Dynamic resource allocation scheme for mobile edge computing

Mobile edge computing is a promising paradigm that provides edge users with dependable computing services. However, due to the dynamic nature of mobile users and the limited resources of edge servers, it is essential to emphasize the load balancing of edge servers and the cooperation of heterogeneous computing resources. This paper proposes a Dynamic Resource Allocation (DRA) scheme based on a Quantum Approximate Optimization Algorithm (QAOA). The DRA is composed of the two components listed below. Firstly, we apply generative adversarial network to predict the future user density in various regions, which is an effective resource allocation aid. Secondly, QAOA is utilized to pre-allocate edge servers resources based on an advanced model of user density. The simulation results demonstrate that the efficient application of DRA ensures the load balancing of edge servers and simultaneously alleviates communication latency.