Abstract:
In multi-access edge computing (MEC) networks, network slicing enables the MEC network service provider (MEC-NSP) to provide customizable MEC services for user devices (U...Show MoreMetadata
Abstract:
In multi-access edge computing (MEC) networks, network slicing enables the MEC network service provider (MEC-NSP) to provide customizable MEC services for user devices (UDs) with diverse QoS (Quality of Service) demands. In MEC network slicing, slice pricing and network resource allocation for slices are two core problems, which have not been jointly considered by existing works. To this end, we propose a two-stage slice pricing scheme to achieve balanced slice pricing and optimal network resource allocation. The goal of our scheme is to reduce the resource costs of the MEC-NSP and ensure its profit while meeting different user QoS requirements. At the first stage, we jointly optimize the computing, cache and communication resource allocation for all the slices by using problem decomposition. Then, we formulate a slice pricing problem based the Stackelberg game, prove the Nash equilibrium existence of the problem, and design an iterative algorithm based on the optimal response function. Extensive simulations are conducted in 4 scenarios, where our scheme is compared with 4 reference schemes. The simulation results demonstrate the superiority of our scheme in all the scenarios. The profit of the MEC-NSP optimized by our scheme is 17.64%-24.39% higher than those by the comparative works.
Published in: IEEE Transactions on Network and Service Management ( Volume: 21, Issue: 4, August 2024)