Dynamic joint resource allocation and user assignment in multi-access edge computing
Multi-Access Edge Computing (MEC) is one of the key technology enablers of the 5G ecosystem, in combination with the high speed access provided by mmWave communications. In this paper, among all services enabled by MEC, we focus on computation offloading, devising an algorithm to optimize computation and communication resources jointly with the assignment of mobile users to Access Points and Mobile Edge Hosts, in a dynamic scenario where computation tasks are continuously generated according to (unknown) random arrival processes at each user. To formulate and solve the dynamic allocation/assignment problem, we merge tools from stochastic optimization and matching theory, thus developing a low complexity algorithmic solution that works in an online fashion. Numerical results illustrate the potential advantages of the proposed approach.