Route planning and optimization tools for optical networks: a comprehensive analysis

This work aims to provide a review of the route planning and optimization tools for optical networks from optimization algorithms to their evaluation approaches. Optical networks are considered one of the most famous technologies in order to implement telecommunications backbones. The optimal performance of optical networks and the recognition of possible performance bottlenecks are of significance to network operators. Nevertheless, since each vendor uses a diverse set of performance indicators and performance prediction approaches, it is very difficult to create a single, vendor-neutral performance map of an optical network. In internet traffic, the steady rise demands large-scale and high-speed optical networks with effectual spectrum resource utilization. Thus, cautious allocation of optical resources is needed; mainly Gaussian Noise simulation in Python (GNPy)-based transmission parameters for route planning is employed. In this paper, various approaches based on different route planning techniques in optical networks are exploited. The research works are analyzed by classifying them based on the approaches used in preceding works. Additionally, the research gaps and challenges recognized in the conventional studies are mentioned; thus, it will assist the researchers in finding an enhanced solution and also improve their studies in the future. In this study, the related works used are verified on the basis of several scenarios, such as platform employed and performance evaluation measures. It is noted that the most commonly used tool using GNPy package is Python. Also, this study enlists the future scope by examining the research gaps present in the related works to researchers; thus, it enhances their studies.