Crosstalk Classification Based on Synthetically Consider Crosstalk and Fragmentation RMCSA in Multi-Core Fiber-Based EONs

Space division multiplexing elastic optical networks (SDM-EONs) based on multi-core fiber (MCF) technologies have attracted widespread attention as a potential means of enhancing large capacity and high flexibility. However, inter-core crosstalk (XT) degrades the quality transmission. The algorithm for minimizing XT leads to an increase in spectrum fragmentation lightpath, which influences utilization. Therefore, question how comprehensively consider two factors improve network performance is issue worthy study. This paper focuses maximizing resource utilization while satisfying constraints. Firstly, we optimize three-dimensional metric model evaluate more exactly SDM-EONs. Furthermore, classification (CC) algorithm, can adjust constraints according actual situation network, proposed. Moreover, match CC describe propose synthetically (SCCF) algorithm. Finally, simulation results show that proposed CC-SCCF routing, modulation, core, allocation reduces existing lightpaths, also provides lower probability blocking greater