Sustainable Edge Node Computing Deployments in Distributed Manufacturing Systems

被引:4
作者
Goudarzi, Shidrokh [1 ]
Soleymani, Seyed Ahmad [2 ]
Anisi, Mohammad Hossein [3 ]
Jindal, Anish [4 ]
Dinmohammadi, Fateme [5 ]
Xiao, Pei [5 ]
机构
[1] Univ West London, Sch Comp & Engn, London W5 5RF, England
[2] Univ Surrey, Ctr Vis Speech & Signal Proc, Guildford GU2 7XH, England
[3] Univ Essex, Sch Comp Sci & Elect Engn, Colchester CO4 3SQ, England
[4] Univ Durham, Dept Comp Sci, Durham DH1 3LE, England
[5] Univ Surrey, Inst Commun Syst, 5G&6G Innovat Ctr, Guildford GU2 7XH, England
基金
英国工程与自然科学研究理事会;
关键词
Edge computing; Smart manufacturing; Computational modeling; Industrial Internet of Things; Manufacturing; Task analysis; Artificial intelligence; Game theory; smart manufacturing; edge node selection; SDN; INDUSTRIAL INTERNET; DECISION-MAKING; THINGS; SELECTION;
D O I
10.1109/TCE.2023.3328949
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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.
引用
收藏
页码:1471 / 1481
页数:11
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