Deployment of Edge Computing Nodes in IoT: Effective Implementation of Simulated Annealing Method Based on User Location

Junhui Zhao; Ziyang Zhang; Zhenghao Yi; Xiaoting Ma; Qingmiao Zhang

doi:10.23919/JCC.fa.2021-0034.202401

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Deployment of Edge Computing Nodes in IoT: Effective Implementation of Simulated Annealing Method Based on User Location

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- Deployment of Edge Computing Nodes in IoT: Effective Implementation of Simulated Annealing Method Based on User Location
- Deployment of Edge Computing Nodes in IoT: Effective Implementation of Simulated Annealing Method Based on User Location
- 中国通信（英文版） 2024年21卷第1期页码：279-296
- 作者机构：
  
  1. 1School of Electronic and Information Engineering, Beijing Jiaotong University,Beijing,China,100044
  2. 2School of Information Engineering, East China Jiaotong University,Nanchang,China,330013
- 作者简介：
- 基金信息：
- DOI：10.23919/JCC.fa.2021-0034.202401
  中图分类号：
- 网络首发：2024-02-21，
  
  纸质出版：2024
- 稿件说明：
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Junhui Zhao, Ziyang Zhang, Zhenghao Yi, Xiaoting Ma, Qingmiao Zhang. Deployment of Edge Computing Nodes in IoT: Effective Implementation of Simulated Annealing Method Based on User Location. China Communications. 2024, 21(1): 279-296 https://doi.

org/10.23919/JCC.fa.2021-0034.202401
Junhui Zhao, Ziyang Zhang, Zhenghao Yi, Xiaoting Ma, Qingmiao Zhang. Deployment of Edge Computing Nodes in IoT: Effective Implementation of Simulated Annealing Method Based on User Location. China Communications. 2024, 21(1): 279-296 https://doi. DOI： 10.23919/JCC.fa.2021-0034.202401.

org/10.23919/JCC.fa.2021-0034.202401 DOI：

摘要

Abstract

Edge computing paradigm for 5G architecture has been considered as one of the most effective ways to realize low latency and highly reliable communication

which brings computing tasks and network resources to the edge of network. The deployment of edge computing nodes is a key factor affecting the service performance of edge computing systems. In this paper

we propose a method for deploying edge computing nodes based on user location. Through the combination of Simulation of Urban Mobility (SUMO) and Network Simulator-3 (NS-3)

a simulation platform is built to generate data of hotspot areas in IoT scenario. By effectively using the data generated by the communication between users in IoT scenario

the location area of the user terminal can be obtained. On this basis

the deployment problem is expressed as a mixed integer linear problem

which can be solved by Simulated Annealing (SA) method. The analysis of the results shows that

compared with the traditional method

the proposed method has faster convergence speed and better performance.

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关联资源

Multi-Agent Reinforcement Learning for Resource Allocation in IoT Networks with Edge Computing

When Edge Computing Meets IoT Systems: Analysis of Case Studies

The Way to Apply Machine Learning to IoT Driven Wireless Network from Channel Perspective

Multi-Receiver Signcryption Scheme with Multiple Key Generation Centers through Public Channel in Edge Computing

Analysis and Optimization of the Status Update Performance in Massive MIMO-Enabled IoT Systems

相关机构

1 Department of Electronic Engineering and Computer Science, Queen Mary University of London, London E1 4NS, U.K

2 Beijing University of Posts and Telecommunications

3 Peng Cheng Laboratory and also with the University of Surrey, ,.K

Faculty of Engineering and Architecture, Kore University of Enna, Cittadella Universitaria, Enna

1 Northwestern Polytechnical University

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