Edge-Assisted Secure and Dependable Optimal Policies for the 5G Cloudified Infrastructure

This paper proposes an optimal admission and placement stochastic controller that inserts security and depend-ability in the operational aspects of edge-cloud system under a 5G deployment. The proposed mechanism uses the frame-work of Semi-Markov Decision Making Process (SMDP) and seeks for an optimal policy that efficiently allocates the virtual resources to secure and run the services across the cloudified infrastructure. Driven by a new latency-oriented cost structure, the optimal controller achieves a dependable and secure operation by optimally balancing the service requests between the edge and the cloud system taking into account the service profile, the workload, and the traffic load. A structural analysis of the optimal policy reveals its implementation friendliness while a cloudnomics analysis shows that the optimal cost can be further optimized by fine tuning the parameters of the proposed cost structure.

I. Introduction

5G wireless networks will enable the deployment of a massive physical and virtual infrastructure where mobile users, mission critical applications, and other critical infrastructure ecosystems will execute their communications and computing tasks. In this respect, security and protection mechanisms should be added by design to ensure a minimal cyber-risk exposure of applications and services.