Throughput Maximization for Multiedge Multiuser Edge Computing Systems

The multiaccess edge computing/mobile-edge computing (MEC) is becoming a key technology toward 'full 5G.' However, as it gets widely used, a fundamental problem is how to support as many service requests as possible under stringent Quality-of-Service (QoS) requirements and limited communications and computing resources. In this article, we study the long-term throughput maximization problem for multicell multiuser MEC systems. Different from most of the existing works that focus on energy or latency minimization problem for a single-edge system, a novel design is proposed from the service provider's perspective to maximize the system-wide throughput under latency bounds by jointly taking user association and resource allocation for both communications and computing into account. To capture the stochastic nature of MEC environments, a Markov decision process (MDP) is employed to model the queuing states for both mobile devices and MEC servers. By combining MDP and matching theory, a joint user association and resource allocation algorithm is given, where the resource allocation policy under given user-server association is solved. Extensive numerical results demonstrate the superiority of the proposed scheme in comparison with several existing approaches.