Article: A novel optimised GWOAN algorithm for scheduling task and power consumption in MEC network Journal: International Journal of Intelligent Systems Technologies and Applications (IJISTA) 2023 Vol.21 No.4 pp.386 - 401 Abstract: In recent decades, the 5G and internet of things (IoT) are occupied with several applications like face recognition, traffic control, video surveillance and telecommunication, etc. Mobile-edge computing (MEC) is a promising paradigm in wireless communication which is carried by the computational scheduling of mobile devices. To enhance the computation design, the AlexNet of the DL model is applied which is based on the convolutional neural network (CNN) used to train a large number of attributes. To provide an optimal solution, the metaheuristics algorithm of grey wolf optimisation (GWO) is combined with an AlexNet which is named a novel grey wolf optimisation-based AlexNet (GWOAN) algorithm. In the proposed GWOAN algorithm, the AlexNet hyperparameters (weights, biases and other parameters) are fine-tuned by GWO and then performed a classification. As a result, the GWOAN has achieved a higher scheduling task and low latency than the standard AlexNet, ResNet-18 and VGGNet-16 respectively. Inderscience Publishers - linking academia, business and industry through research

Title: A novel optimised GWOAN algorithm for scheduling task and power consumption in MEC network

Authors: P. Sivakumar; Murali Murugan; S.K. Somasundaram; S. Nagendra Prabhu

Addresses: School of Computer Science and Engineering, Vellore Institute of Technology, Chennai – 600127, Tamil Nadu, India ' Engineering Retail Business Professional, Georgia, USA ' School of Computer Science and Engineering, Vellore Institute of Technology, Vellore – 632014, Tamil Nadu, India ' Department of Computational Intelligence, SRM Institute of Science and Technology, Chennai – 632014, Tamil Nadu, India

Abstract: In recent decades, the 5G and internet of things (IoT) are occupied with several applications like face recognition, traffic control, video surveillance and telecommunication, etc. Mobile-edge computing (MEC) is a promising paradigm in wireless communication which is carried by the computational scheduling of mobile devices. To enhance the computation design, the AlexNet of the DL model is applied which is based on the convolutional neural network (CNN) used to train a large number of attributes. To provide an optimal solution, the metaheuristics algorithm of grey wolf optimisation (GWO) is combined with an AlexNet which is named a novel grey wolf optimisation-based AlexNet (GWOAN) algorithm. In the proposed GWOAN algorithm, the AlexNet hyperparameters (weights, biases and other parameters) are fine-tuned by GWO and then performed a classification. As a result, the GWOAN has achieved a higher scheduling task and low latency than the standard AlexNet, ResNet-18 and VGGNet-16 respectively.

Keywords: mobile-edge computing; MEC; AlexNet hyperparameter; fine-tuning; scheduling task decision; power control; latency.

DOI: 10.1504/IJISTA.2023.134989

International Journal of Intelligent Systems Technologies and Applications, 2023 Vol.21 No.4, pp.386 - 401

Received: 16 Feb 2022
Accepted: 06 Jan 2023
Published online: 23 Nov 2023 *

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Title: A novel optimised GWOAN algorithm for scheduling task and power consumption in MEC network

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