A DQN-Based Joint Computing Offloading and Resource Allocation Algorithm for MEC Networks

• Published in: IEEE International Conference on Communications (2003) pp. 2553 - 2558
• Main Authors: Yu, Li, Jiang, Shurui, Zheng, Jun, Yan, Feng, Zhao, Shuyuan
• Format: Conference Proceeding
• Language: English
• Published: IEEE 28.05.2023
• Subjects: Benchmark testing; computing offloading; Delays; DQN; Dynamic scheduling; Heuristic algorithms; MEC; MEC network; resource allocation; Resource management; Simulation; Throughput
• ISSN: 1938-1883
• DOI: 10.1109/ICC45041.2023.10279106

This paper studies the joint computing offloading and resource allocation problem in an MEC network. We formulate the problem as an optimization problem with the objective to maximize the network throughput while satisfying the delay requirements of as many service requests as possible. Meanwhile, we propose a deep-Q-network (DQN) based joint computing offloading and resource allocation (D-CORAL) algorithm to solve the formulated problem. The proposed D-CORAL algorithm attempts to jointly optimize edge node selection, and spectrum resource and computing resource allocation for each service request by learning online to better adapt to a dynamic environment. Simulation results show the proposed algorithm can achieve larger network throughput than two benchmark algorithms.