AnalyticalSAR: Analytical Modeling for Blocking Performance With Security-Aware Reconfiguration in Spectrally-Spatially Elastic Optical Networks

Spectrally-spatially elastic optical networks (SS-EONs) enable ultra-high data rate transmission, which raises critical concerns about physical-layer security vulnerabilities, particularly against eavesdropping and unauthorized network access. Dynamic resource allocation through lightpath reconfiguration presents an effective approach to improving security by reducing request exposure windows. However, implementing secure reconfiguration in SS-EONs introduces significant complexity due to the complex relationships between spectral allocation and spatial resource management constraints. This paper proposes an analytical model for blocking performance with security-aware reconfiguration (AnalyticalSAR) in SS-EONs based on continuous-time Markov chain analysis to tackle these security challenges. The AnalyticalSAR provides analytical assessment of how spectrum reconfiguration affects both network security and blocking performance while accounting for inter-core and intermode crosstalks. The model generates all viable states accounting for spectrum reconfiguration processes and their corresponding transitions to establish state probabilities. Our analysis incorporates two distinct spectrum allocation policies: core-modespectrum random fit (CMS-RF) and core-mode-spectrum first fit (CMS-FF) policies. Our model supports diverse traffic scenarios, including single-class requests with uniform slot requirements and multi-class requests including heterogeneous bandwidth demands. To overcome computational complexity limitations in single-hop analyses, we develop an heuristic iterative approach and subsequently extend this approach to multi-hop network scenarios. We compare AnalyticalSAR, the heuristic iterative approach, and Monte Carlo simulation studies for a single-hop link. Analytical evaluation reveals that random spectrum reconfiguration substantially improves security metrics while introducing minimal blocking probability increases. These performance trade-offs depend critically on number of spectrum reconfiguration, link and network load conditions, and available link capacity. The results validate that AnalyticalSAR achieves an effective compromise between security enhancement and operational performance, providing a practical framework for secure resource management in SS-EON deployments.