User Allocation in NOMA-Based Edge Computing Environment

Due to an increasing amount of users, service providers are paying more attentions on how to properly tackle the User Allocation (UA) problem. In the literature, few solutions to the UA problem took into account the heterogeneity of devices and the complexity of the network. Therefore, the paper takes these two factors into account and studies the UA problem in Non-Orthogonal Multiple Access (NOMA)-Based heterogeneous edge computing scenarios. To solve the above problem, we propose the Heuristic Ant colony Systems (HAS) algorithm, which aims to enhance the number of allocated users while reducing the overall deadline violation time. Extensive evaluations that employ a public dataset demonstrate the benefits of our proposed approach.