典型文献
Joint Optimization of Latency and Energy Consumption for Mobile Edge Computing Based Proximity Detection in Road Networks
文献摘要：
In recent years,artificial intelligence and automotive industry have developed rapidly,and au-tonomous driving has gradually become the focus of the industry.In road networks,the problem of prox-imity detection refers to detecting whether two mov-ing objects are close to each other or not in real time.However,the battery life and computing capa-bility of mobile devices are limited in the actual scene,which results in high latency and energy consump-tion.Therefore,it is a tough problem to determine the proximity relationship between mobile users with low latency and energy consumption.In this article,we aim at finding a tradeoff between latency and energy consumption.We formalize the computation offload-ing problem base on mobile edge computing(MEC)into a constrained multiobjective optimization prob-lem(CMOP)and utilize NSGA-Ⅱ to solve it.The simulation results demonstrate that NSGA-Ⅱ can find the Pareto set,which reduces the latency and energy consumption effectively.In addition,a large number of solutions provided by the Pareto set give us more choices of the offloading decision according to the ac-tual situation.
文献关键词：
中图分类号：
作者姓名：
Tongyu Zhao;Yaqiong Liu;Guochu Shou;Xinwei Yao
作者机构：
School of Information and Communication Engineering,Beijing University of Posts and Telecommunications,Beijing 100876,China;Beijing Laboratory of Advanced Information Networks,Beijing Key Laboratory of Network System Architecture and Convergence,Beijing 100876,China;School of Computer Science and Technology,Zhejiang University of Technology,China
文献出处：
引用格式：
[1]Tongyu Zhao;Yaqiong Liu;Guochu Shou;Xinwei Yao-.Joint Optimization of Latency and Energy Consumption for Mobile Edge Computing Based Proximity Detection in Road Networks)[J].中国通信（英文版）,2022(04):274-290
A类：
tonomous,mov,formalize,CMOP
B类：
Joint,Optimization,Latency,Energy,Consumption,Mobile,Edge,Computing,Based,Proximity,Detection,Road,Networks,In,recent,years,artificial,intelligence,automotive,industry,have,developed,rapidly,driving,has,gradually,become,focus,road,networks,problem,detection,refers,detecting,whether,objects,close,each,other,not,real,However,battery,life,computing,capa,bility,mobile,devices,limited,actual,scene,which,results,high,latency,energy,Therefore,tough,determine,proximity,relationship,between,users,low,consumption,this,article,aim,finding,tradeoff,We,computation,base,edge,MEC,into,constrained,multiobjective,optimization,utilize,NSGA,solve,simulation,demonstrate,that,can,Pareto,set,reduces,effectively,addition,large,number,solutions,provided,by,give,more,choices,offloading,decision,according,situation
AB值：
0.586179
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