1297 results about "Optical networking" patented technology

The invention discloses an optical transmission network hidden danger detection method and device and a computer program product, which can realize dynamic adjustment of differentiated bandwidth requirements by acquiring optical network state information in real time, evaluating service priority and establishing an optical channel resource allocation model. And when a topology anomaly is detected, constructing a service quality evaluation model by using a long-short-term memory neural network, and quantitatively analyzing the influence of the anomaly on the service. When a fault occurs, distributed link fault detection and a fault diagnosis engine based on a decision tree are adopted, and fault hidden dangers are quickly positioned and classified. And then, through an elastic recovery mechanism oriented to service sensitivity, the service quality level of a standby optical path is adjusted, and an optical layer topology connection relationship is optimized. According to the method, the resource utilization efficiency, the fault recovery capability and the service quality of the optical network are remarkably improved, and an innovative solution is provided for intelligent optical network management.

The invention provides an assembly line parallel distributed training method, device and system for a deep neural network, and the method comprises the steps: sequentially transmitting each group of small-batch training data forming the current-batch training data to an edge server through an optical network, enabling the edge server to cooperate with the cloud server to perform asynchronous parallel cooperative training on different sub-task models forming the deep neural network in a communication and training decoupling mode, and outputting gradients corresponding to each group of small-batch training data in sequence by the edge server; and sequentially receiving the gradient of each group of small-batch training data. According to the invention, correct transmission of data in a model training process can be ensured, communication overhead in the training process can be reduced, load balance between devices can be realized, model training efficiency and effectiveness can be improved, and the utilization rate of resources of the devices participating in training can be increased.

A method performed by an optical network controller includes: obtaining a topology structure of a subnet of a cluster, where the topology structure records an address of compute nodes in the subnet; determining a wavelength division configuration based on the topology structure, where the wavelength division configuration is used to allocate different wavelengths to the compute nodes in the subnet; providing the wavelength division configuration for the optical network switching device. Then the optical network switching device establishes an optical path between the optical network switching device and the compute node in the subnet based on the wavelength division configuration.

The invention discloses an optical communication network route optimization method and system, particularly relates to the technical field of multi-domain optical network collaborative networking, and is used for solving the problem of path selection deviation caused by topology abstraction and simplification in an existing multi-domain optical network. Intra-domain topology compensation parameters representing potential path resource consumption in sub-domains are reversely generated by acquiring inter-domain topology abstract information of a cross-domain optical network, and a hidden link competition relationship shared by cross-domain optical paths is dynamically monitored in combination with real-time link resource data to generate a competition intensity index; evaluating a port resource consumption weight based on a compensation parameter and a competition intensity index, fusing a load state to generate an optimal port selection weight, and finally screening a global path through a weight priority and triggering an optical switching node instruction to establish a cross-domain optical path; dynamic collaborative optimization of resource consumption and competition conflicts in the multi-domain optical network is realized, the accuracy of cross-domain path selection and the global utilization rate of network resources are effectively improved, and the risks of redundancy jump and local link congestion are reduced.

Described herein are a computing systems comprising a photonic interposer having an optical network comprising a plurality of waveguides and a plurality of controllable optical switches; an electronic die having a surface bonded to the photonic interposer, an inner interface comprising a first plurality of ports electrically coupling the electronic die to the photonic interposer through the surface; and an outer interface comprising a second plurality of ports electrically coupling the electronic die to the photonic interposer through the surface, wherein the outer interface at least partially encloses the inner interface.

The invention discloses a multi-mode optical signal transmission method and device, electronic equipment and a storage medium, and relates to the technical field of computers.The transmitted data stream is divided into a control signal and a data signal, the control signal is a visible light wave band, the data signal is an infrared wave band, and the control signal and the data signal are combined to a single multi-core optical fiber through a combiner; the optical network controller allocates subcarrier resources as required according to the change of network flow in a spectrum dynamic allocation mode to perform data transmission, so that the subcarrier resource allocation adapted to the change of network flow improves the dynamic adaptability, and the allocation of the subcarrier resources as required improves the equipment cooperation efficiency, and in the data transmission process, the data transmission efficiency is improved. Clock synchronization and signal encryption are realized through a quantum key distribution mode, and the security is improved.

The invention discloses a hospital internal network security isolation method based on an all-optical network architecture. The method comprises the following steps: S1, dividing a hospital internal network into a plurality of virtual optical slices by using an all-optical network slicing technology; s2, performing time domain isolation by using an optical time domain multiplexing technology, and transmitting data on different optical wavelengths by using a wavelength selective switching technology; s3, monitoring and managing bandwidth allocation through a software defined network control platform; s4, traffic prediction and resource optimization are carried out based on a decision tree integration algorithm; s5, detecting potential anomalies and security threats by using the graph neural network; s6, abnormal behaviors are detected through an isolation forest algorithm, and abnormal traffic is marked and isolated; s7, recording a network traffic log through a block chain technology; and S8, when a network fault occurs, using an intelligent self-healing mechanism to automatically switch redundant optical path resources and recover the optical path. According to the invention, all-optical network slicing and artificial intelligence technologies are fully utilized, and security isolation and resource optimization of a hospital internal network are realized.

A computing network for space-ground collaborative detection comprises an on-satellite optical computing network and a ground electric computing network, and can directly detect and identify simple targets on a satellite, preprocess complex targets, compress the scale of mass remote sensing data and reduce on-satellite energy consumption and downloading difficulty. And for a simple target identification result and a complex target compression preprocessing result, a compression vector downloaded by an optical network is reconstructed and classified in a ground electric computing network, so that the overall accuracy of the system is improved.

In some embodiments, a system for quantum key distribution, includes a plurality of n devices pairwise connected by an optical network, where n is an integer greater than or equal to 2. The optical network comprises a set of n(n−1) channels. The system employs wavelength-multiplexing, wavelength-demultiplexing, and time-multiplexing to provide a secure quantum key between two devices.

The invention relates to the technical field of data management, and discloses a method for realizing intelligent management of an all-optical network based on big data analysis, which comprises the following steps of: acquiring operation data of the all-optical network, positioning an abnormal point location of link optical power of the all-optical network, and performing data linear repair on power data corresponding to the abnormal point location to obtain target data; analyzing wavelength characteristics of the all-optical network, analyzing signal transmission stability of optical signals of the all-optical network, and analyzing optical signal characteristics of the all-optical network based on the wavelength characteristics and the signal transmission stability; analyzing equipment operation state characteristics of the all-optical network; identifying data service types of the all-optical network, analyzing flow change rules of different service types in the data service types, and analyzing service flow periodicity characteristics of the all-optical network; and performing operation anomaly analysis on the all-optical network to obtain an operation anomaly analysis result, and constructing an intelligent management strategy of the all-optical network based on the operation anomaly analysis result. According to the invention, the operation efficiency and stability of the all-optical network can be improved.

The invention relates to an optical network routing intelligent planning method and system based on multi-objective optimization. The method comprises the following steps: performing recursive partitioning on a target optical network to obtain a plurality of sub-network units and a boundary node set; inputting the plurality of sub-network units into a three-layer deep learning model for processing to obtain a routing decision matrix and a wavelength allocation vector; inputting the plurality of sub-network units and the boundary node set into a distributed controller for processing to obtain an error compensation matrix; based on the routing decision matrix and the wavelength allocation vector, performing dual strategy processing of time delay priority and hop count priority to obtain a time delay weighted evaluation function and a hop count weighted evaluation function; performing multi-target joint optimization to obtain an optimal routing scheme; and performing reconstruction cost calculation on the optical path set according to the error compensation matrix and the optimal routing scheme, and outputting a resource reconfiguration scheme. According to the implementation of the invention, the resource overhead in the network reconstruction process is reduced, and the overall operation efficiency of the network is improved.

The embodiment of the present application provides a method, device and system for obtaining an optical network performance optimization solution and diagnosing faults. The method includes: collecting operation logs, performance indicators and alarm information of various types of equipment in the optical network according to a pre-set data collection frequency, as well as collecting optical network topology data, network-level performance data, equipment configuration information and computer room environment data; cleaning and preprocessing all collected data; inputting all processed data into a pre-trained performance optimization model, a pre-built expert system and / or a pre-trained fault prediction model, generating an optical network performance optimization solution through the performance optimization model, and predicting the potential fault type, possible fault occurrence time and fault location of the optical network through the expert system and / or the fault prediction model. The embodiment of the present application can not only obtain a better optical network performance optimization solution, but also improve the fault location speed and accuracy.

The invention discloses an electric power communication optical network routing optimization method based on a DQN model, and the method comprises the following steps: S1, collecting the information of an electric power communication optical network, and building a state space, an action space and a reward function of the electric power communication optical network routing; s2, performing offline training on the DGQN model according to the state space, the action space and the reward function to obtain a trained DGQN model; and S3, optimizing a target electric power communication optical network route according to the trained DGQN model deployment, and updating model parameters through an online learning mechanism. According to the method, the adaptive learning capability of deep reinforcement learning is utilized, so that the routing decision can dynamically adapt to the continuously changing flow load and link state in the electric power communication optical network, the defect that a traditional static routing method cannot cope with a dynamic environment is overcome, and the response speed and stability of the network are improved.

The invention relates to the technical field of optical network operation and maintenance, and particularly provides an optical network fault prediction method and system based on MEMS characteristic embedding and digital twinning, and the method comprises the steps: collecting multi-physics field coupling parameters of optical network operation in real time through an MEMS multi-physics field coupling sensing unit which is disposed at an optical network key node and is embedded in a physical layer device; constructing an optical network cross-scale digital twin, inputting parameters to realize real-time synchronization and fault rehearsal of a physical entity and a virtual mirror image, and outputting a rehearsal result; constructing a fault prediction model based on an optical network physical mechanism, inputting parameters and rehearsal results to complete feature fusion and trend analysis, and outputting a fault prediction result; an intervention strategy is generated and subjected to twinborn virtual simulation verification; and after the verification is passed, driving the physical layer to execute intervention, and feeding back effect data to dynamically update twin model parameters. A closed loop of perception, modeling, prediction, intervention and feedback is formed, and the problems of prediction lag and low operation and maintenance efficiency in the prior art are solved.

The invention relates to a resource allocation method and system for dynamic load balancing of a data center elastic optical network, and belongs to the technical field of communication. Comprising the following steps: initializing data center elastic optical network parameters, and generating a connection request; judging whether the residual computing power resources of the source node and the destination node meet the request requirement or not, if so, calculating K working paths, selecting the shortest path, calculating the number of required spectrum slots, and judging whether the paths have residual spectrum resources or not; if yes, layered traffic grooming evaluation parameters are calculated, and the optimal spectrum layer is selected for grooming traffic; if not, selecting the highest-price modulation format; judging whether bandwidth and optical channel resources on the path are enough, if so, allocating spectrum resources, otherwise, returning to select the next shortest path; judging whether the spectrum resources meet constraint conditions or not, if yes, allocating computing power resources, and requesting successfully; if not, returning to reselect the path; and after success, updating the network transmission path weight. According to the invention, the network resource waste and blocking rate are effectively reduced, and the optical network energy consumption is reduced.

The invention provides an optical network resource allocation method based on feedback iteration fusion quantum and classical calculation, which comprises the following steps of: preprocessing optical network resources by applying a heuristic algorithm, and establishing a QUBO model of a corresponding resource allocation problem: taking candidate optical paths and candidate resource information as binary logic variables, and according to constraint conditions, establishing a QUBO model of a corresponding resource allocation problem; mapping the resource allocation scheme into Hamiltonian of different sizes; and in combination with a heuristic algorithm, solving the QUBO model in a special quantum computer, and carrying out post-processing to obtain a resource allocation scheme. According to the method, characteristics of classical calculation and quantum calculation are combined, so that a distribution scheme is effectively prevented from falling into local optimum; by using the parallel computing advantage of the special quantum computer, the decision time of resource allocation is reduced, the network is ensured to have relatively low long-term blocking rate and spectrum utilization rate, the requirement of quickly and efficiently solving the optical network resource allocation problem is met, and the method is suitable for popularization and application.

The invention discloses a counting method for system terminal equipment in an NATed network based on an optical network, and belongs to the field of data communication. According to the method, Windows system terminal equipment in a home internal network is monitored and counted in real time by utilizing the high-speed transmission capability and the low-delay characteristic of an optical network; the number of the terminal devices is counted based on the change rate of the IP-ID sequence along with the arrival time of the packet, and different terminal devices are accurately distinguished by analyzing the monotonicity of the IP-ID field in the DNS request packet and the difference of the increase change rate of the IP-ID sequence between different devices. According to the invention, the number of terminal devices can be effectively identified, and the insight ability of an operator for user demands is improved, so that a more personalized service and resource allocation scheme can be provided. Meanwhile, a fixed mode algorithm is adopted, consumption of computing resources is reduced, the recognition speed is increased, the method is very suitable for the scene of recognizing the number of real-time terminal devices, and the stability and reliability of the system are further enhanced.

One or more embodiments of the invention provide an on-chip optical network node fault self-healing method and system, electronic equipment and a storage medium. The self-healing system applied to the node fault of the on-chip optical network comprises a data monitoring module, a fault detection module, a self-healing strategy determination module and a self-healing strategy operation module, and the method comprises the following steps: the data monitoring module obtains health state data of each node of the on-chip optical network; a fault detection module determines a fault node of the on-chip optical network according to the health state data; a self-healing strategy determination module determines a self-healing strategy corresponding to the on-chip optical network in response to the situation that the fault node of the optical network cannot be recovered; and the self-healing strategy operation module resets the node link of the on-chip optical network according to the self-healing strategy. According to the technical scheme, the reliability and flexibility of the network can be effectively improved.

Methods and systems are described herein for monitoring fault events at a fiber optical network. In particular, a system may receive, from components of an optical network, corresponding component data structures comprising optical measurements. The system may extract, from a component data structure, a set of component metrics for light transmission signals being transmitted or received via fiber optic transmission lines at a corresponding component and input the component data structure into a first machine learning model to obtain an indication of an occurrence of an event at one or more components. The system may generate a prompt for input into a second machine learning model configured to identify corrective actions for addressing any events within optical networks to obtain one or more corrective actions for addressing the occurrence of the event.

An optical network unit, ONU, (100) for a passive optical network, PON, comprising:a tunable receiver (110);a tunable transmitter (120); anda controller (130, 230) comprising a processor (132) and memory (134) containing instructions (136) executable by the processor whereby the ONU is operative to:if the tunable transmitter is on, switch the tunable transmitter off and if the tunable receiver is off, switch the tunable receiver on;determine a downstream control channel wavelength;set an operating wavelength of the tunable receiver to the downstream control channel wavelength;receive a downstream control channel signal at the downstream control channel wavelength from a central office, CO, node of the PON, the downstream control channel signal carrying an indication of an allocation of channel wavelengths to ONUs;obtain allocated downstream and upstream channel wavelengths for the ONU from the indication of an allocation of channel wavelengths to ONUs;set an operating wavelength of the tunable receiver to the allocated downstream channel wavelength and set the operating wavelength of the tunable transmitter to the allocated upstream channel wavelength; andswitch the tunable transmitter on.

The invention discloses a registration method and device of an optical communication network, and relates to the technical field of optical communication. The discovery window opened by the OLT is determined according to the distance between the optical relay equipment and the next-level optical network equipment of the optical relay equipment, and the OLT already configures the specified BWmap information for the optical relay equipment, so that the OLT does not need to open a larger discovery window in the registration process of the next-level optical network equipment of the optical relay equipment, and the registration efficiency of the optical relay equipment is improved. And only the discovery window matched with the next-level optical network equipment needs to be opened. Therefore, the OLT only needs to open a smaller discovery window in the discovery process of the SN, the time slot corresponding to the smaller discovery window is reduced, the service interruption time of other optical network equipment communicating with the OLT is shortened, the uplink delay jitter of an optical communication network is reduced, and the communication stability of the optical communication network is improved.

The invention discloses a smart campus Internet of Things multi-service collaborative scheduling control system based on an all-optical network, and relates to the technical field of Internet of Things, and the system comprises an Internet of Things digital platform which is in communication connection with the following modules: an all-optical network infrastructure module which is used for constructing an optical fiber backbone network in a campus, and each subsystem in the campus is accessed. The reliability and stability of the campus Internet of Things are enhanced by constructing all-optical network infrastructure, the subsystems are directly connected through optical fibers by adopting the passive optical network technology, and the use of active equipment is reduced, so that the equipment failure rate and the maintenance cost are reduced, optical wavelength resources are dynamically allocated by utilizing a software defined network controller, and the reliability and the stability of the campus Internet of Things are improved. The transmission path is adjusted according to the service priority, efficient operation of key services is ensured, network stability is improved, high speed and safety of data transmission are guaranteed, and solid network support is provided for various intelligent applications in the campus.

The invention provides a multiband dynamic optical network transmission optimization method and system, and the method comprises the steps: determining whether an optical fiber node is a compensation point or not based on a power spectrum of the optical fiber node in an unoptimized optical network; calculating a target gain curve corresponding to the compensation point based on the power spectrum corresponding to the compensation point; inputting the target gain curve into a pre-trained machine learning model, and constructing an initial pumping power vector based on an output value of the machine learning model; the method comprises the steps of performing iterative calculation on an initial pumping power vector through a plurality of iteration rounds, determining final applied pumping power, in each iteration round, determining a circulating pumping power vector based on a current iteration pumping power vector, calculating an environment difference based on the circulating pumping power vector and the initial pumping power vector, and determining the final applied pumping power according to the environment difference. A new round of iterative pump power vector is calculated based on the environmental difference, and it is determined whether the new round of iterative pump power vector corresponds to a final applied pump power.

The invention belongs to the technical field of all-optical network management, and discloses an all-optical network visual management method and system. The method comprises the following steps that: a cloud data center constructs an all-optical network digital twin model and an artificial intelligence model; the edge computing gateway is used for collecting real-time equipment operation monitoring data and extracting real-time equipment dynamic monitoring data; the edge computing gateway is used for performing equipment fault diagnosis and equipment management strategy generation by using an artificial intelligence model; the edge computing gateway encrypts and transmits the real-time equipment operation monitoring data, the real-time equipment dynamic monitoring data, the real-time equipment fault diagnosis result, the real-time equipment management strategy and the real-time alarm signal of the optical network information transmission equipment to the cloud data center; and the cloud data center is used for performing visual display by using an all-optical network digital twinborn model. According to the invention, the problems of lack of comprehensive real-time monitoring capability, insufficient fault diagnosis precision, low visualization degree and low data processing efficiency in the prior art are solved.

The invention provides an optical network multi-modal data fusion and alarm identification method and device, and relates to the technical field of data processing, and the method comprises the steps: collecting multi-modal alarm data from an optical network, and inputting the multi-modal data into a multi-modal Transform model; the multi-modal Transform model fuses the data of different modals by using position embedding, cross-modal attention and self-attention mechanisms to obtain fused multi-modal data; and inputting the fused multi-modal data into a DNN model, and outputting an alarm identification result of the optical network.

A coolant distribution manifold assembly for use in a module or circuit pack of an optical networking system, including: a body defining a main inlet port at one end, a main outlet port at another end, and a plurality of cooling plate inlet ports and cooling plate outlet ports disposed between the main inlet port and the main outlet port; where the body further defines an upper internal plenum and a lower internal plenum each coupled to one of the main inlet port and the plurality of cooling plate inlet ports and the main outlet port and the plurality of cooling plate outlet ports. Optionally, the upper internal plenum and the lower internal plenum each have a variable cross-sectional area along a length of the body between the main inlet port and the main outlet port.

The invention discloses an optical network dynamic resource allocation method fused with an AI large model, which relates to the technical field of real-time scheduling of network resources, and comprises the following steps: constructing a service prediction model based on terminal behavior characteristics, calculating bandwidth sensitivity Bs and burst probability Pt, generating priority weight Wp, and improving burst service scheduling response; the T-CONT allocation rate and period are adjusted in a self-adaptive mode through a resource allocation efficiency function Ef and a buffer area demand index Bh, and priority scheduling of key services is guaranteed; the scheduling pressure is judged by introducing double thresholds of a signaling overhead index So and a network congestion degree Oc, AI reestimation and resource reallocation are triggered when abnormity occurs, and meanwhile, a bandwidth recovery parameter Br is recorded to optimize a subsequent strategy, so that minute-level intelligent scheduling and resource utilization maximization are realized.

The invention relates to an optical network topology dynamic adjustment method and system, computer equipment, a medium and a product. The method comprises the following steps: acquiring a computing resource association degree parameter according to equipment resource allocation information, acquiring a data transmission delay parameter according to global topology information of a network topology structure, and transmitting the data transmission delay parameter to a computing node under the condition that communication activity data generated by computing equipment of each computing node in a target iteration process passes verification, acquiring a communication traffic matrix according to the communication activity data, acquiring actual communication traffic according to the communication traffic matrix and the global topological information, acquiring a network load balancing parameter according to the actual communication traffic, and acquiring an evaluation function value based on a computing resource association degree parameter, a data transmission delay parameter and the network load balancing parameter; and according to the evaluation function values corresponding to all the network topology structures, determining a target network topology structure, and adjusting the optical connection path to realize optical network topology adjustment. By adopting the method, the network performance can be improved.

The invention provides an intelligent spectrum allocation method and system for a self-adaptive signal-to-noise ratio of a C + L optical network, and relates to the technical field of optical fiber communication, and the method comprises the steps: initializing a C + L wave band elastic optical network, and determining nodes, links, spectrum slots and time slot resources; receiving a service request, and defining a source node, a destination node, time slot requirements and capacities; calculating a link weight according to a transmission distance and spectrum occupation, and selecting an optimal path; determining a modulation format according to the path distance, and calculating a required spectrum gap; high-order modulation is allocated to a C wave band, and low-order modulation is allocated to an L wave band; ensuring that spectrum slots are continuous and links are consistent, otherwise, the request fails; and selecting the spectrum block distribution with the highest OSNR, comparing the OSNR with a threshold value, and determining whether the request is successful or not. According to the invention, the transmission quality of the service request is improved, and resource allocation can be carried out more comprehensively and accurately.

The invention provides an optical network conflict detection method and device and a storage medium, relates to the technical field of communication, and is used for identifying a target optical network unit causing coexistence conflicts. The method is applied to an optical line terminal, the optical line terminal accesses a first passive optical network and a second passive optical network, and the method comprises the following steps: in response to detecting that a first coexistence conflict feature exists, stopping uplink transmission of an optical network unit in the second passive optical network; when it is detected that the second coexistence conflict feature exists, uplink transmission of the optical network unit in the second passive optical network is recovered according to a preset strategy, and whether the first coexistence conflict feature exists or not is detected again; wherein the coexistence conflict degree represented by the second coexistence conflict feature is smaller than the coexistence conflict degree represented by the first coexistence conflict feature; and under the condition that the existence of the first coexistence conflict feature is detected again, determining that the optical network unit which recovers uplink transmission last time is a target optical network unit which causes the coexistence conflict.