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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.