Abstract
In this article, we enhanced the capability of SIMON (Simulator for Optical Networks) by considering the nonlinear effect of the optical network components and different industry network devices. This is achieved by using an optical route planning library called GNPy (Gaussian Noise model in python) as the calculation model within SIMON. SIMON is implemented in C++ and has mainly been used as an optical network learning tool for studying the performance of wavelength-routed optical networks. It measures the network blocking probability by taking into consideration the optical device characteristics. SIMON can capture the most significant impairments when estimating the Bit-Error Rate (BER) but does not consider fiber dispersion and non-linearities. These impairments can be significant when simulating a large-scale network. GNPy, on the other hand, considers those physical impairments and can give a more accurate signal-to-noise ratio (SNR) estimation validated by real-world measurements. By integrating GNPy with SIMON, we are able to set a minimum SNR threshold, which must be satisfied by any call set up in the network. The integration of SIMON and GNPy makes the resulting simulator not only suitable for academic learning but also valuable for real-world network planning, evaluation, and deployment of optical networks.
Byrav Ramamurthy
Professor & PI
My research areas include optical and wireless networks, peer-to-peer networks for multimedia streaming, network security and telecommunications. My research work is supported by the U.S. National Science Foundation, U.S. Department of Energy, U.S. Department of Agriculture, NASA, AT&T Corporation, Agilent Tech., Ciena, HP and OPNET Inc.