AbstractWith the rapid development of mobile Internet, high-definition video and cloud computing, users’ bandwidth demands are not only larger and larger but also more and more diverse. To solve this problem, there searchers put forward the concept of elastic optical network (EON). EON adopts the transmission mode of elastic grid, which can allocate spectrum resources flexibly and meet high bandwidth and diversity requirements at the same time. Routing and spectrum allocation (RSA) is an important issue in EON. In this paper, we present a heuristic algorithm named constrained-lower-indexed-block (CLIB) allocation algorithm for the RSA problem. The algorithm is based on the K candidate paths. When there are available spectrum blocks on multiple candidate paths, if the increase of the path length does not exceed a given threshold, the lower index spectrum would be selected for the connection request on a longer path. The aim of the algorithm is to concentrate the occupied frequency slices on one side of the spectrum and leave another side of the spectrum to the later arrived connection requests as much as possible, to reduce the blocking probability of connection requests. Simulation results show that comparing with the first-last-fit and hybrid grouping algorithms, the CLIB algorithm can reduce the blocking probability of connection requests.
A Research on Routing and Spectrum Allocation Algorithm for Elastic Optical Networks Based on Deep Learning
