Developing a Methodology for IOT Load Distribution within Edge Computing

Authors

  • Abdullah Farhan Mahdi University of Diyala Author
  • Aymen Mudheher Badr University of Diyala Author
  • Israa Mishkhal Universiti Sains Malaysia Author

DOI:

https://doi.org/10.69923/yc6c1d53

Keywords:

Internet of Things, Edge computing, Load balancing, Standard deviation variance

Abstract

Optimizing task distribution and resource allocation becomes crucial with the exponential growth of IoT devices and the proliferation of edge computing. On the other hand, building such a flexible model about resources inside a heterogeneous climate is difficult. Also, the increasing demand for IoT services necessitated working to reduce the time delay by accomplishing successful load balancing. The objective of this study is to enhance load balancing by ensuring equitable allocation of resources among workloads, thereby enhancing Quality of Service (QOS) in cloud computing and minimizing processing time (PT), hence decreasing response time (RT). Our methodology presents a decentralized system with multiple agents that utilize the nodes in the edge and the cloud to distribute the workload caused by incoming tasks and the cost of performing those tasks. A collaborative model is followed to allocate the tasks to the resources to increase the utilization of available resources.

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Author Biographies

  • Abdullah Farhan Mahdi, University of Diyala

    He holds a master's degree in 2012 from the University of Anbar, College of Computer Science and Information Technology, specializing in data warehouses. In 2023, he obtained a doctorate from the University of Anbar, College of Computer Science and Information Technology, specializing in artificial intelligence. He is a lecturer at the University of Diyala, College of Agriculture. He can be contacted at email: abdullahmahdi@uodiyala.edu.iq.

  • Aymen Mudheher Badr, University of Diyala

    He obtained a Bachelor of Science in Computer Science in 2001. And an M.S. degree in computer science from Chongqing University, China, in 2015. He has worked as a lecturer at Diyala University since 2003 until now. He holds a PhD in Computer Science - Medical Informatics from Safx University, Digital Research Center of Sfax (CRNS) Laboratory of Signals, Systems, Artificial Intelligence and Networks (SM@RTS), Tunisia, 2024. He can be contacted at email: aymen.m.badr@uodiyala.edu.iq.

  • Israa Mishkhal , Universiti Sains Malaysia

    Israa Mishkhal was born in Iraq, in Baqubah. She obtained a bachelor’s degree in computer science from Diyala University. She holds a master's degree in computer science from Ball State University (BSU) in the United States of America. She is a Ph.D. student at Universiti Sains Malaysia, Computer Science. She is a lecturer at College Science/Diyala University, Iraq (Diyala). She has many research papers in national and international conferences.

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Published

12/30/2024

Issue

Vol. 1 No. 3 (2024)

Section

Articles

License

Copyright (c) 2024 Iraqi Journal for Applied Science

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References

Marshall,G.C.and H.W.Ohm 1987 .Yield responses of 16 winter wheat cultivars to row spacing and seeding rate .Agronomy Journal .79:1027-1030

How to Cite

[1]
A. . Farhan Mahdi, A. . Mudheher Badr, and I. . Mishkhal, “Developing a Methodology for IOT Load Distribution within Edge Computing”, IJApSc, vol. 1, no. 3, pp. 62–70, Dec. 2024, doi: 10.69923/yc6c1d53.