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Title

Multi-Objective Evolutionary Algorithm to Optimize IoT Based Scheduling Problem Using (NSGA-II Algorithm)

  Syed Mutiullah Hussaini 1 * ,   T. Abdul Razzak 2 ,   Muhammad Abid Jamil 3

1  Part-time Research Scholar, Jamal Mohammed College, Baharathidasan University, Trichy, Tamil Nadu State, India
    (smhussaini@gmail.com)

2  Associate Prof. in Computer Science Dept., Jamal Mohammed College, Baharathidasan University, Trichy, Tamil Nadu State, India
    (abdul1964@gmail.com)

3  Affiliation Department of Computer Science, Umm Al Qura University, Makkah, Saudi Arabia
    (majamil@uqu.edu.sa)


Doi   :   https://doi.org/10.54216/JISIoT.120209

Received: August 16, 2023 Revised: November 12, 2023 Accepted: April: 14, 2024

Abstract :

Due to the continual advancements in the Internet of Things (IoT), which generate enormous volumes of data, the cloud computing infrastructure recently has received the most significance. to meet the demands made by the network of IoT devices. It is anticipated that the planned Fog computing system would constitute the next development in cloud computing. The optimal distribution of computing capacity to reduce processing times and operating costs is one of the tasks that fog computing confronts. In the IoT, fog computing is a decentralized computing approach that moves data storage and processing closer to the network's edge. This research article discusses a unique technique for lowering operating expenses and improving work scheduling in a cloud-fog environment. Non-dominated sorting genetic algorithm II (NSGA-II) is a proposal that is presented in this paper. Its purpose is to allocate service requests with the multi-objective of minimising finishing time and running cost. Determining the Pareto front that is associated with a group of perfect solutions, which are sometimes referred to as non-dominated solutions or Pareto sets, is the fundamental objective of the Pareto NSGA-II. There is a contradiction between the environmental and economic performances, which is shown by the Pareto set of sub-optimal solutions that are the consequence of the bi-objective issue.

Keywords :

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Cite this Article as :
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MLA Syed Mutiullah Hussaini, T. Abdul Razzak, Muhammad Abid Jamil. "Multi-Objective Evolutionary Algorithm to Optimize IoT Based Scheduling Problem Using (NSGA-II Algorithm)." Full Length Article, Vol. 12, No. 2, 2024 ,PP. 122-137 (Doi   :  https://doi.org/10.54216/JISIoT.120209)
APA Syed Mutiullah Hussaini, T. Abdul Razzak, Muhammad Abid Jamil. (2024). Multi-Objective Evolutionary Algorithm to Optimize IoT Based Scheduling Problem Using (NSGA-II Algorithm). Journal of Full Length Article, 12 ( 2 ), 122-137 (Doi   :  https://doi.org/10.54216/JISIoT.120209)
Chicago Syed Mutiullah Hussaini, T. Abdul Razzak, Muhammad Abid Jamil. "Multi-Objective Evolutionary Algorithm to Optimize IoT Based Scheduling Problem Using (NSGA-II Algorithm)." Journal of Full Length Article, 12 no. 2 (2024): 122-137 (Doi   :  https://doi.org/10.54216/JISIoT.120209)
Harvard Syed Mutiullah Hussaini, T. Abdul Razzak, Muhammad Abid Jamil. (2024). Multi-Objective Evolutionary Algorithm to Optimize IoT Based Scheduling Problem Using (NSGA-II Algorithm). Journal of Full Length Article, 12 ( 2 ), 122-137 (Doi   :  https://doi.org/10.54216/JISIoT.120209)
Vancouver Syed Mutiullah Hussaini, T. Abdul Razzak, Muhammad Abid Jamil. Multi-Objective Evolutionary Algorithm to Optimize IoT Based Scheduling Problem Using (NSGA-II Algorithm). Journal of Full Length Article, (2024); 12 ( 2 ): 122-137 (Doi   :  https://doi.org/10.54216/JISIoT.120209)
IEEE Syed Mutiullah Hussaini, T. Abdul Razzak, Muhammad Abid Jamil, Multi-Objective Evolutionary Algorithm to Optimize IoT Based Scheduling Problem Using (NSGA-II Algorithm), Journal of Full Length Article, Vol. 12 , No. 2 , (2024) : 122-137 (Doi   :  https://doi.org/10.54216/JISIoT.120209)