Virtual Network Mapping for Multicast Traffic over Elastic Optical Networks

Network Function Virtualization (NFV) allows multiple Virtual Networks (VNs) to share the underlying physical infrastructure via VN mapping, thus improving the utilization of physical resources. In this paper, for the first time, we study the multicast service-oriented VN mapping that can support big data applications over Elastic Optical Networks (EONs). We first formulate the problem of minimizing the spectrum consumption in multicast service-oriented VN using a Mixed Integer Linear Programming (MILP) model in order to achieve the lower bound on the spectrum consumption. We then propose an efficient heuristic algorithm, called Integrated Genetic and Simulated Annealing (IGSA) algorithm to address the problem with low computational complexity. By encoding node mapping, multicast tree construction, link mapping and spectrum requirements in the same gene and auto-adjusted evolution, and utilizing simulated annealing to find the fittest multicast requests mapping order, IGSA can perform joint optimization for all the multicast requests in a global way. Through extensive simulations, we demonstrate that IGSA outperforms the other heuristic solutions in terms of spectrum consumption, blocking probability and normalized throughput, while achieving close to minimum spectrum consumption with a much lower time complexity than MILP. Keywords—Multicast; Virtual Network Mapping; Elastic Optical Networks (EONs); Mixed Integer Linear Programming (MILP); Integrated Genetic and Simulated Annealing