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

作     者：Junhui Zhao Ziyang Zhang Zhenghao Yi Xiaoting Ma Qingmiao Zhang Junhui Zhao;Ziyang Zhang;Zhenghao Yi;Xiaoting Ma;Qingmiao Zhang

作者机构：School of Electronic and Information EngineeringBeijing Jiaotong UniversityBeijing 100044China School of Information EngineeringEast China Jiaotong UniversityNanchang 330013China 

出 版 物：《China Communications》 (中国通信（英文版）)

年 卷 期：2024年第21卷第1期

页      面：279-296页

核心收录：

学科分类：0810[工学-信息与通信工程] 08[工学] 0804[工学-仪器科学与技术] 080402[工学-测试计量技术及仪器] 

基　　金：supported in part by the Beijing Natural Science Foundation under Grant L201011 in part by the National Natural Science Foundation of China(U2001213 and 61971191) in part by National Key Research and Development Project(2020YFB1807204)。 

主　　题：deployment problem edge computing internet of things machine learning 

摘      要：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 Io T scenario.By effectively using the data generated by the communication between users in Io T 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.