Hybrid quantum-classical computing mechanism for QoT-aware dynamic routing, modulation, and spectrum allocation in a multi-band flexible optical network
Miao Zhu, Rentao Gu, Jiangshan Dong, Lin Ling Bai, Hui Li, Yuefeng Ji
The exponential growth of global network traffic has made the expansion of network capacity increasingly urgent. Multi-band and flexible grid technologies have emerged as promising solutions to enhance network transmission capacity. Fast routing is an important measure to ensure the survivability of a multi-band flexible optical network (MB-FON) that carries massive services. However, the extensive network resources and the inter-channel stimulated Raman scattering (ISRS) effect between different bands pose a challenge to the efficient solution of classical routing, modulation, and spectrum allocation (RMSA) methods. This paper leverages the parallel computing advantage of quantum computing and proposes a hybrid quantum-classical computing mechanism for quality of transmission (QoT)-aware dynamic RMSA in MB-FON. In this mechanism, a decouple-then-integrate strategy is proposed to formulate the QoT-aware RMSA problem as a quadratic unconstrained binary optimization model. The augmented Lagrangian method is introduced to deal with the inequality constraint in an ISRS-aware formulation, and a path fragmentation metric is proposed to design the optimization objective. In addition, a coherent Ising machine is used to solve the problem by adjusting the parameters and precision in combination with classical computing methods. Experiments were conducted on network topologies of different sizes. The experimental results show that the solution time can be reduced from nearly 6 s to 537 µs compared with the auxiliary graph-based heuristic algorithm in a 142-node network. It also demonstrates that the proposed mechanism outperforms classical heuristic algorithms in terms of blocking probability and spectrum utilization.
The exponential growth of global network traffic has made the expansion of network capacity increasingly urgent. Multi-band and flexible grid technologies have emerged as promising solutions to enhance network transmission capacity. Fast routing is an important measure to ensure the survivability of a multi-band flexible optical network (MB-FON) that carries massive services. However, the extensive network resources and the inter-channel stimulated Raman scattering (ISRS) effect between different bands pose a challenge to the efficient solution of classical routing, modulation, and spectrum allocation (RMSA) methods. This paper leverages the parallel computing advantage of quantum computing and proposes a hybrid quantum-classical computing mechanism for quality of transmission (QoT)-aware dynamic RMSA in MB-FON. In this mechanism, a decouple-then-integrate strategy is proposed to formulate the QoT-aware RMSA problem as a quadratic unconstrained binary optimization model. The augmented Lagrangian method is introduced to deal with the inequality constraint in an ISRS-aware formulation, and a path fragmentation metric is proposed to design the optimization objective. In addition, a coherent Ising machine is used to solve the problem by adjusting the parameters and precision in combination with classical computing methods. Experiments were conducted on network topologies of different sizes. The experimental results show that the solution time can be reduced from nearly 6 s to 537 µs compared with the auxiliary graph-based heuristic algorithm in a 142-node network. It also demonstrates that the proposed mechanism outperforms classical heuristic algorithms in terms of blocking probability and spectrum utilization.
The rapid advancement of beyond-5G and 6G services is creating computational challenges that classical optimisation methods for Elastic Optical Networks (EONs) cannot effectively handle. Specifically, the multi-objective Routing and Spectrum Assignment (RSA) problem—aimed at minimising blocking probability, maximising spectral efficiency, and reducing fragmentation—poses significant challenges and is NP-hard, particularly in dynamic traffic. This paper introduces a hybrid framework that combines quantum and classical computing, dividing the optimisation tasks into classical pre-processing, a quantum optimisation core, and classical post-processing with Pareto frontier management. The RSA problem is modelled using a Quadratic Unconstrained Binary Optimisation (QUBO) formulation that accounts for blocking, efficiency, and a quadratic fragmentation metric. Simulations conducted on NSFNET and UBN topologies under Poisson traffic conditions revealed that even in realistic, noisy quantum environments, this hybrid method reduces the blocking probability by 14% and improves fragmentation by 7.3% compared to the top classical heuristics. A scaling analysis indicates a key point of around 220 variables where this hybrid strategy surpasses traditional meta-heuristics in both solution quality and execution time, emphasising its significant potential in the current NISQ era.
Flexi-grid technology has revolutionized optical networking by enabling Elastic Optical Networks (EONs) that offer greater flexibility and dynamism compared to traditional fixed-grid systems. As data traffic continues to grow exponentially, the need for efficient and scalable solutions to the routing and spectrum assignment (RSA) problem in EONs becomes increasingly critical. The RSA problem, being NP-Hard, requires solutions that can simultaneously address both spatial routing and spectrum allocation. This paper proposes a novel quantum-based approach to solving the RSA problem. By formulating the problem as a Quadratic Unconstrained Binary Optimization (QUBO) model, we employ the Quantum Approximate Optimization Algorithm (QAOA) to effectively solve it. Our approach is specifically designed to minimize end-to-end delay while satisfying the continuity and contiguity constraints of frequency slots. Simulations conducted using the Qiskit framework and IBM-QASM simulator validate the effectiveness of our method. We applied the QAOA-based RSA approach to small network topology, where the number of nodes and frequency slots was constrained by the limited qubit count on current quantum simulator. In this small network, the algorithm successfully converged to an optimal solution in less than 30 iterations, with a total runtime of approximately 10.7 s with an accuracy of 78.8%. Additionally, we conducted a comparative analysis between QAOA, integer linear programming, and deep reinforcement learning methods to evaluate the performance of the quantum-based approach relative to classical techniques. This work lays the foundation for future exploration of quantum computing in solving large-scale RSA problems in EONs, with the prospect of achieving quantum advantage as quantum technology continues to advance.
Quantum key distribution (QKD) is considered as a promising solution for secure communications. Nevertheless, challenges such as the elevated cost of dark-fibers used for QKD, quantum transceivers (Q-TRx), and security issues with QKD trusted nodes impede its widespread deployment. This paper explores a multi-band elastic optical network (MB-EON) for implementing QKD on the existing fiber infrastructure, augmenting network capacity without the need for new fiber installations. The careful transmission of classical and quantum channels in MB-EON necessitates impairment-aware algorithms to shield quantum channels from potential disruptions caused by classical channels. To tackle this, we conduct an in-depth analysis of various noise sources to pinpoint the optimal key transfer scenario. Our study further includes calculations for the upper bound of the public interaction channel (PICh) bit rate in the BB84-Decoy protocol and the secret key rate (SKR). Furthermore, a time division multiplexing technique is proposed to allocate bit-rate of each Q-TRx and PICh-TRx among received demands and grooming them as a one connection. Furthermore, we delve into the QKD trusted node placement method as a robust solution for long-distance QKD, effectively minimizing Q-TRx usage and selecting less QKD trusted nodes to bolster network security by proposing the hot-links algorithm (HLA). Finally, three routing, modulation format, spectrum, and time slot assignment (RMSTA) algorithms are proposed and compared. The simulation results reveal that the proposed HLA trusted node placement method with flexible routing of classical channels and QKD channels demonstrates significant improvements in key transfer efficiency, network security, and blocking probability compared to the fixed-distance trusted node placement with joint routing of CChs and QKD channels.
Quantum-key-distribution (QKD) enabled optical networks can provide secure keys for different kinds of applications to ensure the high security of communication processes. As the number of wavelength channels in a single-core fiber is limited, space division multiplexing (SDM) has been considered to be a valuable technique to provide more wavelength resources, which solves the problem of insufficient channel capacity. Due to the rapid expansion of data volume, the SDM-based QKD network has been regarded as an important paradigm. At the same time, resource allocation in multi-core optical networks is a problem worthy of studying. In this work, four routing, core, and wavelength allocation (RCWA) algorithms are proposed in the multi-core optical network for quantum service requests and classical service requests, which are referred to as RCWA without perception (RCWA-WP), RCWA with crosstalk perception (RCWA-XTP), RCWA with spectrum perception (RCWA-SP), and RCWA with core perception (RCWA-CP). Simulations are carried out to evaluate the network performance in terms of blocking probability, key utilization, and average crosstalk intensity. The comparative results indicate that the RCWA-SP algorithm can improve network performance and reduce the blocking probability, while the RCWA-XTP algorithm can reduce inter-core crosstalk during transmission.
Optimization problems are fundamental in a wide range of fields, including telecommunications, where efficient resource allocation is critical to ensure good network performance and high scalability. In the context of elastic optical networks (EONs), the multi-objective routing and spectrum assignment (MO-RSA) problem represents a key challenge, as it involves selecting a valid path and assigning frequency slots while fulfilling continuity and contiguity constraints and optimizing multiple conflicting objectives. This paper presents a novel, to the best of our knowledge, quantum-based approach to solving the MO-RSA problem. We first formulate the MO-RSA problem as a quadratic unconstrained binary optimization (QUBO) problem and then solve it using the quantum approximate optimization algorithm (QAOA). Our method accounts for both minimizing the total number of used links (or any non-negative additive metric) and maximizing the optical signal-to-noise ratio. For our simulations, we employed the Qiskit framework and IBM’s sampler-based quantum backend to implement and test the proposed approach. Our results demonstrate that by encoding the MO-RSA problem into a QUBO model and optimizing it with QAOA, we achieved an approximation ratio of 88% and a computational complexity of O ( n 2 ) , which represents a significant improvement over the exponential complexity of traditional integer linear programming methods.