Quick and Good:A DRL Based Communication-Caching-Energy Joint Optimization Scheme for Prolonging the Lifetime of UAV Assisted IoE  

作　　者：Chun Zhu Guilong Zhu Jie Yang Miao Liu Zheng Shi 

机构地区：[1]School of Communications and Information Engineering,Nanjing University of Posts and Telecommunications,Nanjing 210003,China

出　　处：《Journal of Communications and Information Networks》2024年第4期348-361,共14页通信与信息网络学报(英文)

基　　金：supported by the National Key Research and Development Program of China under Grant 2021ZD0113003;the National Natural Science Foundation of China under Grant 92367302.

摘　　要：The rapid increase in the number of Internet of things(IoT)devices has led to significant access pressure,making network energy consumption and communication load key challenges.Edge caching,cooperative communication,and energy management technologies have proven to be effective in alleviating these issues.This paper investigates a unmanned aerial vehicle(UAV)-assisted Internet of everything(IoE)architecture that integrates caching,communication,and energy management.A collaborative communicationcaching-energy optimization scheme is proposed,which involves the joint operation of the UAV and base station(BS)to pre-cache content required by ground users,thus minimizing system energy consumption.We model the joint optimization of content caching,communication,and energy consumption as a Markov decision process(MDP),transforming it into a long-term optimization problem solvable by deep reinforcement learning.Based on the simple deep Q-network(DQN),we design a dynamic content placement strategy that jointly optimizes communication,caching,and energy consumption.Simulation results demonstrate that the proposed method,compared to branch and bound(B&B),particle swarm optimization(PSO),genetic algorithm(GA),and random algorithms,not only approaches the optimal solution most closely,effectively reducing system energy consumption,but also exhibits the lowest time complexity.

关 键 词：wireless caching energy sustainable UAV-assisted network communication-caching-energy integration deep reinforcement learning(DRL) 

分 类 号：TN929.5[电子电信—通信与信息系统]