The increasing demand for flexible and efficient optical networks has led to the development of Software-Defined Elastic Optical Networks (SD-EONs). These networks leverage the programmability of Software-Defined Networking (SDN) and the adaptability of Elastic Optical Networks (EONs) to optimize network performance under dynamic traffic conditions. However, existing simulation tools often fall short in terms of transparency, flexibility, and advanced functionality, limiting their utility in cutting-edge research. In this paper, we present a Flexible Unified Simulator for Intelligent Optical Networking (FUSION), a fully open-source simulator designed to address these limitations and provide a comprehensive platform for SD-EON research. FUSION integrates traditional routing and spectrum assignment algorithms with advanced machine learning and reinforcement learning techniques, including support for the Stable Baselines 3 library. The simulator also offers robust unit testing, a fully functional Graphical User Interface (GUI), and extensive documentation to ensure usability and reliability. Performance evaluations demonstrate the effectiveness of FUSION in modeling complex network scenarios, showcasing its potential as a powerful tool for advancing SD-EON research.

翻译：随着对灵活高效光网络需求的日益增长，软件定义弹性光网络应运而生。这类网络结合了软件定义网络的可编程性与弹性光网络的适应性，旨在动态流量条件下优化网络性能。然而，现有仿真工具在透明度、灵活性和高级功能方面往往存在不足，限制了其在前沿研究中的应用。本文提出了一种面向智能光网络的灵活统一仿真器，该完全开源的仿真器旨在突破这些局限，为SD-EON研究提供综合平台。FUSION将传统路由与频谱分配算法同先进的机器学习和强化学习技术相融合，包括对Stable Baselines 3库的支持。该仿真器还提供稳健的单元测试、功能完整的图形用户界面以及详尽的文档，以确保其可用性与可靠性。性能评估表明，FUSION在复杂网络场景建模方面成效显著，展现了其作为推动SD-EON研究有力工具的潜力。