’ QoS need. As a result, it increases the efficiency of resource usage and boosts user and resource supplier profit. This research intends to introduce a novel strategy for computing fog via emergency-oriented resource allotment, which aims and determines the effective process under different parameters. The modeling of a non-linear functionality that is subjected to an objective function and incorporates needs or factors like Service response rate, Execution efficiency, and Reboot rate allows for the resource allocation of cloud to fog computing in this work. Apart from this, the proposed system considers the resource allocation in emergency priority situations that must cope-up with the immediate resource allocation as well. Security in resource allocation is also taken into consideration with this strategy. Thus the multi-objective function considers 3 objectives such as Service response rate, Execution efficiency, and Reboot rate. All these strategies in resource allocation are fulfilled by Levy Flight adopted Particle Swarm Optimization (LF-PSO). Finally, the evaluation is performed to determine whether the developed strategy is superior to numerous traditional schemes. However, the cost function attained by the adopted technique is 120, which is 19.17%, 5%, and 2.5% greater than the conventional schemes like GWSO, EHO, and PSO, when the number of iterations is 50.
- Fog computing,
- Allocation strategy,
- Execution efficiency,
- Reboot rate,
- LF-PSO Optimization

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References(41)

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