An Enhanced Exploration GRASP-Based Algorithm for Virtual Network Embedding

With the rise of distributed clouds and Virtualized functions, Virtual Network Embedding (VNE) has become a key challenge in enabling network slicing. Several approaches exist in the literature to tackle such a problem; some of them (e.g., heuristics) converge quickly to a local minimum, while others are not explainable and, therefore, do not provide the necessary guarantees for their deployment in a real network (e.g., artificial intelligence-based techniques). In this paper, we propose an enhanced GRASP-based algorithm that efficiently explores the solution space using a broader candidate selection and deeper local search. The simulation results show the potential of the proposed method for solving services’ placement problems and its superiority over some heuristics in terms of placement success rate and the Revenue to the Cost (R/C) metric.