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Sustainable Edge Node Computing Deployments in Distributed Manufacturing Systems

Goudarzi, S.; Soleymani, S. A.; Anisi, M. H.; Jindal, A.; Dinmohammadi, F.; Xiao, Pei

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Authors

S. Goudarzi

S. A. Soleymani

M. H. Anisi

F. Dinmohammadi

Pei Xiao



Abstract

The advancement of mobile internet technology has created opportunities for integrating the Industrial Internet of Things (IIoT) and edge computing in smart manufacturing. These sustainable technologies enable intelligent devices to achieve high-performance computing with minimal latency. This paper introduces a novel approach to deploy edge computing nodes in smart manufacturing environments at a low cost. However, the intricate interactions among network sensors, equipment, service levels, and network topologies in smart manufacturing systems pose challenges to node deployment. To address this, the proposed sustainable game theory method identifies the optimal edge computing node for deployment to attain the desired outcome. Additionally, the standard design of Software Defined Network (SDN) in conjunction with edge computing serves as forwarding switches to enhance overall computing services. Simulations demonstrate the effectiveness of this approach in reducing network delay and deployment costs associated with computing resources. Given the significance of sustainability, cost efficiency plays a critical role in establishing resilient edge networks. Our numerical and simulation results validate that the proposed scheme surpasses existing techniques like shortest estimated latency first (SELF), shortest estimated buffer first (SEBF), and random deployment (RD) in minimizing the total cost of deploying edge nodes, network delay, packet loss, and energy consumption.

Citation

Goudarzi, S., Soleymani, S. A., Anisi, M. H., Jindal, A., Dinmohammadi, F., & Xiao, P. (2023). Sustainable Edge Node Computing Deployments in Distributed Manufacturing Systems. IEEE Transactions on Consumer Electronics, https://doi.org/10.1109/tce.2023.3328949

Journal Article Type Article
Acceptance Date Oct 16, 2023
Online Publication Date Oct 31, 2023
Publication Date 2023
Deposit Date Nov 25, 2023
Publicly Available Date Nov 27, 2023
Journal IEEE Transactions on Consumer Electronics
Print ISSN 0098-3063
Electronic ISSN 1558-4127
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
DOI https://doi.org/10.1109/tce.2023.3328949
Public URL https://durham-repository.worktribe.com/output/1952140

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