Graph Signal Processing Meets Optical Resource Allocation

Graph signal processing is an emerging field in which traditional signal processing tools from regular Euclidean domain are adapted for use in irregular domains such as graphs. This paper demonstrates how graph signal processing can be used as an efficient tool to solve an optical resource allocation problem, particularly the routing and wavelength assignment problem, where a reduction of 25% in blocking probability can be achieved compared to the conventional counterpart schemes.