On Throughput Optimization in Software-Defined Multi-Dimensional Space Division Multiplexing Optical Networks

Abstract

The capacity expansion of a single time division multiplexing (TDM) or wavelength division multiplexing (WDM) domain is difficult to cope with long-term capacity pressure. The emergence of space division multiplexing (SDM) technology provides a new dimension for the expansion of optical network capacity, namely the spatial dimension. However, this also poses a challenge to both network control and resource optimization. Therefore, to improve the flexibility of network control, we propose an architecture of software-defined multi-dimensional SDM optical networks based on architecture on demand (AoD) nodes and multi-core fiber (MCF) links in this paper. Next, we mathematically describe the system model including a model of the SDM network, a model of multi-type service requests, and a MCF model. Then, an integer linear programming (ILP) is developed to minimize the index of multi-dimensional resources occupied by multiple types of services in the time, frequency, and space domains. To reduce inter-core crosstalk between homogeneous cores, the core classification algorithm is designed to build multi-granular network layers. Also, for adjacent heterogeneous cores, we utilize the AoD to customize different functions and use different spectrums to transmit different types of services. Finally, we propose routing and multi-dimensional resource allocation algorithms to optimize network throughput. The simulation results show that the proposed algorithms can effectively improve the throughput of the software-defined multi-dimensional SDM optical networks compared with the benchmark algorithms.