Resource-Aware Virtual Network Parallel Embedding Based on Genetic Algorithm

Abstract

Embedding virtual network requests in an underlying physical infrastructure, the so-called virtual network embedding (VNE) problem, has attracted significant research interests already. A realistic scenario might entail embedding multiple VN requests (MVNE) that arrive simultaneously (batch arrivals). The existing heuristic MVNE approaches neither consider the coordination among multiple VNR embeddings nor embed all the arriving VNRs simultaneously considering the available physical resources. This paper considers the MVNE problem in the scenario where the available physical resources may not be sufficient to satisfy the physical resource demands of all the VNRs in the batch. We explore applying genetic algorithm (GA) to handle the MVNE problem. We propose an algorithm to decide which VNRs could be mapped together. Extensive simulations are carried out to evaluate the performance of the proposed algorithms in terms of the VN acceptance ratio and the long-term revenue of the service provider.