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Sustainable Edge Node Computing Deployments in Distributed Manufacturing Systems
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DOI：10.1109/TCE.2023.3328949.png)
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Abstract
En 中文
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.
Keywords:
Edge computing
Smart manufacturing
Computational modeling
Industrial Internet of Things
Manufacturing
Task analysis
Artificial intelligence
Game theory
smart manufacturing
edge node selection
SDN
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10.9
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5.1K
Citations:
6.8K
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