Elastic Optical Networks (EONs) increase the transport capacity of standard optical networks, and have been proposed as a short-term solution to satisfy the dynamic demands of service quality requirements. To this end, the development of algorithms to better facilitate Routing and Spectrum Allocation (RSA) is envisaged to have a critical impact on the performance of EON. Given the abundance of RSA algorithms, this study presents the unique challenge of organizing and classifying them meaningfully to understand and select the most suitable approach for the corresponding niche service quality requirements. This study proposes a novel taxonomy structure for grouping RSA algorithms based on the following criteria: (1) resource assignment policies, (2) flexibility type, (3) traffic type, (4) optimization approaches, (5) number of objective functions, and (6) problem separability. Finally, the contributions of this study are twofold: it presents a state-of-the-art taxonomy framework that organizes existing published works based on a set of predetermined criteria, and explores research opportunities involving RSA algorithms to realize the full potential of EONs in telecommunications.

This paper addresses serialized approaches of the routing, modulation level, and spectrum assignment (RMLSA) problem in elastic optical networks, using multiple sequential sub-sets of requests, under Integer Linear Programming (ILP). The literature has reported two-stage serial optimization methods referred to as RML+SA, which retain computational efficiency when the problem grows, compared to the classical one-stage RMLSA optimization approach. However, there still remain numerous issues in terms of the spectrum used that can be improved when compared to the RMLSA solution. Consequently, this paper proposes RML+SA solutions considering multiple sequential sub-sets of requests, split traffic flow, as well as path-oriented and link-oriented routing models. Simulation results on different test scenarios determine that: (a) the multiple sequential sub-sets of request-based models improve computation time without worsening the spectrum usage when compared to just one set of requests optimization approaches, (b) divisible traffic flow approaches show promise in cases where the number of request sub-sets is low compared to the non-divisible counterpart, and (c) path-oriented routing succeeds in improving the used spectrum by increasing the number of candidate routes compared to link-oriented routing.