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A Resource Allocation Scheme for Edge Computing Network in Smart City Based on Attention Mechanism

Authors: Zhengjie Sun, Hui Yang, Chao Li, Qiuyan Yao, Yun Teng, Jie Zhang, Sheng Liu, Yunbo Li, Athanasios V. VasilakosAuthors Info & Claims

ACM Transactions on Sensor Networks

Accepted on 25 February 2024

https://doi.org/10.1145/3650031

Online AM: 11 March 2024 Publication History

Abstract

In recent years, the number of devices and terminals connected to the smart city has increased significantly. Edge networks face a greater variety of connected objects and massive services. Considering that a large number of services have different QoS requirements, it has always been a huge challenge for smart city to optimally allocate limited computing resources to all services to obtain satisfactory performance. In particular, delay is intolerable for services in certain applications, such as medical, industrial applications, etc, that such applications require the high priority. Therefore, through flexibly dynamic scheduling, it is crucial to schedule services to the optimal node to ensure user experience. In this paper, we propose a resource allocation scheme for hierarchical edge computing network in smart city based on attention mechanism, for extracting a small number of features that can represent services from a large amount of information collected from edge nodes. The attention mechanism is used to quickly determine the priority of the services. Based on this, task deployment and resource allocation for different task priorities are developed to ensure the quality of service in smart cities by introducing Q-learning. Simulation results show that the proposed scheme can effectively improve the edge network resource utilization, reduce the average delay of task processing, and effectively guarantee the quality of service.

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Cited By

Ospina Cifuentes BSuárez ÁGarcía Pineda VAlvarado Jaimes RMontoya Benitez AGrajales Bustamante J(2024)Analysis of the Use of Artificial Intelligence in Software-Defined Intelligent Networks: A SurveyTechnologies10.3390/technologies1207009912:7(99)Online publication date: 2-Jul-2024
https://doi.org/10.3390/technologies12070099
Wang ZYang HLi YYao QYu TZhang CLiu WLin WZhang JLiu YCheriet M(2024)Co-Route Fiber Recognition and Status Diagnosis Based on Integrated Sensing and Communication in 6G Transport NetworksIEEE Internet of Things Journal10.1109/JIOT.2024.341486311:18(29348-29359)Online publication date: 15-Sep-2024
https://doi.org/10.1109/JIOT.2024.3414863
Yu TYang HNie JYao QLiu WZhang JCheriet M(2024)Bias-Compensation Augmentation Learning for Semantic Segmentation in UAV NetworksIEEE Internet of Things Journal10.1109/JIOT.2024.337345411:12(21261-21273)Online publication date: 15-Jun-2024
https://doi.org/10.1109/JIOT.2024.3373454

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A Resource Allocation Scheme for Edge Computing Network in Smart City Based on Attention Mechanism

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cover image ACM Transactions on Sensor Networks

ACM Transactions on Sensor Networks Just Accepted

EISSN:1550-4867

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Association for Computing Machinery

New York, NY, United States

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ACM Journals for the Design of Smart and Connected Systems

Publication History

Online AM: 11 March 2024

Accepted: 25 February 2024

Revised: 27 December 2023

Received: 23 November 2022

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Cited By

Ospina Cifuentes BSuárez ÁGarcía Pineda VAlvarado Jaimes RMontoya Benitez AGrajales Bustamante J(2024)Analysis of the Use of Artificial Intelligence in Software-Defined Intelligent Networks: A SurveyTechnologies10.3390/technologies1207009912:7(99)Online publication date: 2-Jul-2024
https://doi.org/10.3390/technologies12070099
Wang ZYang HLi YYao QYu TZhang CLiu WLin WZhang JLiu YCheriet M(2024)Co-Route Fiber Recognition and Status Diagnosis Based on Integrated Sensing and Communication in 6G Transport NetworksIEEE Internet of Things Journal10.1109/JIOT.2024.341486311:18(29348-29359)Online publication date: 15-Sep-2024
https://doi.org/10.1109/JIOT.2024.3414863
Yu TYang HNie JYao QLiu WZhang JCheriet M(2024)Bias-Compensation Augmentation Learning for Semantic Segmentation in UAV NetworksIEEE Internet of Things Journal10.1109/JIOT.2024.337345411:12(21261-21273)Online publication date: 15-Jun-2024
https://doi.org/10.1109/JIOT.2024.3373454

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