Joint Planning of Network Slicing and Mobile Edge Computing: Models and Algorithms

Multi-access Edge Computing (MEC) facilitates the deployment of critical applications with stringent QoS requirements, latency in particular. This article considers problem jointly planning availability computational resources at edge, slicing mobile network and edge computation resources, routing heterogeneous traffic types to various slices. These aspects are intertwined must be addressed together provide desired all users still keeping costs under control. We formulate our as a mixed-integer nonlinear program (MINLP) we define heuristic, named Neighbor Exploration Sequential Fixing (NESF), facilitate solution problem. The approach allows operators fine tune operation cost total experienced by users. evaluate performance proposed model heuristic against two natural greedy approaches. show impact variation considered parameters (viz., different traffic, tolerable latency, topology bandwidth, link capacity) on defined model. Numerical results demonstrate that NESF is very effective, achieving near-optimal resource allocation solutions short computing time even for large-scale scenarios.