Energy Efficient Computation Offloading in Aerial Edge Networks With Multi-Agent Cooperation

Abstract

With the high flexibility of supporting resource-intensive and time-sensitive applications, unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) is proposed as an innovational paradigm to support the mobile users (MUs). As a promising technology, digital twin (DT) is capable of timely mapping the physical entities to virtual models, and reflecting the MEC network state in real-time. In this paper, we first propose an MEC network with multiple movable UAVs and one DT-empowered ground base station to enhance the MEC service for MUs. Considering the limited energy resource of both MUs and UAVs, we formulate an online problem of resource scheduling to minimize the weighted energy consumption of them. To tackle the difficulty of the combinational problem, we formulate it as a Markov decision process (MDP) with multiple types of agents. Since the proposed MDP has huge state space and action space, we propose a deep reinforcement learning approach based on multi-agent proximal policy optimization (MAPPO) with Beta distribution and attention mechanism to pursue the optimal computation offloading policy. Numerical results show that our proposed scheme is able to efficiently reduce the energy consumption and outperforms the benchmarks in performance, convergence speed and utilization of resources.

arXiv comment14 pages, 13 figures

References in corpus (5)

• 6G Internet of Things: A Comprehensive Survey
• UAV Communications for 5G and Beyond: Recent Advances and Future Trends
• The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Games
• Low-latency Federated Learning and Blockchain for Edge Association in Digital Twin empowered 6G Networks
• Digital Twin Assisted Task Offloading for Aerial Edge Computing and Networks

Cited by in corpus (4)

• Robust Computation Offloading and Trajectory Optimization for Multi-UAV-Assisted MEC: A Multi-Agent DRL Approach
• Digital Twin-Empowered Task Assignment in Aerial MEC Network: A Resource Coalition Cooperation Approach with Generative Model
• Delay-Aware Digital Twin Synchronization in Mobile Edge Networks with Semantic Communications
• Air-to-Ground Communications Beyond 5G: CoMP Handoff Management in UAV Network