Flexible Grid Optical Networks Research Articles

Novel Application of Quantum Computing for Routing and Spectrum Assignment in Flexi-Grid Optical Networks

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.

Long-term upgrade strategies in multiband and multifiber optical transport networks

Flexible-grid optical transport networks (OTNs) are currently undergoing a massive scale upgrade to bandwidth variable transceivers (BVTs) to cater to the exponential Internet traffic growth. Network operators seeking to plan future capacity in a scalable manner can also add additional bands of operations or additional fibers in the OTN. We propose two strategies for planning multiband upgrades in OTNs, which use an integer linear programming (ILP) solution and a heuristic solution with a reinforcement learning (RL)-based extension. Network simulation studies on three differently sized OTNs show that the heuristic and its RL-based extension perform extremely close to the optimal ILP-based solution while reducing execution times drastically. Finally, a techno-economic study based on what we believe to be a novel cost model highlights the cost-per-bit-per-second savings through carefully planned upgrades.

Congestion aware ant colony optimisation algorithm for routing and spectrum assignment in flexi-grid optical burst switching networks

This paper presents an improved distributed ant colony optimisation algorithm for routing and spectrum assignment (RSA) on optical burst switched (OBS), flexible spectrum networks, with the spectrum continuity constraint imposed. The improved algorithm incorporates a distributed method for monitoring the congestion along the links and using this information to determine what route-spectrum combination should be selected to minimise the burst loss probability (BLP). Evaluations were performed on an optical burst switching simulator to determine the effect on BLP when a dynamic route congestion measure is considered as opposed to the use of the static route length measure. The evaluations, considering the effects of optical impairments, were made on different network topologies, with multiple spectrum widths provisioned on the network, and with different loads. The incorporation of congestion measures into the algorithm showed improvements in BLP over previous work in the range of 2–32% depending on the evaluation conditions.

A polyhedral study of a relaxation of the routing and spectrum allocation problem (Brief Announcement)

The routing and spectrum allocation (RSA) problem arises in the context of flexible grid optical networks, and consists in routing a set of demands through a network while simultaneously assigning a bandwidth to each demand, subject to non-overlapping constraints. One of the most effective integer programming formulations for RSA is the DR-AOV formulation, presented in a previous work. In this work we explore a relaxation of this formulation with a subset of variables from the original formulation, in order to identify valid inequalities that could be useful within a cutting-plane environment for tackling RSA. We present basic properties of this relaxed formulation, we identify several families of facet-inducing inequalities, and we show that they can be separated in polynomial time.

Dynamic Virtual Network Embedding with Latency Constraint in Flex-Grid Optical Networks

Dynamic Virtual Network Embedding with Latency Constraint in Flex-Grid Optical Networks

Broadband polarization-entangled source for C+L-band flex-grid quantum networks.

The rising demand for transmission capacity in optical networks has motivated steady interest in expansion beyond the standard C-band (1530-1565 nm) into the adjacent L-band (1565-1625 nm) for an approximate doubling of capacity in a single stroke. However, in the context of quantum networking, the L-band has yet to be fully leveraged with the suite of advanced tools for characterization and management available from classical lightwave communications. In this work, we demonstrate an ultrabroadband two-photon source integrating both C- and L-band wavelength-selective switches for complete control of spectral routing and allocation across 7.5 THz in a single setup. Polarization state tomography of all 150 pairs of 25-GHz-wide channels reveals an average fidelity of 0.98 and total distillable entanglement greater than 181 kebits/s. This source is explicitly designed for flex-grid optical networks and can facilitate optimal utilization of entanglement resources across the full C+L-band.

Partial-Failure Segregated Spectrum Assignment for Multicast Traffic in Flex-Grid Optical Networks

In this paper, we propose a new algorithm called the partial-failure segregated multicasting routing and spectrum assignment (PFS MRSA) algorithm to improve the service blocking performance of the multicast transmission in flex-grid optical networks (FGONs). By segregating one failure destination leaf-node from a blocked multicast request and accommodating the failure destination leaf-node and the remaining multicast request independently, the success probability of accommodating the originally blocked multicast request can be greatly increased. In this way, the proposed PFS MRSA algorithm can effectively reduce the service blocking probability for the multicast services in FGONs. Simulation results show that the proposed PFS MRSA algorithm achieves significant reduction in service blocking probability when compared with the conventional MRSA algorithms, and such reduction can even reach 100% in some scenarios with low traffic load.

Spectrum-Entropy-Minimized Routing and Spectrum Allocation in IP over Mixed-Fixed/Flex-Grid Optical Networks

Mixed-Fixed/Flex-Grid Optical Networks (MFGONs) are a new paradigm that emerged during the brown-field migration from fixed-grid Wavelength Division Multiplexing (WDM) optical networks to flex-grid Elastic Optical Networks (EONs). Based on the flex-grid, we can accommodate IP traffic directly to the optical layer by configuration. Considering the different granularities of spectrum resources and complex constraints in MFGONs, it is difficult to apply Routing and Wavelength/Spectrum Allocation (RWA/RSA) algorithms proposed in either fixed-grid or flex-grid optical networks. This paper first proposes two concepts, i.e., Link Spectrum Compactness (LSC) and Radiancy of Nodes (RoNs), to evaluate different scenarios of candidate paths for the end-to-end requests in MFGONs. Then, based on these two concepts, a Spectrum Entropy (SE) model is proposed in MFGONs. Here, the SE is the metric that combines LSC and RoNs to judge the fragmentation of network resources, and the value of SE is treated as the cost of candidate paths during the RSA operation. Finally, an SE-minimized RSA algorithm in MFGONs is designed. Simulation results prove that the proposed algorithm can effectively reduce the Bandwidth Blocking Ratio (BBR) and increase the revenues for upgrading the nodes compared to the state-of-the-art RSA algorithm. Particularly, the performance improvement is more obvious for highly connected networks.

Dynamic Routing and Spectrum Assignment Based on the Consecutive Sub-Channels in Flexible-Grid Optical Networks

Using Optical Orthogonal Frequency Multiplexing (O-OFDM), variable bandwidth channels can be created in Elastic Optical Networks (EON). This allows the use of spectrum more efficiently by allocating integral multiple of basic bandwidth slots to the lightpath requests. Consequently, such networks are also called flexible grid optical networks. It also adds a constraint of keeping all the allocated slots together when deciding the routes for the requests. This constraint called the contiguity constraint makes the routing and spectrum algorithms more challenging. In any network, the lightpath requests will arrive and depart dynamically and will invariably lead to spectrum fragmentation, and hence network will have a reduction in maximum possible utilization due to increased blocking probability. In this paper, we have presented an improvised RSA algorithm that leads to lesser fragmentation. It is evident from the results that the presented RSA algorithm uses adaptive parameters to reduce the blocking probability and fragmentation compared to other algorithms reported in the recent past.

Fragmentation-Minimized Periodic Network-Bandwidth Expansion Employing Aligned Channel Slot Allocation in Flexible Grid Optical Networks

Fragmentation-Minimized Periodic Network-Bandwidth Expansion Employing Aligned Channel Slot Allocation in Flexible Grid Optical Networks

Virtual Network Provisioning over Mixed-Fixed/Flexible-Grid Optical Infrastructures

With the emergence of cloud services based on data centers, demands for bandwidth-intensive applications have increased dramatically, and application services have transferred to a more diversified direction. Management as well as capacity of the backbone network needs further development to catch up with rapidly evolved application demands. Optical network virtualization can facilitate the sharing of physical infrastructure among multiple network applications. Virtual Network Embedding (VNE), the main implementation of network virtualization, determines how to map a virtual network request onto physical substrate. To expand the network capacity, flexible-grid elastic optical networks have been considered as a promising supporting technology for the future infrastructure of the next-generation Internet. However, due to the expense of key enabling equipment for flexible grid optical networks, the brown-field migration from a fixed grid to a flexible grid gave birth to the co-existing fixed/flexible grid. Based on the co-existing fixed/flexible grid optical networks, we investigate the problem of Virtual Optical Network (VON) provisioning, and present a flexible-grid-aware virtual network embedding algorithm to map the virtual networks onto the substrate network. In addition, the performance of the algorithm was evaluated under four different network scenarios. Simulation results show that the proposed algorithm can achieve better performance in all four scenarios.

Resource Distribution Equilibrium for Virtual Network Embedding Over Flexi-Grid Optical Networks

Virtual network embedding (VNE) in network virtualization over flexi-grid networks is one of the main challenges up to now. Many models and algorithms based on reducing the cost or keeping integrity and continuity of spectrum slots have been already proposed. In this paper, we employ the concept of distribution equilibrium of computation resources to improve performance of VNE. An integer linear programming (ILP) model and an algorithm based on the concept of distribution equilibrium for virtual node embedding are developed. The experimental results show that this algorithm has some significant advantages. And then, an ILP model based on resource distribution equilibrium and adaptive modulation for VNE over flexi-grid optical networks is established. Since the ILP problem is NP-complete, a heuristic algorithm to manipulate VNE on table is developed. The simulation results reveal the superiority in terms of acceptance ratios and system revenues.

Cross-layer static resource provisioning for dynamic traffic in flexible grid optical networks

Flexible grid networks need rigorous resource planning to avoid network over-dimensioning and resource over-provisioning. The network must provision the hardware and spectrum resources statically, even for dynamic random bandwidth demands, due to the infrastructure of flexible grid networks, hardware limitations, and reconfiguration speed of the control plane. We propose a flexible online–offline probabilistic (FOOP) algorithm for the static spectrum assignment of random bandwidth demands. The FOOP algorithm considers the probabilistic nature of random bandwidth demands and balances hardware and control plane pressures with spectrum assignment efficiency. The FOOP algorithm uses the probabilistic spectrum Gaussian noise (PSGN) model to estimate the physical-layer impairment (PLI) for random bandwidth traffic. Compared to a benchmark spectrum assignment algorithm and a widely applied PLI estimation model, the proposed FOOP algorithm using the PSGN model saves up to 49% of network resources.

Weight distributed spectrum allocation in flexible-grid optical networks

An Elastic or flexible-grid Optical Network (EON) is an emerging technology for efficient resource utilization. In this paper, a Weight distributed service provisioning (WDSP) algorithm for routing and spectrum assignment (RSA) based on a request for a connection is proposed. This novel technique for spectrum allocation based on the demands of the connection request reduces the blocking of connections due to improper spectrum assignment. The connection requests are classified into two categories based on demand: small and large connection requests. The smaller size connection requests are assigned to the lower index slots, and the larger size connection requests are assigned to the highest index slots. By implementing this approach, a relatively large number of connection requests can be handled via the availability of a large set of contiguous slots. The simulation results illustrate that the proposed algorithm is relatively more efficient due to enhanced blocking performance; effective spectrum efficiency can be achieved.

Dynamic adaptive spectrum allocation in flexible grid optical network with multi‐path routing

Fragmentation is one of the major issues in elastic optical network (EON) due to its dynamic characteristics which may possibly degrade the spectrum efficiency. Several techniques have been presented in the literature to get the optimal solution of this problem while multi-path provisioning comes out to be very compelling among them. In multi-path provisioning enable networks, multi-path routing and spectrum assignment (MPRSA) creates further complications due to the hardware availability and more spectrum consumption. This paper presents a novel technique termed as adaptive service provisioning (ASP) to come up with a solution of the MPRSA problem and it minimizes the spectrum fragments in the network by precisely managing the scattered spectrum slots. This technique performs the adaptive traffic demand splitting on disjoint paths in case it is unable to be served by k-shortest routing paths based on the parameters such as hardware support, capacity available and demand. An integer linear programming (ILP) model as well as a heuristic algorithm for solving MPRSA problem in large optical networks where ILP is not compliant is developed. Numerical simulations are performed to investigate the performance of the algorithm in terms of blocking probability and spectrum utilization.

Solving routing and spectrum allocation problems in flexgrid optical networks using pre-computing strategies

Flexible optical network architectures are considered a very promising solution where spectrum resources are allocated within flexible frequency grids. This paper presents a minimum spectrum utilization (SU) and average path length (APL) approach to solve the (off-line) routing and spectrum allocation problem (RSA) based on combining a simple ordering pre-computation strategy, namely most subcarriers first (MSF) with three nature-inspired algorithms. These algorithms are ant colony optimization, differential evolution based relative position indexing (DE-RPI), and differential evolution general combinatorial (DE-GC). We begin by showing that MSF is the most effective ordering pre-computation strategy when compared to other well-known typical heuristics in the literature, such as first-fit, and longest path first. Then, we apply MSF in combination with the three nature-inspired algorithms to simultaneously optimize the SU and APL. The usefulness of MSF ordering pre-computation strategy is presented via a comparison of results obtained when using and not using MSF under the same scenarios. The algorithms are evaluated in benchmark optical networks, such as the NSFNet, the European optical network, and the 40-node USA network. We show that DE-RPI with MSF ordering pre-computation is the best option to solve the RSA problem, obtaining an average improvement percentage in the range of 0.9772–4.4086% on the SU and from $$-0.1668$$ to 0.8511% on the APL when compared to other meta-heuristics, either with or without the MSF ordering policy.

On solving the capacitated routing and spectrum allocation problem for flexgrid optical networks

The elastic optical networks, a.k.a., flexgrid networks, have flexible spectrum allocation. Such flexibility is possible due to the division of the spectrum into narrow frequency slots and the use of bandwidth-variable transponders. This enables the demand, in terms of band request, to be contiguously allocated starting from any available slot of the spectrum. In this context, the RSA (Routing and Spectrum Allocation) was proposed as an offline optimization problem of allocating the optical transmission resources in order to meet a predefined set of demands. This work deals with the capacitated version of the RSA problem. To solve it, we develop a multi-commodity flow formulation based on ILP (Integer Linear Programming) and a load balancing procedure that generate promising paths for an ILP formulation from the literature. Extensive computational experiments show that the proposed solution approaches are capable of obtaining high quality solutions on a variety of scenarios.

Experimental evaluation of dynamic resource orchestration in multi-layer (packet over flexi-grid optical) networks

Network services in 5G will be rolled out as pools of virtual network functions (VNFs) exploiting the advantages of both software-defined networking and network function virtualization. In this context, 5G network services are envisaged as ordered sequences of VNFs resulting in the so-called VNF Forwarding Graphs (VNFFGs). Such VNFs can be allocated over a number of distributed but interconnected data centers (DCs). In this work, a cloud/network orchestrator is discussed to dynamically process and accommodate VNFFG requests over a pool of DCs interconnected by a multi-layer (packet/flexi-grid optical) transport network infrastructure. Two different cloud and network resource allocation algorithms are proposed aiming at: (1) minimizing the distance between the selected DCs and (2) minimizing the load (i.e., consumed cloud resources) of the chosen DCs. In the performance evaluation, the proposed algorithms are experimentally validated and compared on the CTTC ADRENALINE testbed.

Effects of all-optical wavelength conversion on signal quality under variable-channel spacing in elastic optical networks

All-optical wavelength converters (AOWCs) based on parametric amplification in highly nonlinear fibers are investigated and evaluated, aiming at application flex-grid optical networks. A multichannel transmission system with a multilevel modulation format at 56-Gb / s bit rate is adopted. Parameters such as symbol error rate and signal bandwidth allocation are evaluated considering the optical signal-to-noise ratio, the power reception level, the channel spacing, and the impact of several cascade conversions—series of multiple AOWCs—on the signal quality. This work was carried out with an analytical modeling and computer simulations. Results reveal consistent modeling and adequate operation of the proposed AOWCs for flex-grid wavelength-division multiplexing networks and indicate that the number of conversions is limited by the size of the converter operating band and the allowed flex-grid slot size.

Service differentiation-based spectrum defragmentation in mixed grid optical networks

Abstract As the most promising candidate for upgrading today’s fixed-grid networks, the concept of flexible grid has been introduced into elastic optical networks (EONs), which enables on-demand spectrum assignment and adaptive modulation formats. Considering the cost of network upgrade, it is practical and economical for network operators to adopt the gradual migration from fixed grid to flexible grid optical network. Thus, a mixed grid optical network is a typical network scenario in the near future where fixed grid technology coexists with flexible grid technology. Spectrum fragmentation is regarded as a significant issue in flexible grid optical network. Compared with flexible grid, with heterogeneous spectral widths, more spectrum fragmentation is induced in mixed grid optical networks. Therefore, spectrum fragmentation in mixed grid optical network is actually much more challenging than flexible grid optical network. This paper first analyzes the resource allocation and proposes a novel spectrum defragmentation algorithm based on service differentiation in mixed grid optical networks. The performance of the proposed algorithm is evaluated in simulation with different traffic profiles. Simulation results verify that the proposed algorithm can effectively reduce the blocking probability by consolidating spectrum fragmentation in mixed grid optical networks.