Software-defined Elastic Optical Networks Research Articles

Active Learning-Aided CNN-Based Entropy-Tunable Automatic Modulation Identification for Rate-Flexible Coherent Optical System

Flexible rate and real-time link monitoring are important tasks in the development of software-defined elastic optical networks (EONs). The tunable spectral efficiency characteristic of probabilistic constellation shaping (PCS) naturally provides a possibility to dynamically regulate the rate for future optical communication systems. In this work, we firstly propose an active learning-aided entropy-tunable automatic modulation identification (AL-aided ET-AMI) scheme based on convolution neural network (CNN) model for a PCS-based coherent optical system. An AL-based neural network allows monitoring of the link rate and signal-to-noise ratio (SNR) with tuning entropy or optical power fluctuation. The proposed ALaided ET-AMI scheme is demonstrated over a 350 ∼ 550-Gbps line rate 10-km dual-polarized coherent optical communication system at entropies from 3.5 to 5.5. When the entropy tuning step is 0.1, corresponding to a rate tuning step of 5 Gbps at 50 Gbaud, the recognition accuracy can reach 98% with data aggregation (DA). When the fluctuation of SNR is 1 dB, the recognition rate can reach 87% at an entropy of 4.5 over 400 samples. The verifications show that our proposed AL-aided ET-AMI solution can monitor the rate and SNR performance of PCS-based high-speed rateflexible optical links well. The solution provides a new perspective and tool for future optical systems and network monitoring.

Multi-Agent and Cooperative Deep Reinforcement Learning for Scalable Network Automation in Multi-Domain SD-EONs

The service provisioning in multi-domain software-defined elastic optical networks (SD-EONs) is an interesting but difficult problem to tackle, because the basic problem of lightpath provisioning, i.e., the routing and spectrum assignment (RSA), is <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathcal {NP}$ </tex-math></inline-formula> -hard, and each domain is owned and operated by a different carrier. Therefore, even though numerous RSA heuristics have been proposed, there does not exist a universal winner that can always achieve the lowest blocking probability in all the scenarios of a multi-domain SD-EON. This motivates us to revisit the inter-domain provisioning problem in this paper by leveraging deep reinforcement learning (DRL). Specifically, we propose DeepCoop, which is an inter-domain service framework that uses multiple cooperative DRL agents to achieve scalable network automation in a multi-domain SD-EON. DeepCoop employs a DRL agent in each domain to optimize intra-domain service provisioning, while a domain-level path computation element (PCE) is introduced to obtain the sequence of the domains to go through for each lightpath request. By sharing a restricted amount of information among each other, the DRL agents can make their decisions distributedly. To ensure scalability and universality, we design the action space of each DRL agent based on well-known RSA heuristics, and architect the agents based on the soft actor-critic (SAC) scenario. We run extensive simulations to evaluate DeepCoop, and the results show that DeepCoop can adapt to the dynamic environment in a multi-domain SD-EON to always select the best RSA heuristic for minimizing blocking probability, and it outperforms the existing algorithms on inter-domain provisioning in various scenarios. Moreover, we verify that the distributed training implemented in DeepCoop ensures its universality and scalability (i.e., its training and operation do not depend on the topology of the SD-EON).

Highly-Efficient and Automatic Spectrum Inspection Based on AutoEncoder and Semi-Supervised Learning for Anomaly Detection in EONs

To closely monitor the performance of lightpaths in an elastic optical network (EON), people need to rely on real-time and fine-grained spectrum monitoring. This, however, will generate tremendous telemetry data, which can put great pressure on both the control and data planes. In this work, we design and experimentally demonstrate AutoSpecheck, which is a DL-assisted network automation (DLaNA) system that can realize highly-efficient and automatic spectrum inspection for anomaly detection in EONs. Specifically, we architect AutoSpecheck based on the software-defined EON (SD-EON) architecture, and propose techniques to greatly reduce the loads of data reporting (in the data plane) and data analyzing (in the control plane). To reduce the loads of data reporting, we leverage the AutoEncoder (AE) technique to design a spectrum data compression method. To improve the efficiency of data analytics, we first design a coarse filtering module (CFM) to let the control plane filter out most of the normal data before invoking the DL-based anomaly detection. Then, to address the difficulty of labeling massive spectrum data, we develop a DL-based anomaly detection based on semi-supervised learning. Our experimental demonstrations consider two representative intra-channel anomalies ( i.e. , the filter drifting and in-band jamming), and the results confirm that AutoSpecheck can achieve highly-efficient and automatic spectrum inspection for anomaly detection in EONs.

Joint multi-dimensional resource allocation algorithm for a TWDM/OFDM-PON-based software-defined elastic optical access network

Abstract With the rapid growth of high-bandwidth services such as 5G, access networks only rely on physical layer technology to build a large-scale rigid pipeline, but cannot meet the need for the intelligent, flexible, and open networks of future business. Therefore, we herein propose a fairness-aware joint multi-dimensional resource allocation algorithm. It is based on software-defined elastic optical access network architecture and is intended to improve network throughput and the quality of service users experience. The simulation results show that the network throughput and user satisfaction rate of the proposed algorithm increases by about 30% during peak traffic periods compared with fixed allocation. The proposed algorithm can ensure that all users utilize the system bandwidth fairly.

Recent research progress on spectrum management approaches in software-defined elastic optical networks

The flex-grid technology or elastic optical network (EON) is accepted to be a propitious solution for the future transport network due to its unique properties, which are bandwidth aggregation that creates super wavelength channels, different data rate accommodation, bandwidth segmentation that creates sub-wavelength channels, and elastic variation of assigned bandwidth. The software-defined network (SDN) is incorporated with the emerging technology of EON for enhancing its performance by enabling dynamic provisioning and releasing of optical lightpaths. This reduces the required time for lightpath control, which leads to improve the network performances. This paper exploits the software-defined elastic optical network (SD-EON) by identifying its architectures, existing literature, resource management approaches, and future challenges. In addition, the performance of EONs related to the SDN technology is compared in terms of blocking probability. Numerical results indicate that the SD-EON accommodates 25% more admissible traffic than the EON without considering SDN, when the acceptable blocking probability is considered 0.01.

Build to Tenants’ Requirements: On-Demand Application-Driven vSD-EON Slicing

Application-driven networks (ADNs) aim to build logically separate virtual networks (VNs) to meet the distinct demands of different applications. In this paper, we study how to realize the on-demand slicing of application-driven virtual software-defined elastic optical networks (vSD-EONs) based on the concept of ADN. We design the network system for on-demand application-driven vSD-EON slicing and demonstrate the building and operating of application-driven vSD-EONs with it experimentally. Specifically, our experimental demonstrations consider three scenarios: (1) the tenant's application requires high availability for the data plane, (2) the tenant's application is interactive and thus requires short end-to-end latency, and (3) the tenant's application needs an enhanced physical-layer security guarantee. With an experimental testbed that consists of commercial optical transmission facilities, bandwidth-variable wavelength-selective switches, erbium-doped fiber amplifiers, and high-performance servers with both optical and electrical ports, we verify that the proposed vSD-EON slicing system can build vSD-EONs on-demand according to tenants' application demands and operate them correctly.

SDN Enabled Restoration With Triggered Precomputation in Elastic Optical Inter-Datacenter Networks

Flexi-grid elastic optical networks (EONs) provide a promising infrastructure for meeting the high-bandwidth and low-latency requirements of interconnecting datacenters. Since failures of high-capacity fiber links prevent users from accessing cloud services and lead to large amounts of data loss, much recent research has focused on inter-datacenter network failure recovery. In this paper, we build upon software-defined networking (SDN) technology and develop a fast restoration strategy with triggered precomputation (FR-TP) that achieves fast failure recovery with minimal resource overhead. Our work makes several contributions. We extend the controller functionality and OpenFlow protocol for software-defined elastic optical inter-datacenter network architectures, so as to obtain the global network state information quickly and accurately. We then present the FR-TP strategy and an associated trigger mechanism to compute backup paths before a link failure occurs. Furthermore, to improve the efficiency of path computation and bandwidth resource assignment, we construct a layered auxiliary graph of spectrum window planes (SWP-LAG) using a residual capacity matrix to change dynamically the width of the spectrum window planes (SWPs) to satisfy different service requests. Simulation results demonstrate that, compared with existing restoration strategies, the proposed FR-TP strategy combined with SWP-LAG reduces the recovery time by up to 30.4% in the network topologies studied without increasing the blocking probability.

Experimental demonstration of an intelligent control plane with proactive spectrum defragmentation in SD-EONs.

The cooperation of software-defined networking and flexible grid optical transport technology allows operators to elastically control the network using software running on a network operating system within a centralized way. However, existing approaches dealing with spectrum fragmentation are mostly the reactive strategy, which reconfigures network resources to overcome spectrum fragmentation when the controller detects the fragmentation. In this paper, we focus on how to improve the control plane intelligence of software-defined elastic optical networks (SD-EONs) by using a proactive strategy. More specifically, we design a novel routing, modulation level and spectrum allocation algorithm (RMLSA) based on spectral efficiency and connectivity (SEC) i.e., SEC-RMLSA, in order to improve the utilization efficiency of network resources. Meanwhile, we develop a routing application and an extended OpenFlow protocol to achieve a seamless operation between the controller and the optical data plane. Moreover, all the proposed methodologies are implemented and demonstrated in an SD-EON testbed that has both OpenFlow-based control plane and data plane. Finally, the proposed framework, experimental demonstration, and numerical evaluation are reported for different optical flows. The results show the system's overall feasibility and efficiency.

Multibroker-Based Service Provisioning in Multidomain SD-EONs: Why and How Should the Brokers Cooperate With Each Other?

It is known that software-defined elastic optical networks (SD-EONs) facilitate optical networking that provides better network programmability, more powerful manageability, and more flexible service provisioning capability. Moreover, the hierarchical architecture of multibroker-based multidomain SD-EONs cannot only improve the network scalability but also maintain the autonomy of each administrative domain. In this paper, we study why and how the brokers should cooperate with each other to provision interdomain lightpaths in multibroker-based multidomain SD-EONs. We first formulate a cooperative market in which the brokers negotiate about their market shares (i.e., the opportunities to provision interdomain lightpaths) and seek for a mutual agreement with Nash bargaining [1] . Then, we design a mathematical model to describe the market as well as the brokers’ behaviors in it. An effective algorithm is derived from the model to solve the Nash bargaining problem for allocating lightpath requests among the brokers. The proposed algorithm also addresses the resource collision during request provisioning and can achieve collision-free request allocation. Extensive simulations verify the effectiveness of our proposal.

Experimental demonstration of building and operating QoS-aware survivable vSD-EONs with transparent resiliency.

Software-defined elastic optical networks (SD-EONs) provide operators more flexibility to customize their optical infrastructures dynamically. By leveraging infrastructure-as-a-service (IaaS), virtual SD-EONs (vSD-EONs) can be realized to further enhance the adaptivity of SD-EONs and shorten the time-to-market of new services. In this paper, we design and demonstrate the building and operating of quality-of-service (QoS) aware survivable vSD-EONs that are equipped with transparent data plane (DP) resiliency. Specifically, when slicing a vSD-EON, our network hypervisor (NHV) chooses to use "1:1" virtual link (VL) protection or on-demand VL remapping as the DP restoration scheme, according to the service-level agreement (SLA) between the vSD-EON's operator and the infrastructure provider (InP). Then, during an actual substrate link (SL) failure, the NHV realizes automatic DP restoration that is transparent to the controllers of vSD-EONs. We build a network testbed to demonstrate the creation of QoS-aware survivable vSD-EONs, the activation of lightpaths in the vSD-EONs to support upper-layer applications, and the automatic and simultaneous QoS-aware DP restorations during an SL failure. The experimental results indicate that our vSD-EON slicing system can build QoS-aware survivable vSD-EONs on-demand, operate them to set up lightpaths for carrying real application traffic, and facilitate differentiated DP restorations during SL failures to recover the vSD-EONs' services according to their SLAs.

Spectrum-space-divided spectrum allocation approaches in software-defined elastic optical networks

Recently, the architecture of elastic optical network (EON) has been proposed as a candidate solution to accommodate both huge bandwidth requirements and flexible connections in next generation optical networks. In order to improve the spectrum efficiency, we propose different spectrum-space-divided approaches and develop two integer linear programming (ILP) models and several spectrum-space-divided spectrum allocation approaches with and without dedicated-path protection in software-defined elastic optical networks (SD-EONs). Simulation results show that the ILP models achieve better performance in terms of the number of frequency slots and hop counts than the proposed spectrum-space-divided spectrum allocation approaches with and without dedicated-path protection under the static scenario of connection requests. Furthermore, we apply the spectrum-space-divided spectrum allocation approaches with and without dedicated-path protection to reduce the blocking probability and to improve spectrum efficiency under the dynamic connection requests compared to the traditional first-fit spectrum allocation approach in SD-EONs.

Energy-Efficient Survivable Grooming in Software-Defined Elastic Optical Networks

Survivability in the OpenFlow-based software-defined elastic optical networks (SD-EONs) are more challenging than that in the conventional optical networks because failures can affect control plane operations. Meanwhile, traffic grooming is enabled by sliceable transponders can reduce power consumption and obtain higher spectrum efficiency. In this paper, we study the survivable grooming routing and spectrum allocation in SD-EON. First, provide an integer linear programming formulation to minimize both the required transponders and the maximum number of occupied frequency slots. Then, we develop a heuristic algorithm called shared backup path grooming protection (SBPGP) to get enough protection and less resources consumption. Extensive simulations are performed to study the power consumption of optical elements in data plane. Numerical results show that the proposed SBPGP scheme achieves better performances than the traditional shared backup path protection without grooming.

Virtual infrastructure mapping in software-defined elastic optical networks

Software-defined networking (SDN) enables efficient and scalable network virtualization, which allows infrastructure resources such as computing and networking resources to be abstracted and outsou...

Incentive-Driven Bidding Strategy for Brokers to Compete for Service Provisioning Tasks in Multi-Domain SD-EONs

It is known that the multi-broker-based management plane can potentially provide a realistic solution to facilitate incentive-driven cross-domain network orchestration in multi-domain software-defined elastic optical networks (SD-EONs). Such network orchestration assures the autonomy of each domain and supports economical service provisioning across multiple domains as well. In this study, we consider the economic principle in multi-broker-based multi-domain SD-EONs and study how to realize incentive-driven service provisioning with broker competitions. We first present the theoretical model of the network operations to describe the noncooperative game in which the brokers compete for interdomain provisioning tasks with only incomplete information on their competitors. Then, we analyze the Nash equilibrium in a simplified version of the game, and show that to maximize the brokers’ profits in long-term repeated games, an effective bidding strategy is needed for the brokers to predict their competitors’ behaviors and price their services in the optimal way. The bidding strategy is designed by leveraging the kernel density estimation scheme. Finally, to demonstrate the effectiveness of the proposed bidding strategy, we implement it in an OpenFlow-based multi-domain SD-EON control plane testbed. The experimental results verify that our system performs well and the brokers can obtain higher profits with the proposed bidding strategy in repeated games.

Survivable Control Plane Establishment With Live Control Service Backup and Migration in SD-EONs

It is known that software-defined elastic optical networks (SD-EONs) are programmable and application-aware. However, due to the centralized network control and management, SD-EONs are vulnerable to the network failures that can affect control plane operations. In this paper, we study the problem of survivable control plane establishment (SCPE), i.e., the controller placement and related communication planning for control service backup and migration to protect the control plane of an SD-EON against single node failures. We first propose a novel mutual backup model to improve the survivability of the control plane with high protection efficiency. An integer linear programming (ILP) model is then formulated to solve the SCPE problem with the objective to minimize both the number of deployed OpenFlow controllers (OF-Cs) and the average control channel latency. We also propose a time-efficient heuristic and use simulations to verify that it can obtain similar solutions to those of the ILP. On top of the theoretical investigation, we design and implement the system to facilitate live control service backup and migration with SCPE in an SD-EON control plane testbed. Experimental results demonstrate that the proposed scheme works efficiently, and compared with that using a single OF-C, our scheme achieves much shorter average provisioning latency in dynamic provisioning.

Control plane innovations to realize dynamic formulation of multicast sessions in inter-DC software-defined elastic optical networks

It is known that to support the applications such as datacenter backup and migration, multicast should be supported efficiently in inter-datacenter (inter-DC) networks to carry the corresponding point-to-multiple-point communications. Moreover, due to the traffic dynamics in inter-DC networks, we might have to consider the case that the multicast members can join or leave a multicast session dynamically. Therefore, in this work, we try to leverage control plane innovations to realize dynamic formulation of multicast sessions in inter-DC software-defined elastic optical networks (SD-EONs), which are equipped with multicast-incapable bandwidth-variable wavelength selective switches (MI-BV-WSS'). Here, one key issue to address is that the continuous changing of multicast group members can degrade the optimality of a multicast-tree. Hence, we propose to rearrange the multicast-trees adaptively to reduce their spectrum usage. Meanwhile, we try to minimize the frequency of rearrangements to avoid unnecessary operation complexity. Based on these considerations, we propose several multicast-tree rearrangement algorithms for updating multicast sessions dynamically with lightpath reroutings in inter-DC SD-EONs. Both partial and full multicast-tree rearrangements are studied. Simulation results indicate that the proposed algorithms can rearrange the multicast-trees intelligently such that the blocking probability can be reduced effectively with the least lightpath reroutings. Next, based on these theoretical investigations, we consider how to implement the proposed algorithms in the control plane of an inter-DC SD-EON. We extend the OpenFlow (OF) protocol to support the dynamic formulation of multicast sessions and also design the functional models in the control plane elements to realize multicast-tree rearrangements. Experiment results verify the effectiveness of our proposed algorithms and system design.

Fragmentation-aware service provisioning for advance reservation multicast in SD-EONs.

In this paper, we study the service provisioning schemes for dynamic advance reservation (AR) multicast requests in elastic optical networks (EONs). We first propose several algorithms that can handle the service scheduling and routing and spectrum assignment (RSA) of AR multicast requests jointly, including an integrated two-dimensional fragmentation-aware RSA (2D-FMA) that can alleviate the 2D fragmentation caused by light-tree provisioning. Then, we leverage the idea of software-defined EONs (SD-EONs) that utilizes OpenFlow (OF) in the control plane to demonstrate and evaluate the proposed algorithms. Specifically, we build an SD-EON control plane testbed, implement the algorithms in it, and perform control plane experiments on dynamic AR multicast provisioning. The results indicate that 2D-FMA achieves the best blocking performance and provides the shortest average setup delay.

Flexible Availability-Aware Differentiated Protection in Software-Defined Elastic Optical Networks

Availability-aware service provisioning tries to satisfy the availability requirements of clients on demand and can improve the resource efficiency in optical networks. This paper studies the problem of flexible availability-aware differentiated protection (ADP) in elastic optical networks (EONs). We first consider the unique features in EONs, e.g., flexible spectrum allocation and bandwidth-squeezed protection, describe the problem of ADP, and present a theoretical analysis on service availability. Then, we develop an ADP algorithm that can change the path protection scheme to adapt to different service availability requirements. An availability-aware backup reprovisioning strategy is also proposed as a supplement of the ADP algorithm to further improve the protection efficiency. We also discuss the system design for OpenFlow-based software-defined EON (SD-EON) framework to facilitate the ADP scheme. Finally, to demonstrate the overall design, we construct an SD-EON control plane testbed that consists of 14 standalone nodes, implement the proposed algorithms in the OpenFlow controller, and perform experiments to evaluate their performance. The results indicate that the system performs well, and the proposed algorithms can reduce blocking probability effectively without sacrificing the service availability of requests.

Availability-aware service provisioning in SD-EON-based inter-datacenter networks

The tremendous transmission capacity and flexible spectrum allocation scheme make elastic optical networks (EONs) one of the most promising infrastructures for constructing the interconnection in datacenter (DC) networks. Meanwhile, as DC traffics exhibit highly dynamic and heterogeneous features, differentiated service provisioning schemes are desired. In this paper, we take the advantage of centralized network control and management provided by the software-defined elastic optical networks (SD-EONs) and investigate availability-aware service provisioning in SD-EON-based inter-datacenter (inter-DC) networks. We first describe the problem of availability-aware service provisioning in SD-EON-based inter-DC networks and present the theoretical analysis for service availability. Then, we propose an availability-aware service provisioning algorithm (ASP) that leverages different path protection schemes to satisfy different service availability requirements. A service downgrading (SD) strategy is also designed as a supplement of ASP to further improve its performance. Simulation results show that the proposed ASP-SD algorithm can effectively improve the spectrum efficiency without sacrificing availability.

Leveraging master-slave OpenFlow controller arrangement to improve control plane resiliency in SD-EONs.

In this paper, we study how to improve the control plane resiliency of software-defined elastic optical networks (SD-EONs) and design a master-slave OpenFlow (OF) controller arrangement. Specifically, we introduce two OF controllers (OF-Cs), i.e., the master and slave OF-Cs, and make them work in a collaborative way to protect the SD-EON against controller failures. We develop a controller communication protocol (CCP) to facilitate the cooperation of the two OF-Cs. With the CCP, the master OF-C (M-OF-C) can synchronize network status to the slave OF-C (S-OF-C) in real time, while S-OF-C can quickly detect the failure of M-OF-C and take over the network control and management (NC&M) tasks timely to avoid service disruption. We implement the proposed framework in an SD-EON control plane testbed built with high-performance servers, and perform NC&M experiments with different network failure scenarios to demonstrate its effectiveness. Experimental results indicate that the proposed system can restore services in both the data and control planes of SD-EON jointly while maintaining relatively good scalability. To the best of our knowledge, this is the first demonstration that realizes control plane resiliency in SD-EONs.