Lightpath Establishment Research Articles

Latency-Aware Scheduling Scheme for Deterministic Signaling in F5G

At present, the development of optical transport and access network has entered the fifth-generation fixed network (F5G) era. Services carried by optical transport network of F5G have stringent requirements for network performance. Optical transport networks can provide services with deterministic bandwidth and delay after lightpaths are established. The time to establish a lightpath may determine whether the service can be successfully transmitted. Lightpath establishment delay includes signaling delay and device configuration delay. Signaling delay is not deterministic as signaling is implemented based on non-deterministic packet switching in data communication network (DCN). Thus, realizing the deterministic signaling is a key research problem. Deterministic signaling means to complete signaling transmission at a given time, which can be divided into hard real-time signaling and soft real-time signaling. In this paper, we propose a latency-aware scheduling scheme for deterministic signaling in F5G. Simulative results show that i) for hard real-time signaling scheduling, the proposed latency-aware scheduling ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LAS</i> ) scheme reduces scheduling failure rate by 11.25%, improves resource utilization rate by 3.56%; ii) for hard real-time signaling and soft real-time signaling scheduling, the proposed scheme reduces scheduling failure rate by 6.57%, improves resource utilization rate by 3.34% and reduces end-to-end latency by 1.01s.

End-to-end service provisioning based on extended segment routing in multi-domain optical networks of F5G

As the most important fabric of fixed networks, the optical network plays an important role in expanding network capacity and providing long distance communication. At present, the fixed network has entered a key era, i.e., the fifth-generation fixed network (F5G). As one of the main features of F5G, the full-fiber connection requires a tenfold to hundredfold increase in the number of connections, which means F5G will have tens of thousands of nodes and millions of connections. Large-scale networks are composed of multiple network domains connected to each other. The whole network can be subdivided according to network functional domain. To meet different service requirements, how to provision fast end-to-end service in a multi-domain scenario has become a key issue. In optical networks, lightpath establishment must precede service transmission. The latency of lightpath establishment includes lightpath establishment signaling latency and optical interleaving device configuration latency. The latter depends on equipment performance. Therefore, how to provision fast lightpath establishment signaling is a key problem. To reduce end-to-end service provisioning latency, we propose an extended-segment-routing-based fast service provisioning scheme for the first time, to our knowledge, which consists of two steps: signaling path acquisition and signaling provisioning. For the signaling path acquisition step, we propose an adaptive segment routing (ASR) algorithm that first performs service path calculation based on service requirements, then performs a label compression algorithm to obtain the signaling path represented by the minimum number of labels according to the service path. For the signaling provisioning step, we propose a fast-signaling provisioning (FSP) process that can realize fast signaling provisioning in both single-domain and multi-domain scenarios. The simulation results show that, (1) compared to the Dijkstra algorithm, the ASR algorithm achieves a lower blocking probability for service and a better label compression effect for reducing the number of labels representing the signaling path, and, (2) compared to the traditional distributed signaling provisioning process and centralized signaling provisioning process, the FSP process achieves lower end-to-end latency.

Colorless, partially directionless, and contentionless architecture for high-degree ROADMs

With the rapid growth of Internet traffic, there can be multiple pairs of bi-directional fibers on a network link. This leads to the need for high-degree reconfigurable optical add/drop multiplexers (ROADMs) in an optical network. However, this high-degree requirement poses new challenges to ROADMs since it is challenging and expensive for a wavelength selective switch (WSS), a key switching component in a ROADM, to expand its size. Therefore, a common strategy is to use small-size WSSs to build a high-degree ROADM. In this paper, we design a novel colorless, partially directionless, and contentionless (CpDC) ROADM architecture, in which the sizes of WSSs can be significantly reduced by partially sacrificing the directionless feature of a ROADM. The partially directionless feature may degrade the switching performance of a ROADM. Thus, to tackle this issue, we also propose an interconnection pattern for the ROADM backplane to effectively connect fiber links and add/drop modules. An analytical model is developed to evaluate the lightpath blocking performance of a single CpDC ROADM. Efficient routing, fiber, wavelength, and add/drop port assignment (RFWPA) algorithms (i.e., the shortest-path-based and waveplane-based algorithms) are also developed for lightpath establishment in an optical network made up of CpDC ROADMs, in which two wavelength selection strategies [i.e., non-interconnection aware (NIA) and interconnection aware (IA)] are further proposed. Simulation studies show that, while these achieve almost the same lightpath blocking performance as conventional CDC ROADMs, CpDC ROADMs are more effective from considerations of cost, insertion loss, and node volume. The waveplane-based RFWPA algorithm with the IA strategy is also found to be the most effective for lightpath provisioning in an optical network made up of CpDC ROADMs.

Dynamic impairment-aware RMCSA in multi-core fiber-based elastic optical networks

Space division multiplex elastic optical networks (SDM-EONs) based on multi-core fiber (MCF) have been regarded as one of the promising solutions to address the future network capacity crunch. Inter-core crosstalk (XT) and intra-core physical layer impairments (PLI) exist in the MCF and degrade the quality of transmission (QoT) for lightpaths. Meanwhile, the establishment of new lightpaths affects the QoT of existing lightpaths due to dynamic spectrum occupancy in the network. This paper focuses on resource allocation under the constraint of physical impairment. Firstly, a dynamic impairment (DI) evaluation model is established to assess the level of impairment influence in terms of dynamic spectrum occupancy. Then, a DI-aware routing, modulation, core, and spectrum allocation (RMCSA) algorithm is proposed, which considers the influence of new lightpath establishment on existing lightpaths. Here, the core and spectrum resources with the least impact of impairment on existing lightpaths are selected preferentially to improve the QoT of lightpaths. Simulation results indicate that the proposed DI-aware RMCSA algorithm reduces the accumulated physical impairment on existing lightpaths, providing a lower probability of blocking and greater spectrum utilization.

Cross-feature trained machine learning models for QoT-estimation in optical networks

The ever-increasing demand for global internet traffic, together with evolving concepts of software-defined networks and elastic-optical-networks, demand not only the total capacity utilization of underlying infrastructure but also a dynamic, flexible, and transparent optical network. In general, worst-case assumptions are utilized to calculate the quality of transmission (QoT) with provisioning of high-margin requirements. Thus, precise estimation of the QoT for the lightpath (LP) establishment is crucial for reducing the provisioning margins. We propose and compare several data-driven machine learning (ML) models to make an accurate calculation of the QoT before the actual establishment of the LP in an unseen network. The proposed models are trained on the data acquired from an already established LP of a completely different network. The metric considered to evaluate the QoT of the LP is the generalized signal-to-noise ratio (GSNR), which accumulates the impact of both nonlinear interference and amplified spontaneous emission noise. The dataset is generated synthetically using a well-tested GNPy simulation tool. Promising results are achieved, showing that the proposed neural network considerably minimizes the GSNR uncertainty and, consequently, the provisioning margin. Furthermore, we also analyze the impact of cross-features and relevant features training on the proposed ML models’ performance.

Static routing and spectrum allocation method for design of low-power elastic optical networks with multifiber environments

This paper proposes a static Routing and Spectrum Allocation (RSA) method to design low-power elastic optical networks. In the elastic optical networks, data are transmitted via lightpaths, which are routes flexibly assigned frequency resources according to transmission distances and traffic demands. When designing the elastic optical networks with a static lightpath establishment policy, lightpaths are generally established so as to minimize frequency bandwidth allocated in order to save frequency resources necessary for constructing the networks. The proposed method focuses on not only this performance metric but also the power consumption of optical amplifiers. An optical amplifier in an optical fiber works when any of optical signals pass through it, and thus in multifiber environments where each link consists of multiple optical fibers, lightpaths should be collectively amplified from the view point of the power efficiency. Therefore, the relationship between these two performance metrics is a trade-off. The proposed method develops an Integer Linear Programming (ILP) formulation for the RSA problem taking the trade-off into account. Furthermore, the proposed method provides a heuristic algorithm that performs route selection and frequency spectrum allocation for reducing the total power consumption of optical amplifiers while saving necessary frequency resources. Through numerical experiments, we show the performance of the proposed method.

Impairment-aware spectrum allocation in elastic optical networks: A dispersion-sensitive approach

The degradation of quality-of-transmission (QoT) due to the dispersion effect is a critical issue in elastic optical networks (EONs). To satisfy the required quality of transmission, a robust modulation level needs to be adopted. Thus, the number of required slots for spectrum allocation is increased. Although dispersion compensation devices reduce the effect of dispersion, they require an additional cost. This paper presents a dispersion-sensitive spectrum allocation approach for EONs to suppress the call blocking in the network. The presented spectrum allocation approach does not use any dispersion compensating device for suppressing the dispersion effect. It allocates shorter lightpath requests from the largest indexed spectrum slot, where the effect of dispersion is higher, and longer lightpath requests from the smallest indexed spectrum slot, where the effect of dispersion is lower. To satisfy the required QoT threshold level for the longer lightpath requests, the presented approach uses a less robust modulation level. Thus, for lightpath establishment, a lower number of spectrum slots are required. In the presented approach, lightpath requests are separated as longer and shorter lightpath requests using either the predetermined-threshold policy or the lightpath threshold selection algorithm. When the traffic condition is not known in advance, the predetermined-threshold policy is not applicable. In that case, the lightpath threshold selection algorithm is used to find the distance threshold value, which provides the lowest blocking probability. Simulation results indicate that the presented dispersion-sensitive spectrum allocation approach outperforms the conventional spectrum allocation scheme in terms of available contiguous aligned slot ratio and blocking probability.

Machine Learning for Spectrum Defragmentation in Space-Division Multiplexing Elastic Optical Networks

In Elastic Optical Networks with Space Division Multiplexing, the dynamic allocation and deallocation of frequency slots can generate spectrum fragmentation, which increases the blocking of requests for lightpath establishment. In this article, we introduce a reactive algorithm and a proactive one that can jointly reduce spectrum fragmentation. We introduce a novel defragmentation approach based on an unsupervised machine learning technique to rearrange a fragmented spectrum by clustering lightpaths. A Routing, Modulation Format, Core, and Spectrum Allocation algorithm uses information on the clustering of lightpaths to establish new lightpaths for incoming requests. Results show that our approach can reduce the blocking of requests and spectrum fragmentation.

Design of low‐power all‐optical networks under the constraint of four‐wave mixing

SummaryIn this paper, we propose a static lightpath establishment method to design low‐power all‐optical networks under the constraint of four‐wave mixing (FWM). Since the FWM causes nonlinear interchannel crosstalk, it degrades the communication quality of optical signals. The FWM crosstalk effect becomes strong in a fiber as the number of passing optical signals increases. Therefore, we should reduce the number of optical signals passing through the same fiber from the perspective of the FWM. Meanwhile, in order to enhance the power efficiency of optical amplifiers, which are deployed at each optical fiber, it is preferred that multiple optical signals are transmitted in the same fiber. In order to decrease the power consumption while keeping high communication quality, the proposed method statically selects routes, wavelengths, and fibers for each traffic demand, considering the FWM crosstalk effect and the usage efficiency of the optical amplifiers. We show the performance of the proposed method through numerical experiments.

Lightpath routing and wavelength assignment for static demand in translucent optical networks

Translucent optical networks use sparsely located regenerator nodes to increase the optical reach, otherwise limited by the physical layer impairments. Routing in translucent networks often causes the lightpath to traverse a fiber more than once, requiring the use of multiple wavelengths on a fiber for the same lightpath. Most of the routing and wavelength assignment (RWA) algorithms for static demand in translucent networks (termed static RWA) require loop-free routes for shortest path routing and also are agnostic to traffic load. In this paper, we address the problem of static RWA in translucent networks without using physical layer information and show how to route lightpaths on paths with a loop (i.e., not a simple path). We propose integer linear programming formulation to get the exact solutions to the static RWA problem. This work is the first one to optimally solve the static RWA problem for non-simple paths, providing the lower bound on the number of wavelengths and regeneration needed for static lightpath establishment when regeneration facilities are limited. We propose a heuristic algorithm based on the concept of Wardrop equilibrium, to adaptively equalize the mean delay along all the lightpath routes from source to destination. The proposed heuristic can not only accommodate the correlation between feasible lightpath routes but also account for the fact that alternate routes correspond to different levels of choice randomness. Wavelength assignment is done using graph coloring with branch-and-price method. Numerical results demonstrate that the proposed heuristic reduces the number of regenerators and wavelengths required to satisfy a given demand.

Low-Crosstalk-Margin Routing for Spectrally-Spatially Flexible Optical Networks

In multicore fiber (MCF) equipped spectrally-spatially flexible optical networks (SS-FONs), the inter-core crosstalk (XT) affects quality of transmission (QoT) of lightpaths if it exceeds threshold XT ( $XT_{th}$ ). Thus, XT-management is of predominant concern in SS-FONs. In this work, we exploit the spatial dimension (i.e., core) of SS-FONs to calculate XT-aware routes, and propose a novel low-crosstalk-margin (LCM) routing scheme. The proposed LCM routing offers a proactive approach of XT-management, where two-dimensional (2D) routes leveraging core-switching are calculated and prioritized offline on the basis of XT-margins. Simulations indicate that the proposed LCM routing achieves up to 53.6% and 60.5% higher lightpath establishment as compared to the existing proactive XT-management methods, namely, XT-Avoid, and WC-XT, respectively. Further, the proposed LCM routing obtains near-optimal performance without the need of complex calculations that are performed dynamically by the optimal SXT-Check method.

Minimizing Cost of Regeneration at Regeneration Sites–A New Approach for Dynamic Lightpath Establishment in Translucent Optical Networks

Lightpaths in translucent optical networks have to undergo regeneration at certain nodes designated as regeneration sites to maintain its quality of transmission. Regenerating an optical signal necessitates optical-electronic-optical conversion and is thus a costly affair due to use of regeneration resources. Thus minimizing the cost of regeneration in such networks is vital. Minimizing cost of regeneration leads to two different problems; 1) the problem of minimizing the total cost of regeneration for the connections served and 2) the problem of minimizing the cost of regeneration at regeneration sites while serving the connections. The previous works on lightpath establishment in such networks have mostly addressed the first problem. In this paper we study the second problem i.e. the problem of minimizing the cost of regeneration at regeneration sites during dynamic establishment of lightpaths. As the problem is NP-Complete, we propose an Integer Linear Program for small networks and then propose two heuristic routing approaches for large networks. Time complexity analysis shows that our heuristic algorithms run in polynomial time. Extensive simulation experiments reveal that our approaches are not only efficient to address the problem but can also provide better blocking performance when regeneration resources are scarcely deployed at regeneration sites.

Hybrid Algorithm Based Effective Light Trail Creation in an Optical Networks

Abstract With the overwhelming use of the Internet, the wavelength division multiplexing (WDM) optical networks have become the major mode of communication for wide applications. Hence, the routing and wavelength assignment (RWA) for a given traffic in WDM networks is the chief challenge in optical networks. This paper presents the RWA problem in WDM networks using the hybrid algorithm of flower pollination (FP) and simulated annealing (SA) algorithm (FA+SA) with and without wavelength conversion capability at the nodes of the network. Comparative analysis with techniques presented in literature is also carried out, i. e. differential evolution algorithm (DEA), firefly algorithm (FA), particle swarm optimization with less number of informers (Psolbest), SA and genetic algorithm (GA). The results prove that hybrid algorithm of FP and SA is potentially more efficient than algorithms present in literature for the light path establishment in an optical network.

PLI-Aware Cost Management for Green Backbone All-Optical WDM Networks via Dynamic Topology Optimization

To cope with the energy inefficiency as well as the temporal uncertainty of real-world traffic in all-optical backbone networks, we explore the performance gains obtained from adaptively putting network elements into sleep mode, taking into account physical layer impairments (PLIs). Despite recent progress on link sleep mechanisms, the beneficial impacts of periodically activating and deactivating line amplifiers are seriously restricted by extra incurred operational expenditures due to accelerated aging of network equipment, which is a direct consequence of temperature fluctuations. In this paper, we revisit the problem of green PLI-constrained lightpath establishment, paying close attention to minimizing the number of on/off transitions. Toward this end, we formulate green lightpath establishment as a nonlinear multi-objective optimization problem, which addresses not only the energy efficiency, but also the grade of service and quality of service, using accurate models of a wide variety of linear/nonlinear PLIs. To tackle the developed problem under realistic scenarios, we propose the so-called green adaptive time-aware algorithm, which consists of lightpath establishment as well as wake-up/sleep procedures. The presented analysis followed by verifying simulations confirms that the proposed algorithm stands as a practical solution to the cost-efficient green impairment-constrained lightpath establishment problem under temporal uncertainly of incoming traffic.

Link Fault Tolerant Algorithms to Optimize the Blocking in Optical Burst Switching Networks

Abstract In this paper, link fault tolerant algorithms (LFTAs) are employed for optimization of blocking performance in optical burst switching (OBS) networks for dynamic establishment of wavelength-routed lightpaths. This paper presents two algorithms: link fault tolerance algorithm for least congestion (LFTALC) and link fault tolerance algorithm for optimized blocking (LFTAOB). In former algorithm, the path with least congestion is selected and in the latter algorithm the path with least blocking probability is selected and then both the algorithms check for the availability of fault on the links present in the selected path. The findings indicate that methods of developing link based fault tolerant algorithms keep good performance and fairness among all the connections. The key advantage of these proposed algorithms as compared to routing and wavelength assignment algorithm is that these are very simple in nature and require less service disruption time.

Deep-Learning-Assisted Network Orchestration for On-Demand and Cost-Effective vNF Service Chaining in Inter-DC Elastic Optical Networks

This work addresses the relatively long setup latency and complicated network control and management caused by on-demand virtual network function service chain (vNF-SC) provisioning in inter-datacenter elastic optical networks. We first design a provisioning framework with resource pre-deployment to resolve the aforementioned challenge. Specifically, the framework is designed as a discrete-time system, in which the operations are performed periodically in fixed time slots (TS). Each TS includes a pre-deployment phase followed by a provisioning phase. In the pre-deployment phase, a deep-learning (DL) model is designed to predict future vNF-SC requests, then lightpath establishment and vNF deployment are performed accordingly to pre-deploy resources for the predicted requests. Then, the system proceeds to the provisioning phase, which collects dynamic vNF-SC requests from clients and serves them in real-time by steering their traffic through the required vNFs in sequence. In order to forecast the high-dimensional data of future vNF-SC requests accurately, we design our DL model based on the long/short-term memory-based neural network and develop an effective training scheme for it. Then, the provisioning framework and DL model are optimized from several perspectives. We evaluate our proposed framework with simulations that leverage real traffic traces. The results indicate that our DL model achieves higher request prediction accuracy and lower blocking probability than two benchmarks that also predict vNF-SC requests and follow the principle of the proposed provisioning framework.

Attack-aware resource planning and sparse monitor placement in optical networks

This work presents joint optimization algorithms for lightpath establishment as well as sparse placement of optical performance monitoring (OPM) equipment in optical networks. OPMs are necessary to efficiently monitor the impact of physical layer attacks and are usually placed at locations that are more probable to be impacted by jamming attacks. A jamming attack is defined as a harmful signal interference with other signals, leading to service degradation, that is possible through intra-channel or inter-channel crosstalk effects. An Integer Linear Program (ILP) formulation is proposed to solve the problem of attack-aware routing and wavelength assignment (Aa-RWA), jointly with the placement of OPM equipment, in order to minimize the impact of physical layer jamming attacks in optical networks. Moreover, a Genetic Algorithm (GA) is proposed to solve the same optimization problem. The proposed GA algorithm is compared to the ILP formulation as well as to an attack-unaware RWA algorithm that has as an objective the minimization of the number of wavelengths required to accommodate all traffic demands, not accounting for the crosstalk interactions. Simulation results indicate that the proposed GA algorithm provides a solution that is close to the optimal in terms of crosstalk interactions, while also providing a very good solution in resource usage, measured in terms of the required number of wavelengths.

On Cost-Efficient Integrated Multilayer Protection Planning in IP-Over-EONs

In this work, we investigate the problem of integrated multilayer protection planning in IP over elastic optical networks (IP-over-EONs). We consider a single-failure scenario where either a router outage or a fiber cut would occur in any time period. To protect against a router outage, we formulate the backup router planning problem as a mixed linear programming (MILP) model in which the optical-layer spare capacity can be reused by the IP-layer spare capacity and the total cost consisting of the extra spare capacity and the IP-layer backup lightpaths is to be minimized. According to the time complexity of the weighted set-covering problem, we prove the $\mathcal{NP}$ -hardness of the backup router planning problem and, therefore, propose a heuristic algorithm. To protect against fiber cuts, we employ shared “1 + 1” path protection and propose a lightpath establishment algorithm that can not only clarify the types of the spare capacity but also perform spectrum sharing among them adaptively. Extensive numerical simulations show that our proposed backup router algorithm can achieve 96.88% similar results to the MILP model, and requires about 43.78% less IP-layer lightpaths than the benchmark algorithm based on dedicated backup routers. Meanwhile, our proposed lightpath establishment algorithm can reduce the planned spectrum resources by ${\text{35.67}}\%$ .

A routing and wavelength assignment scheme considering full optical carrier replication in multi-carrier-distributed optical mesh networks with wavelength reuse

This paper proposes a routing and wavelength assignment (RWA) scheme that considers full optical carrier replication to minimize the number of required wavelengths for wavelength-reusable multi-carrier-distributed (WRMD) mesh networks. Unlike the conventional wavelength division multiplexing networks where each node contains multiple laser diodes, the WRMD networks use a light source, called the multi-carrier light source, to ease the difficulty of controlling many light source devices. The optical carrier replication at any node of optical carrier or any end node of lightpath, called full optical carrier replication, improves the performance of the conventional schemes, which do not consider full optical carrier replication. This paper first formulates the RWA problem considering full optical carrier replication as an integer linear programming problem that minimizes the number of required wavelengths to satisfy the given lightpath setup requests. A heuristic RWA scheme is then proposed to solve the RWA problem in practical times. Simulation results show that our proposed heuristic RWA scheme for the WRMD network achieves a near-optimum number of wavelengths. In addition, it is able to reduce the number of required wavelengths for lightpath establishment, compared to the conventional scheme.

Sliding Scheduled Lightpath Establishment With Time-Slotted Wavelength-Switching

Extreme-scale transmissions exhibit schedules dependent upon the equipment used to generate data, availability of the collaborators who will investigate and analyze the data, and the availability of storage and supercomputing resources, which must be dedicated to distribution, backup, computation, and visualization of data. Given such a wide array of dependencies, these applications, which are often scientific in nature, offer the luxury of in-advance reservation of network resources prior to the demand uptimes. Advance reservation (AR) allows for efficient scheduling around or in cooperation with competing reservations from other applications. This work focuses on static inputs to two classifications of AR demands: with and without sliding-window flexibility. We further introduce the ability for a demand to be assigned to more than one dedicated wavelength at different points throughout its lifetime depending on availability. This λ-switching functionality is incorporated at time-slot granularity, which limits the overhead associated with reconfiguring wavelength resources at runtime and enhances opportunities for scheduling efficiency. A novel λ-switching integer linear program is presented to evaluate this enhancement under varying degrees of temporal flexibility. Detailed and novel proofs are provided, which demonstrate that AR scheduling with and without λ-switching is in the complexity class NP-complete. Conservative heuristics are presented to harness the benefits of λ-switching while lowering the trade-off from transceiver reconfiguration overhead. Lower bounds also are developed as a baseline comparison for these heuristics, and we evaluate these solutions through extensive simulation. We also introduce the notion of considering time-slotted, wavelength-routed networks from the perspective of a finer resource granularity represented by the intersection of the temporal and spectral resource domains.