Digital Twin Assisted Computation Offloading and Service Caching in Mobile Edge Computing

Zhenyu Zhang, Huan Zhouand, Liang Zhao, Victor C. M. Leung
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引用次数: 1

Abstract

This paper considers the joint optimization of computation offloading, service caching, and resource allocation in the Digital Twin Edge Network (DTEN), and formulates the problem as Mixed-Integer Non-Linear Programming (MINLP), whose goal is to minimize the long-term energy consumption of the system. To solve the optimization problem, a Deep Deterministic Policy Gradient (DDPG) based algorithm is proposed for determining the strategies of computation offloading, service caching, and resource allocation. Simulation results demonstrate that the proposed DDPG based algorithm can reduce the long-term energy consumption of the system greatly, and outperform other benchmark algorithms under different scenarios.
移动边缘计算中的数字孪生辅助计算卸载和服务缓存
本文考虑了数字双边缘网络(DTEN)中计算卸载、服务缓存和资源分配的联合优化问题,并将其表述为以系统长期能耗最小为目标的混合整数非线性规划(MINLP)问题。为了解决该优化问题,提出了一种基于深度确定性策略梯度(Deep Deterministic Policy Gradient, DDPG)的算法来确定计算卸载、服务缓存和资源分配策略。仿真结果表明,所提出的基于DDPG的算法可以大大降低系统的长期能耗,并且在不同场景下优于其他基准算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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