Automated and Optimized Embedding of Virtual Networks and Network Slices

Abstract

In this paper we propose a mechanism to automate the management of large networks based on the autonomic network management scheme. It incorporates a novel embedding algorithm that is 3 to 6 times faster than related work in finding out optimal embedding a virtual network (VN) or network slice (NS) to a substrate network (SN). It therefore finds out a configuration that assigns the elements of the VN/NS to the elements of the SN. The main novelty of this algorithm is the application of the knowledge from the VN/NS to get a configuration by improving a previous configuration, so less computing power is required than related work. The reasoning process is designed to consider the traffic of the network together with node load, so the resulting configuration optimizes the overall usage of the SN. Finally, the algorithm and heuristic also target the minimization of the number of operations required to obtain a new configuration from the current configuration, thus avoid the addition, removal, or movement of elements as much as possible. We demonstrate these claims by evaluating a proof-of-concept implementation of our solution and comparing it with the previous solutions.