A Study on Resource Allocation for Mobile Edge Computing-Assisted Industrial Iot

Since the advancement of mobile communication technology, traditional industries are gradually transforming and upgrading, which leads to problems such as insufficient computing resources and excessive energy consumption of Internet of Things (IoT) devices. To address this issue, a resource allocati...

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Bibliographic Details
Published in2023 International Conference on Networks, Communications and Intelligent Computing (NCIC) pp. 176 - 182
Main Authors Lu, Jie, Zhang, Yuexia, Li, Junjie
Format Conference Proceeding
LanguageEnglish
Published IEEE 17.11.2023
Subjects
Additional Keywords and Phrases
Cloud computing
Computational modeling
Convex functions
Costs
data processing
Energy consumption
Industrial internet of things
mobile edge computing
mobile network
modified ADMM
resource allocation
Resource management
Servers
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Summary:Since the advancement of mobile communication technology, traditional industries are gradually transforming and upgrading, which leads to problems such as insufficient computing resources and excessive energy consumption of Internet of Things (IoT) devices. To address this issue, a resource allocation algorithm for the mobile edge computing-assisted industrial IoT (IIoT) is proposed. First, a mobile edge computing-assisted IIoT network model was constructed. Using the collaboration between IoT devices, mobile edge computing (MEC) servers, and cloud servers, the issue of minimizing all IIoT devices energy cost was proposed. Subsequently, in order to address the optimization issue, obtain its optimal solution, the alternating direction method of multipliers (ADMM) algorithm is introduced. Finally, the ADMM algorithm's convergence was verified through an experimental simulation. In contrast to baseline algorithm 1 and algorithm 2, the ADMM algorithm can significantly diminish energy cost, proving the effectiveness of the proposed scheme.
DOI:10.1109/NCIC61838.2023.00035