Large Optical Networks Research Articles

Multi-core shared tree based MP2MP RWA algorithms in large scale and multi-domain optical networks

The increasing demands of bandwidth-intensive parallel computing and collaborative applications, efficient service provisioning to support multipoint to multipoint (MP2MP) communications have attracted increasing attention. However, with the development of larger-scale and multi-domain optical networks, MP2MP RWA are introduced optimal domain sequence selection and core nodes belong to which domains problems which cannot be tackled by the conventional algorithms proposed aim at a signal domain. In this paper, we proposed a multi-core node shared multicast tree heuristic algorithm (MCSMT) which calculation could be parallelized, delay and minimal cost constrained for multi-domain optical networks. It could realize the accurate calculation of minimum number of cores and the hosted domains of the cores. The source and destination nodes were added in different shared trees respectively with delay constrained algorithms according to specific QoS selection strategy. At the same time, according to more complicated MP2MP algorithms we propose a PCE-cloud based control architecture for optical networks by applying the cloud computing technology (e.g. virtualization and parallel computing) to reform the control plane for improving system reliability, intelligence and maximizing resource utilization. The performances of the proposed heuristic with regard to the number of multi-core nodes, wavelength channel occupied and MP2MP setup latency are compared. In addition, the performance about path computing latency for PCE-cloud control architecture is compared with conversional control architecture.

Graph model for multiple scattering in lithium niobate on insulator integrated photonic networks

We present a graph-based model for multiple scattering of light in integrated lithium niobate on insulator (LNOI) networks, which describes an open network of single-mode integrated waveguides with tunable scattering at the network nodes. We first validate the model at small scale with experimental LNOI resonator devices and show consistent agreement between simulated and measured spectral data. Then, the model is used to demonstrate a novel platform for on-chip multiple scattering in large-scale optical networks up to few hundred nodes, with tunable scattering behaviour and tailored disorder. Combining our simple graph-based model with material properties of LNOI, this platform creates new opportunities to control randomness in large optical networks.

Hierarchical Reinforcement Learning in Multi-Domain Elastic Optical Networks to Realize Joint RMSA

To improve the network scalability, a large elastic optical network is typically segmented into multiple autonomous domains, where each domain possesses high autonomy and privacy. This architecture is referred to as the multi-domain elastic optical network (MDEON). In the MDEON, the routing, modulation, and spectrum allocation (RMSA) for the inter-domain service requests are challenging. As a result, deep reinforcement learning (DRL) has been introduced recently where the RMSA policies are learned during the interaction of the DRL agents with the MDEON environment. Due to the autonomy of each domain in the MDEON, joint RMSA is essential to improve the overall performance. To realize the joint RMSA, we propose a hierarchical reinforcement learning (HRL) framework which consists of a high-level DRL module and multiple low-level DRL modules (one for each domain), with the collaboration of DRL modules. More specifically, for the inter-domain service requests, the high-level module obtains some abstracted information from the low-level DRL modules and generates the inter-domain RMSA decision for the low-level modules. Then the low-level DRL module gives the intra-domain RMSA decision and feeds back to the high-level module. The proposed HRL framework preserves the autonomy of each single domain while delivering effective overall network performance through the cooperation of the high-level and low-level DRL modules. Simulation results demonstrate that our proposed method outperforms previous approaches.

Long-distance distribution of qubit-qubit entanglement using Gaussian-correlated photonic beams

We investigate the deterministic generation and distribution of entanglement in large quantum networks by driving distant qubits with the output fields of a nondegenerate parametric amplifier. In this setting, the amplifier produces a continuous Gaussian two-mode squeezed state, which acts as a quantum-correlated reservoir for the qubits and relaxes them into a highly entangled steady state. Here we are interested in the maximal amount of entanglement and the optimal entanglement generation rates that can be achieved with this scheme under realistic conditions taking, in particular, the finite amplifier bandwidth, waveguide losses, and propagation delays into account. By combining exact numerical simulations of the full network with approximate analytic results, we predict the optimal working point for the amplifier and the corresponding qubit-qubit entanglement under various conditions. Our findings show that this passive conversion of Gaussian into discrete-variable entanglement offers a robust and experimentally very attractive approach for operating large optical, microwave, or hybrid quantum networks, for which efficient parametric amplifiers are currently developed.

Smart Algorithms for Hierarchical Clustering in Optical Network

Network design process is a very important in order to balance between the investment in the network and the supervises offered to the network user, taking into consideration, both minimizing the network investment cost, on the other hand, maximizing the quality of service offered to the customers as well.Partitioning the network to smaller sub-networks called clusters is required during the design process inorder to ease studying the whole network and achieve the design process as a trade-off between several atrtributes such as quality of service, reliability,cost, and management. Under CANON, a large scale optical network is partitioned into a number of geographically limited areas taking into account many different criteria like administrative domains, topological characteristics, traffic patterns, legacy infrastructure etc. An important consideration is that each of these clusters is comprised of a group of nodes in geographical proximity. The clusters can coincide with administrative domains but there could be many cases where two or more clusters belong to the same administrative domain. Therefore, in the most general case the partitioning into specific clusters can be either a off-line or a on-line process. In this work only the off-line case is considered. In this Study, we look at the problem of designing efficient 2- level Hierarchical Optical Networks (HON), in the context of network costs optimization. 2-level HON paradigm only have local rings to connect disjoint sets of nodes and a global sub mesh to interconnect all the local rings. We present an Hierarchical algorithm that is based on two phases. We present results for scenarios containing a set of real optical topologies.

Strategies for training optical neural networks

Optical neural networks have great potential to process information efficiently with the speed of light. Compared with electronic competitors, multiple tasks have been successfully demonstrated in such computing systems with several orders of magnitude improvement in energy consumption. However, current training strategies, as a critical step for bringing optical neural networks into reality, are still at an early stage. The high complexity and long training time fail to meet the requirement for training optical neural networks massively and efficiently. Therefore, appropriate training strategies are still in great demand for future deployment of large scale optical neural networks. In this paper, we investigate current training approaches and the possible paths which could make optical neural networks highly expressive and realistic are also discussed.

Blockchain-Anchored Disaggregated Optical Networks

Optical network disaggregation is attracting significant consensus to avoid vendor lock-in solutions. However, the presence of network controllers, nodes, and hardware/software components potentially provided by different entities and manufacturers may lead to remarkable responsibility issues in case of service level degradation. We propose the use of the blockchain technology to provide reliable and trusted accountability of events and interactions among disaggregated network elements. Three levels of interactions are specifically considered: <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i)</i> among SDN controllers, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ii)</i> between each SDN controller and the underlying network nodes, and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">iii)</i> within disaggregated network nodes. The proposed solutions have been implemented and experimentally validated in a disaggregated network testbed. Results show the effectiveness of the method even in case of controversial service level degradation upon failure events. Results also show good scalability performance to retrieve/add/validate blocks recorded in the blockchain even in case of large optical network scenarios.

Hardware error correction for programmable photonics

Programmable photonic circuits of reconfigurable interferometers can be used to implement arbitrary operations on optical modes, providing a flexible platform for accelerating tasks in quantum simulation, signal processing, and artificial intelligence. A major obstacle to scaling up these systems is static fabrication error, where small component errors within each device accrue to produce significant errors within the circuit computation. Mitigating this error usually requires numerical optimization dependent on real-time feedback from the circuit, which can greatly limit the scalability of the hardware. Here we present a deterministic approach to correcting circuit errors by locally correcting hardware errors within individual optical gates. We apply our approach to simulations of large scale optical neural networks and infinite impulse response filters implemented in programmable photonics, finding that they remain resilient to component error well beyond modern day process tolerances. Our results highlight a potential way to scale up programmable photonics to hundreds of modes with current fabrication processes.

Statistical Benchmarking of Scalable Photonic Quantum Systems.

Targeting at the realization of scalable photonic quantum technologies, the generation of many photons, their propagation in large optical networks, and a subsequent detection and analysis of sophisticated quantum correlations are essential for the understanding of macroscopic quantum systems. In this experimental contribution, we explore the joint operation of all mentioned ingredients. We benchmark our time-multiplexing framework that includes a high-performance source of multiphoton states and a large multiplexing network, together with unique detectors with high photon-number resolution, readily available for distributing quantum light and measuring complex quantum correlations. Using an adaptive approach that employs flexible time bins, rather than static ones, we successfully verify high-order nonclassical correlations of many photons distributed over many modes. By exploiting the symmetry of our system and using powerful analysis tools, we can analyze correlations that would be inaccessible by classical means otherwise. In particular, we produce on the order of ten photons and distribute them over 64 modes. Nonclassicality is verified with correlation functions up to the 128th order and statistical significances of up to 20 standard deviations.

Activities of PMO optical space debris survey

Space debris division of PMO is devoted to play an important role in the research of orbital mechanics and the development of space debris observation techniques in China. To support the work, this division builds and operates a large optical network across China. The observational network include two major subsets, large field survey telescopes and precise tracking telescopes. The main objective of the network is to maintain cataloged orbital debris and detect uncatalogued debris. CHES at YaoAn site is the most recent facility, for higher orbits survey. New operational software and data pipeline that aims at detecting unresolved objects has being developed. This paper presents the details of this facility and related activities.

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.

A Comparative Evaluation of Nature Inspired Algorithms for Telecommunication Network Design

The subject of the study was an application of nature-inspired metaheuristic algorithms to node configuration optimization in optical networks. The main objective of the optimization was to minimize capital expenditure, which includes the costs of optical node resources, such as transponders and amplifiers used in a new generation of optical networks. For this purpose a model that takes into account the physical phenomena in the optical network is proposed. Selected nature-inspired metaheuristic algorithms were implemented and compared with a reference, deterministic algorithm, based on linear integer programming. For the cases studied the obtained results show that there is a large advantage in using metaheuristic algorithms. In particular, the evolutionary algorithm, the bees algorithm and the harmony search algorithm showed superior performance for the considered data-sets corresponding to large optical networks; the integer programming-based algorithm failed to find an acceptable sub-optimal solution within the assumed maximum computational time. All optimization methods were compared for selected instances of realistic teletransmission networks of different dimensions subject to traffic demand sets extracted from real traffic data.

Smart Algorithms for Hierarchical Clustering in Optical Network

Network design process is a very important in order to balance between the investment in the network and the supervises offered to the network user, taking into consideration, both minimizing the network investment cost, on the other hand, maximizing the quality of service offered to the customers as well.Partitioning the network to smaller sub-networks called clusters is required during the design process inorder to ease studying the whole network and achieve the design process as a trade-off between several atrtributes such as quality of service, reliability,cost, and management. Under CANON, a large scale optical network is partitioned into a number of geographically limited areas taking into account many different criteria like administrative domains, topological characteristics, traffic patterns, legacy infrastructure etc. An important consideration is that each of these clusters is comprised of a group of nodes in geographical proximity. The clusters can coincide with administrative domains but there could be many cases where two or more clusters belong to the same administrative domain. Therefore, in the most general case the partitioning into specific clusters can be either a off-line or a on-line process. In this work only the off-line case is considered. In this Study, we look at the problem of designing efficient 2- level Hierarchical Optical Networks ( HON ), in the context of network costs optimization. 2-level HON paradigm only have local rings to connect disjoint sets of nodes and a global sub mesh to interconnect all the local rings. We present an Hierarchical algorithm that is based on two phases. We present results for scenarios containing a set of real optical topologies.

Strict-sense nonblocking networks with k degrees of freedom

In this paper we extended the well known conditions for strict-sense nonblocking operation of the three-stage Clos switching network to the case in which k multiplexing levels (called later in this paper as k degrees of freedom) are used on input, output, and interstage links. Up till now only the cases with one multiplexing level were considered in the literature—time-division or wavelength-division. Current research shows that transmission systems with many multiplexing levels will be used in the future to increase available transmission speed in telecommunication networks. There will be also a need for switching connecting paths going through such multiplexed links in large capacity optical cross-connect systems, routers, or data center networks. In this paper we proved the strict-sense nonblocking conditions for the three-stage Clos network with k degrees of freedom. We also analyzed the cost of switching fabrics of selected capacities and with three degrees of freedom in terms of the required number of elements.

Resource efficient multicast traffic grooming in WDM mesh networks

In this paper, we have considered an optimal design and provisioning of WDM networks for the grooming of sub-wavelengths traffic requests. As higher layer electronic ports, such as transceivers and optical splitters are dominant cost factors of an optical network, it is essential to reduce their numbers of use while grooming the multicast traffic requests into high bandwidth light-trees. This paper provides an optimal cost design of WDM networks with multicast traffic grooming under static traffic demand. We develop a unified framework for the optimal provisioning of different practical scenarios of multicast traffic grooming in a static traffic scenario. In this study, we design an Integer linear Programming (ILP) formulation for multicast traffic grooming to minimize the cost associated with the higher layer electronic ports such as transceivers, splitters and wavelengths, and simultaneously maximize the bandwidth utilization of the network. We propose a heuristic algorithm called Efficient Light-Tree based Multicast Traffic Grooming (ELT-MTG) algorithm to achieve scalability in large size optical networks. Simulations are conducted on several standard well-known WDM mesh networks to study the design cost (based on number of transceivers, optical splitters and wavelengths) used in the networks. The result, thus obtained by comparison, helped us to conclude that the proposed approach ELT-MTG gives better performance than well-known existing logical-first sequential routing with single-hop grooming (LFSEQSH) and logical-first sequential routing with multi-hop grooming (LFSEQMH) algorithms in a static traffic environment.

A Review of Various Algorithms Used toOptimize RWA Problem in WDM Network

Wavelength Division Multiplexing (WDM) is expected to be a popular technique for constructing large optical networks interconnecting a large number of nodes. With suitable optical cross connects (OXC) at the nodes, such a network will allow very flexible switching of the various wavelengths and light-paths between the active sourcedestination pairs. This flexibility in routing will make these networks easy to configure and operate and will also improve the reliability of the network by providing easy-to-set-up alternate paths in case of node and link failures. This paper discuss various nature inspired algorithms to optimize the RWA problem WDM network where traffic conditions are static or may change dynamically as a wavelength assignment problem. Aim of the algorithms explained in this paper is to reduce blocking probability, increase throughput and make the network more efficient for communication.

Experimental demonstration of large capacity WSDM optical access network with multicore fibers and advanced modulation formats.

Towards the next generation optical access network supporting large capacity data transmission to enormous number of users covering a wider area, we proposed a hybrid wavelength-space division multiplexing (WSDM) optical access network architecture utilizing multicore fibers with advanced modulation formats. As a proof of concept, we experimentally demonstrated a WSDM optical access network with duplex transmission using our developed and fabricated multicore (7-core) fibers with 58.7km distance. As a cost-effective modulation scheme for access network, the optical OFDM-QPSK signal has been intensity modulated on the downstream transmission in the optical line terminal (OLT) and it was directly detected in the optical network unit (ONU) after MCF transmission. 10 wavelengths with 25GHz channel spacing from an optical comb generator are employed and each wavelength is loaded with 5Gb/s OFDM-QPSK signal. After amplification, power splitting, and fan-in multiplexer, 10-wavelength downstream signal was injected into six outer layer cores simultaneously and the aggregation downstream capacity reaches 300 Gb/s. -16 dBm sensitivity has been achieved for 3.8 × 10-3 bit error ratio (BER) with 7% Forward Error Correction (FEC) limit for all wavelengths in every core. Upstream signal from ONU side has also been generated and the bidirectional transmission in the same core causes negligible performance degradation to the downstream signal. As a universal platform for wired/wireless data access, our proposed architecture provides additional dimension for high speed mobile signal transmission and we hence demonstrated an upstream delivery of 20Gb/s per wavelength with QPSK modulation formats using the inner core of MCF emulating a mobile backhaul service. The IQ modulated data was coherently detected in the OLT side. -19 dBm sensitivity has been achieved under the FEC limit and more than 18 dB power budget is guaranteed.

A New Traffic Engineering Algorithm to Simplify Network in Optical Switching Network

With the explosive growth of optical network dimensioning [1] and the call of traffic, the network traffic is becoming more and more imbalanced. When some links are busy and have congestion, some others are idle for long time. This paper proposes a theory which simplifies a complex optical network into an equivalent easy one using the bandwidth of the optical link. and we call this theory TDBB. For the large capacity optical switching network node 1000×1000,divided in two level :the ms level 32×32 optical switching and ns level 32×32 using time division multiplexing in subcarrier wave. Every subcarrier [2] has 10G bandwidth. So we have 10T in single wave ,200T in single fiber. 10P capacity of total 50 ports. which is to say this theory can work for TE project in optical switching network which has more than 10pbs large capacity.

Quantum teleportation on a photonic chip

Quantum teleportation is a fundamental concept in quantum physics which now finds important applications at the heart of quantum technology including quantum relays, quantum repeaters and linear optics quantum computing (LOQC). Photonic implementations have largely focussed on achieving long distance teleportation due to its suitability for decoherence-free communication. Teleportation also plays a vital role in the scalability of photonic quantum computing, for which large linear optical networks will likely require an integrated architecture. Here we report the first demonstration of quantum teleportation in which all key parts - entanglement preparation, Bell-state analysis and quantum state tomography - are performed on a reconfigurable integrated photonic chip. We also show that a novel element-wise characterisation method is critical to mitigate component errors, a key technique which will become increasingly important as integrated circuits reach higher complexities necessary for quantum enhanced operation.

Experimental performance evaluation of software defined networking (SDN) based data communication networks for large scale flexi-grid optical networks.

Software defined networking (SDN) has become the focus in the current information and communication technology area because of its flexibility and programmability. It has been introduced into various network scenarios, such as datacenter networks, carrier networks, and wireless networks. Optical transport network is also regarded as an important application scenario for SDN, which is adopted as the enabling technology of data communication networks (DCN) instead of general multi-protocol label switching (GMPLS). However, the practical performance of SDN based DCN for large scale optical networks, which is very important for the technology selection in the future optical network deployment, has not been evaluated up to now. In this paper we have built a large scale flexi-grid optical network testbed with 1000 virtual optical transport nodes to evaluate the performance of SDN based DCN, including network scalability, DCN bandwidth limitation, and restoration time. A series of network performance parameters including blocking probability, bandwidth utilization, average lightpath provisioning time, and failure restoration time have been demonstrated under various network environments, such as with different traffic loads and different DCN bandwidths. The demonstration in this work can be taken as a proof for the future network deployment.