Distributed Resource Allocation Optimization in 5G Virtualized Networks

The concepts of network function virtualization and end-to-end network slicing are the two promising technologies empowering 5G networks for efficient and dynamic network/service deployment and management. In this paper, we propose a resource allocation model for 5G virtualized networks in a heterogeneous cloud infrastructure. In our model, each network slice has a resource demand vector for each of its virtual network functions. We first consider a system of collaborative slices and formulate the resource allocation as a convex optimization problem, maximizing the overall system utility function. We further introduce a distributed solution for the resource allocation problem by forming a resource auction between the slices and the data centers. By using an example, we show how the selfish behavior of non-collaborative slices affects the fairness performance of the system. For a system with non-collaborative slices, we formulate a new resource allocation problem based on the notion of dominant resource fairness and propose a fully distributed scheme for solving the problem. Simulation results are provided to show the validity of the results, evaluate the convergence of the distributed solutions, show protection of collaborative slices against non-collaborative slices and compare the performance of the optimal schemes with the heuristic ones.