Delay Minimization in Sliced Multi-Cell Mobile Edge Computing (MEC) Systems

Here, we consider the problem of jointly optimizing users' offloading decisions, communication and computing resource allocation in a sliced multi-cell mobile edge (MEC) network. We minimize weighted sum gap between observed delay at each slice its corresponding requirement, where weights set priority slice. Fractional form objective function, discrete subchannel allocation, considered partial offloading, interference incorporated rate make complex mixed integer non-linear programming problem. Thus, decompose original into two sub-problems: (i) decision-making (ii) joint computation resource, subchannel, power allocation. solve first sub-problem optimally for second sub-problem, leveraging on novel tools from fractional Augmented Lagrangian method, propose an efficient algorithm whose computational complexity is proved to be polynomial. Using alternating optimization, these sub-problems iteratively until convergence obtained. Simulation results demonstrate our proposed effectiveness compared existing schemes.