In digital twin-enabled Mobile Edge Computing(MEC)networks,how to realize the efficient deployment of digital twin servers is the bottleneck problem to ensure the real-time interactivity of digital twin.To address this problem,an adaptive joint deployment optimization mechanism of digital twin servers for dynamic edge networks is proposed.First,the mechanism constructs a two-tier digital twin model for dynamic edge networks to capture features such as MEC network status and UE(user equipment)resource utilization in real-time.Secondly,the digital twin server adaptive dynamic update deployment problem is established by jointly using the digital twin interaction latency model,the load balancing model,and the energy consumption model.Finally,a multi-stage adaptive joint deployment optimization algorithm is proposed to decompose the digital twin server adaptive dynamic update deployment problem into two stages for optimization and solution,including initial deployment for the digital twin server and the adaptive dynamic update deployment for the digital twin server.Thus,the adaptive dynamic adjustment of the deployment policies with the immediate system status of the MEC networks is established.Simulation analysis verifies the effectiveness of the proposed multi-stage adaptive joint deployment optimization algorithm in terms of prediction accuracy,interaction latency,workload,and energy consumption.
关键词
数字孪生网络/服务器部署/多目标优化/动态边缘网络/物联网系统
Key words
digital twin networks/server deployment/multi-objective optimization/dynamic edge networks/IoT systems
维普
万方数据