Low-power-consumption long-distance 400G coherent optical module intelligent scheduling and optimizing system

Abstract

The invention discloses an intelligent scheduling and optimizing system for a low-power-consumption long-distance 400G coherent optical module, and relates to the technical field of optical communication, and the system comprises a link performance monitoring and predicting unit which monitors the parameters of the optical module in real time, predicts the link performance, and constructs a performance data link; the monitoring node configuration unit is used for analyzing transmission target parameters and configuring multi-gradient monitoring nodes according to distances; the parameter compensation unit compensates the parameters of the optical module based on the performance data chain and the monitoring node to generate a compensation data chain; and the optimization and scheduling optimization unit is used for optimizing regulation and control parameters by taking minimum power consumption and maximum stability as targets based on the compensation data chain and generating a scheduling scheme. Therefore, the technical effects of dynamically adjusting and optimizing transmission parameters of the optical module, reducing power consumption and improving transmission stability are achieved.

Description

Technical Field

[0001] The present invention relates to the field of optical communication technologies, and particularly to an intelligent scheduling and optimization system for low-power long-distance 400G coherent optical modules. Background Art

[0002] In long-distance transmission scenarios, optical modules not only need to meet the requirements of high-speed transmission but also achieve low power consumption and high energy efficiency. Currently, link monitoring and adjustment optimization for high-speed optical modules mainly rely on basic monitoring devices and preset parameter adjustment mechanisms. On the one hand, some systems monitor link performance changes through fixed thresholds but lack in-depth data mining and prediction means for link performance data. On the other hand, existing transmission task scheduling schemes basically adopt static configuration strategies and cannot flexibly configure monitoring nodes and perform dynamic parameter compensation according to multiple factors such as real-time road conditions, distance, and power consumption. In addition, in terms of parameter compensation and scheduling optimization, most also rely on simple algorithms or empirical models and it is difficult to simultaneously achieve the dual goals of minimizing power consumption and maximizing transmission stability, resulting in the regulation effect and energy consumption performance of the system not reaching the ideal level when facing complex or long-distance transmission environments. Summary of the Invention

[0003] The present invention provides an intelligent scheduling and optimization system for low-power long-distance 400G coherent optical modules to solve the technical problems in the prior art of single link performance monitoring and compensation mechanisms and difficulty in simultaneously achieving low power consumption and high transmission stability, and to achieve the technical effects of dynamically adjusting and optimizing the transmission parameters of optical modules, reducing power consumption, and improving transmission stability.

[0004] The intelligent scheduling and optimization system for low-power long-distance 400G coherent optical modules provided by the present invention includes: A link performance monitoring and prediction unit, configured to monitor optical module parameters in real time through optical module components, predict link performance according to the optically monitored module parameters in real time, and construct a link performance data chain.

[0005] A monitoring node configuration unit, configured to analyze the transmission target parameters of a transmission task and configure multi-gradient monitoring nodes according to the distance of the transmission task.

[0006] A parameter compensation unit, configured to perform optical module parameter compensation according to the link performance data chain, the transmission target parameters, and their multi-gradient monitoring nodes to obtain a compensation data chain.

[0007] An optimization and scheduling optimization unit, configured to perform optimization of regulation parameters based on the compensation data chain with the goals of minimizing power consumption and maximizing transmission stability to obtain an optimized parameter scheduling scheme.

[0008] In a feasible implementation manner, the link performance monitoring and prediction unit includes: A performance change trend prediction subunit, where the optical module parameters include temperature, voltage, transmitted optical power, received optical power, and bias current, and is used to use the optical module parameters as input parameters, and perform performance change trend prediction through a performance prediction module fitted with historical data to obtain performance prediction data corresponding to the prediction time frequency.

[0009] A link performance data chain construction subunit, which is used to concatenate the performance prediction data according to the time series relationship to construct the link performance data chain.

[0010] In a feasible implementation manner, the monitoring node configuration unit includes: A transmission task parameter acquisition subunit, which is used to acquire the transmission distance, transmission time, transmission data type, and data volume of the transmission task.

[0011] A bandwidth requirement and maximum tolerable delay analysis subunit, which is used to analyze the bandwidth requirement and maximum tolerable delay according to the transmission distance, transmission time, transmission data type, and data volume.

[0012] A node spacing calculation subunit, which is used to calculate the node spacing according to the transmission performance of the optical module channel and the transmission distance.

[0013] A multi-gradient monitoring node division subunit, which is used to divide the transmission distance according to the node spacing to obtain multiple gradient monitoring nodes.

[0014] In a feasible implementation manner, calculating the node spacing according to the transmission performance of the optical module channel and the transmission distance, the execution steps of the node spacing calculation subunit include: According to the transmission performance of the optical module channel, calculate the fiber attenuation relationship of the channel transmission performance with respect to the transmission distance to obtain the transmission attenuation coefficient.

[0015] Calculate the node spacing according to the transmission distance, transmission attenuation coefficient, and combined with the initial OSNR data.

[0016] In a feasible implementation manner, obtaining multiple gradient monitoring nodes, the execution steps of the multi-gradient monitoring node division subunit further include: Establish a long-distance transmission path according to the transmission starting point and transmission destination of the transmission task.

[0017] Perform cross-regional geographical transmission network difference analysis according to the long-distance transmission path to obtain network difference nodes.

[0018] Add gradient monitoring nodes according to the network difference nodes.

[0019] In a feasible implementation manner, the parameter compensation unit includes: A performance parameter trend chart building subunit, configured to build a performance parameter trend chart according to the link performance data chain.

[0020] A demand data trend chart construction subunit, configured to build a demand data trend chart according to the transmission target parameters and their multi-gradient monitoring nodes, and configure a node compensation space according to the node attributes and performance characteristics of the gradient monitoring nodes.

[0021] A supply-demand difference obtaining subunit, configured to align the performance parameter trend chart with the demand data trend chart to obtain a supply-demand difference.

[0022] A compensation data chain generating subunit, configured to perform compensation positioning fusion on the supply-demand difference by using the node compensation space to obtain the compensation data chain.

[0023] In a feasible implementation manner, performing compensation positioning fusion on the supply-demand difference by using the node compensation space to obtain the compensation data chain, and the execution steps of the compensation data chain generating subunit include: Performing difference projection according to the correspondence between the supply-demand difference and the transmission position to obtain a demand difference data chain.

[0024] Compensating the channel performance parameters of the node position according to the node compensation space of the gradient node to obtain compensation parameters.

[0025] Performing corresponding demand compensation adjustment according to the position positioning relationship between the gradient node and the demand difference data chain, and reconstructing the demand data of the nodes in the demand difference data chain to obtain the compensation data chain.

[0026] In a feasible implementation manner, configuring a node compensation space according to the node attributes and performance characteristics of the gradient monitoring node, and the execution steps of the demand data trend chart construction subunit include: Identifying the node attributes of the gradient monitoring node, where the node attributes include network difference nodes and attenuation distance nodes.

[0027] When the node attribute is the network difference node, identifying the fiber optic terrain type and service provider rules of the node.

[0028] Performing performance change analysis according to the fiber optic terrain type and service provider rules, and configuring the node compensation space according to the performance change relationship of the gradient node.

[0029] In a feasible implementation manner, the optimization and scheduling optimization unit includes: A compensation position positioning analysis subunit, configured to perform compensation position positioning analysis according to the compensation data chain to obtain a compensation variable that affects node spectrum resource scheduling.

[0030] The compensation relationship establishing subunit is used to establish a compensation relationship according to the adjustment influence relationship between the compensation variable and the channel transmission performance.

[0031] The compensation evaluation function establishing subunit is used to perform power consumption evaluation and transmission stability evaluation based on the compensation relationship and establish a compensation evaluation function.

[0032] The optimized parameter scheduling scheme generation subunit is used to search the spectrum resource allocation strategy and its channel control parameters for each compensation demand in the compensation data link according to the compensation evaluation function with the goal of minimizing power consumption and maximizing transmission stability, and obtain the optimized parameter scheduling scheme. The optimized parameter scheduling scheme is the spectrum resource allocation strategy and its channel control parameters with the highest compensation evaluation result when the search end condition is met.

[0033] In a feasible implementation, the compensation variables include: physical layer compensation parameters and network layer compensation parameters, wherein the physical layer compensation parameters include power, modulation format, signal gain, dispersion compensation, and redundancy; and the network layer compensation parameters include wavelength, path, node sleep policy, and network service provider selection.

[0034] The present invention discloses a low-power, long-distance 400G coherent optical module intelligent scheduling and optimization system, comprising: a link performance monitoring and prediction unit, which monitors optical module parameters in real time and predicts link performance, and builds a performance data chain; a monitoring node configuration unit, which parses transmission target parameters and configures multi-gradient monitoring nodes according to distance; a parameter compensation unit, which compensates optical module parameters based on the performance data chain and the monitoring node, and generates a compensation data chain; a search and scheduling optimization unit, which optimizes and controls parameters based on the compensation data chain with minimum power consumption and maximum stability as the goals, and generates a scheduling plan. The low-power, long-distance 400G coherent optical module intelligent scheduling and optimization system disclosed in the present invention solves the technical problems of a single link performance monitoring and compensation mechanism and difficulty in taking into account both low power consumption and high transmission stability, and realizes the dynamic adjustment and optimization of optical module transmission parameters, reducing power consumption and improving transmission stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 This is a structural schematic diagram of the low-power, long-distance 400G coherent optical module intelligent scheduling and optimization system of the present invention.

[0036] Figure 2 It is a schematic diagram of the execution steps of the compensation data link generation subunit in the low-power long-distance 400G coherent optical module intelligent scheduling and optimization system of the present invention.

[0037] Explanation of the reference numerals: link performance monitoring and prediction unit 11 , monitoring node configuration unit 12 , parameter compensation unit 13 , optimization and scheduling optimization unit 14 . DETAILED DESCRIPTION

[0038] The above technical solutions will be described in detail below in combination with the accompanying drawings of the specification and specific implementation manners to better understand the above technical solutions. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments of the present invention. It should be understood that the present invention is not limited to the example embodiments only used to explain the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention. In addition, it should be noted that for the sake of convenience of description, only the parts related to the present invention are shown in the drawings, rather than all of them.

[0039] Embodiment Figure 1 is a schematic structural diagram of the intelligent scheduling and optimization system for a low-power long-distance 400G coherent optical module of the present invention. Among them, the intelligent scheduling and optimization system for the low-power long-distance 400G coherent optical module includes: A link performance monitoring and prediction unit 11, configured to monitor optical module parameters in real time through an optical module component, predict link performance according to the optical module parameters monitored in real time, and construct a link performance data chain.

[0040] Specifically, the function of the link performance monitoring and prediction unit is to obtain the key parameters of the optical module (such as temperature, voltage, transmitted optical power, received optical power, bias current, etc.) in real time through an optical module component (such as an optical power meter, a temperature sensor, a bias current monitor, etc.), and then perform dynamic prediction of link performance. Among them, the link performance data chain is a dynamic and continuous performance data structure formed by connecting the predicted performance data in a time series relationship for subsequent parameter compensation and optimized scheduling.

[0041] Specifically, first, the key parameters of the optical module are collected in real time through an optical module component (such as an optical power meter, a temperature sensor, etc.). For example, during operation, the temperature sensor records the internal temperature of the module every 1 second, and the optical power meter records the transmitted optical power and the received optical power every 5 seconds. Then, based on the collected optical module parameters, the change trend of the link performance is calculated and predicted through algorithms such as trend analysis. For example, by analyzing the temperature change trend of the optical module in the past 10 minutes, the temperature change situation in the next 5 minutes is predicted. The prediction results are connected in a time series relationship to form a link performance data chain.

[0042] Exemplarily, assume that the transmitted optical power data of the optical module in a certain time period is: 10mW, 9.8mW, 9.6mW, 9.4mW. Through prediction by a linear regression model, the transmitted optical power in the next 5 minutes may drop to 9.2mW, 9.0mW, 8.8mW. Connecting the above prediction data in a time series can form a link performance data chain for subsequent parameter compensation and optimized scheduling.

[0043] In some embodiments, the link performance monitoring and prediction unit 11 includes: A performance change trend prediction subunit, where the optical module parameters include temperature, voltage, transmitted optical power, received optical power, and bias current, and is configured to use the optical module parameters as input parameters, and perform performance change trend prediction through a performance prediction module fitted with historical data to obtain performance prediction data corresponding to the prediction time frequency; a link performance data chain construction subunit, configured to concatenate the performance prediction data according to the time series relationship to construct the link performance data chain.

[0044] Specifically, the optical module parameters real-time monitored by the optical module component at least include temperature, voltage, transmitted optical power, received optical power, and bias current. Through the above-mentioned various optical module parameters, the state change and potential performance fluctuation of the optical module during the entire operation cycle can be reflected.

[0045] Specifically, taking the collected optical module parameters as the input of the performance prediction module fitted with historical data, corresponding performance prediction data can be obtained. The performance prediction data is a string of discrete performance values at a fixed time interval. Based on the timestamp or output order, the above-mentioned performance prediction data can be serially arranged into a link performance data chain according to the time series relationship. The data in the link performance data chain has a strict time sequence relationship.

[0046] Specifically, to fit historical data and obtain a performance prediction module, first, key parameters (such as temperature, voltage, transmitted optical power, etc.) are extracted from the historical operation records of the optical module and sorted according to the time series to form a data form consistent with the optical module parameters; then, feature extraction is performed on the collected data. Exemplarily, such as calculating the average value, change rate, fluctuation range, etc. of the parameters to capture the internal law of the data; further, a suitable fitting method (such as linear regression, time series analysis, neural network, etc.) is selected, and the selected fitting model is fitted and trained with historical data to learn the feature change pattern in the feature extraction result, and the prediction accuracy of the model is evaluated by means of cross-validation or leaving out a validation set, and the model parameters are optimized to obtain the performance prediction module.

[0047] Through the collaborative work of the performance change trend prediction subunit and the link performance data chain construction subunit, the optical module parameters are real-time collected, and the link performance data chain is generated through the trend prediction module, thereby providing a reliable data basis for subsequent parameter compensation and optimized scheduling, enabling the system to perform dynamic adjustment based on high-accuracy performance data, compensate before problems occur, and ensure transmission stability while optimizing power consumption performance.

[0048] The monitoring node configuration unit 12 is used to parse the transmission target parameters of the transmission task and configure multi-gradient monitoring nodes according to the distance of the transmission task.

[0049] Specifically, the multi-gradient monitoring nodes refer to the monitoring points divided on the transmission path according to certain rules and distances, which are used to monitor the link performance in real time and perform parameter compensation. Among them, the multi-gradient monitoring nodes are determined based on the transmission target parameters of the transmission task. That is to say, the higher the requirements corresponding to the transmission target parameters of the transmission task, the closer the distance between the nodes of the multi-gradient monitoring nodes can be, so as to ensure that the requirements of higher transmission target parameters can be met on the entire transmission path.

[0050] Optionally, the transmission target parameters include transmission distance, transmission time, transmission data type, and data volume, etc. Among them, the transmission distance includes the optical path distance and the actual physical distance of the link, the transmission time corresponds to the required transmission delay, the transmission data type is 400G coherent optical signal, and the data volume corresponds to the total transmission volume of a single transmission task, such as the size of a single data packet.

[0051] In some embodiments, the monitoring node configuration unit 12 includes: A transmission task parameter acquisition subunit, which is used to acquire the transmission distance, transmission time, transmission data type, and data volume of the transmission task; a bandwidth requirement and maximum tolerable delay parsing subunit, which is used to parse the bandwidth requirement and maximum tolerable delay according to the transmission distance, transmission time, transmission data type, and data volume; a node spacing calculation subunit, which is used to calculate the node spacing according to the transmission performance of the optical module channel and the transmission distance; a multi-gradient monitoring node division subunit, which is used to divide the transmission distance according to the node spacing to obtain multiple gradient monitoring nodes.

[0052] Specifically, first, the transmission task parameter acquisition subunit extracts key parameters such as transmission distance, transmission time, transmission data type, and data volume from the transmission task. For example, the transmission distance is 1000 kilometers, the transmission time is 5 minutes, the data type is 400G coherent optical signal, and the data volume is 100GB, and verifies whether the extracted parameters are complete and accurate to ensure the reliability of subsequent calculations; then, the bandwidth requirement and maximum tolerable delay parsing subunit calculates the required bandwidth according to the transmission data volume and transmission time. For example, if it takes 5 minutes to transmit 100GB of data, the bandwidth requirement is: ; At the same time, according to the transmission distance and the propagation speed of the optical signal, the maximum tolerable delay is calculated. For example, the propagation speed of the optical signal in the optical fiber is about 200,000 kilometers per second, and the delay for transmitting 1000 kilometers is 0.005 seconds (i.e., 5 milliseconds).

[0053] Specifically, the node spacing calculation subunit further calculates the transmission attenuation according to the optical fiber attenuation coefficient and the transmission distance, and correspondingly defines the node spacings of multiple gradient monitoring nodes. In other words, the node spacing corresponds to the transmission distance when the transmission attenuation does not meet the preset model requirements (i.e., the transmission attenuation amount reaches the preset threshold).

[0054] Further, the multi-gradient monitoring node division subunit divides the 1000-kilometer transmission path into gradient monitoring nodes (the starting point does not need to be monitored), and configures monitoring devices on each monitoring node to ensure real-time monitoring of the link performance and parameter compensation.

[0055] Through the above process, the key parameters of the transmission task can be accurately obtained, providing reliable data support for subsequent bandwidth demand and delay calculation. Based on the bandwidth demand and maximum tolerable delay analysis subunit and the node spacing calculation subunit, the distribution of monitoring nodes can be dynamically adjusted according to the specific requirements of the transmission task, ensuring efficient performance monitoring and compensation under different transmission distances and conditions, and providing monitoring support for the low power consumption and high transmission stability of the system.

[0056] In some implementation manners, the node spacing is calculated according to the transmission performance and transmission distance of the optical module channels. The execution steps of the node spacing calculation subunit include: According to the transmission performance of the optical module channels, calculate the relationship between the channel transmission performance and the optical fiber attenuation with the transmission distance to obtain the transmission attenuation coefficient; according to the transmission distance and the transmission attenuation coefficient, combined with the initial OSNR data, calculate the node spacing.

[0057] Specifically, the initial OSNR refers to the optical signal-to-noise ratio of the optical module at the transmission starting point, which is used to quantify the quality of the starting optical signal.

[0058] Specifically, when the optical signal is transmitted in the optical fiber, the optical signal will continuously attenuate as the transmission distance increases, and the relationship between the transmission distance and the optical signal attenuation can usually be represented by an exponential attenuation model, that is, the optical signal attenuates exponentially with the transmission distance, and the transmission attenuation coefficient is the constant in the above exponential attenuation model. The transmission attenuation coefficients of optical module channels with different transmission performances are different. Optionally, the transmission attenuation coefficient can be determined through transmission experiments or fitting analysis based on historical data.

[0059] Specifically, according to the transmission distance and the transmission attenuation coefficient, combined with the initial OSNR data, calculate the node spacing d, and the calculation formula is as follows: ; Among them, D total is the transmission distance, k is the transmission attenuation coefficient,OSNR initial is the initial OSNR data (initial optical signal-to-noise ratio).

[0060] By calculating and obtaining the node spacing through the above process, it is ensured that after the optical signal is transmitted through the defined node spacing length, the OSNR is still above the lowest level allowed by the system.

[0061] In some implementations, obtaining multiple gradient monitoring nodes, the execution steps of dividing the multi-gradient monitoring nodes into sub-units further include: Establish a long-distance transmission path according to the transmission starting point and destination of the transmission task; perform cross-regional analysis of the differences in the regional transmission network according to the long-distance transmission path to obtain network difference nodes; add gradient monitoring nodes according to the network difference nodes.

[0062] Specifically, the long-distance transmission path refers to the complete transmission route from the starting point to the destination of the transmission task. The differences in the regional transmission network refer to the differences in fiber type, network topology structure, service provider rules, etc. in different regions. According to the above differences, network difference nodes can be identified, that is, the key points on the transmission path where the transmission performance changes due to regional network differences.

[0063] Specifically, in the long-distance transmission path, when cross-regional transmission occurs, there may be changes in network specifications, which may lead to a relationship between the transmission distance and signal attenuation that does not conform to the previously defined one, such as an increase in attenuation or the introduction of additional signal attenuation points (factors). Therefore, it is necessary to analyze and identify the nodes with differences (network parameter changes) accordingly (i.e., network difference nodes), and set the obtained network difference nodes as the added gradient monitoring nodes to avoid missing and omitting monitoring.

[0064] Exemplarily, assume that the starting point of the transmission task is A, the destination is B, and the transmission distance is 1000 kilometers. After establishing a long-distance transmission path from Beijing to Shanghai according to the topological connection relationship of the optical fiber line, it is found through analysis that the low-attenuation optical fiber (attenuation coefficient 0.18 dB / km) is used for the section from A to the intermediate point C, and the standard optical fiber (attenuation coefficient 0.22 dB / km) is used for the section from C to B. In addition, the service provider rules at C limit the maximum transmission power, so C can be correspondingly identified as a network difference node because the fiber type and service provider rules change at this node, and a gradient monitoring node is added at C to monitor and compensate for the performance changes at this node.

[0065] The parameter compensation unit 13 is used to perform optical module parameter compensation according to the link performance data chain according to the transmission target parameters and its multi-gradient monitoring nodes to obtain a compensation data chain.

[0066] In some embodiments, the parameter compensation unit 13 includes: A performance parameter trend chart building subunit, configured to build a performance parameter trend chart according to the link performance data chain; a demand data trend chart construction subunit, configured to build a demand data trend chart according to the transmission target parameter and its multi-gradient monitoring nodes, and configure a node compensation space according to the node attributes and performance characteristics of the gradient monitoring nodes; a supply-demand difference obtaining subunit, configured to perform supply-demand alignment on the performance parameter trend chart and the demand data trend chart to obtain a supply-demand difference; and a compensation data chain generating subunit, configured to perform compensation positioning fusion on the supply-demand difference by using the node compensation space to obtain the compensation data chain.

[0067] Specifically, the performance parameter trend chart refers to a change trend chart of optical module parameters drawn according to the data in the link performance data chain in time or distance sequence. The demand data trend chart refers to a change trend chart of optical module parameter requirements drawn according to the transmission target parameter and its multi-gradient monitoring nodes.

[0068] Specifically, the node compensation space refers to an adjustment range reserved for parameter compensation on each monitoring node according to the node attributes and performance characteristics, such as a signal strength adjustment space determined according to the signal strength limit of the location. The compensation data chain refers to a dynamic and continuous compensation data structure formed by connecting the compensated performance data in time and distance sequences.

[0069] Specifically, by aligning (including the time dimension and the node dimension) and comparing the performance parameter trend chart with the demand data trend chart, and identifying the gaps at the corresponding nodes, the supply-demand difference can be obtained, that is, the difference between the predicted transmission performance (optical signal parameters) and the transmission target parameter at different nodes, so as to perform corresponding compensation.

[0070] Specifically, since environmental factors in different regions will affect the signal transmission of optical fibers, it is necessary to perform adaptive compensation (i.e., compensation positioning fusion) on the supply-demand difference through the compensation data chain generating subunit in combination with the node compensation space. For example, in plateau and mountainous areas affected by PMD (polarization mode dispersion in single-mode optical fibers), an additional 2 dB needs to be added to the original signal compensation amount. Optionally, the obtained compensation data chain includes the compensation amounts required for multiple optical signal compensation components performing signal compensation in the long-distance transmission path at different time nodes, so as to ensure that the signals at the multi-gradient monitoring nodes meet the requirements.

[0071] Each sub-unit of the above-mentioned parameter compensation unit can accurately identify the performance gap through the comparison of the performance parameter trend chart and the demand data trend chart, and perform compensation at key nodes to ensure that the optical module parameters meet the transmission target requirements. The generation of the compensation data chain enables the system to dynamically adjust the optical module parameters during the transmission process, perform compensation at multi-gradient monitoring nodes, timely solve the performance problems in the transmission, and ensure the stability and reliability of the transmission.

[0072] In some implementation manners, such as Figure 2 shown, the supply-demand difference is compensated and located and fused by using the node compensation space to obtain the compensation data chain. The execution steps of the compensation data chain generation sub-unit include: Performing difference projection according to the corresponding relationship between the supply-demand difference and the transmission position to obtain a demand difference data chain; compensating the channel performance parameters of the node position according to the node compensation space of the gradient node to obtain compensation parameters; performing corresponding demand compensation adjustment according to the position positioning relationship between the gradient node and the demand difference data chain, and reconstructing the demand data of the nodes in the demand difference data chain to obtain the compensation data chain.

[0073] Optionally, first, extract the supply-demand difference of each node from the supply-demand difference acquisition sub-unit, and project the supply-demand difference onto the transmission path according to the corresponding relationship between the supply-demand difference and the transmission position to form a demand difference data chain; then, obtain the node compensation space of each gradient node, and calculate the compensation parameter corresponding to each node by combining the node compensation space and the supply-demand difference. For example, the compensation space of node A is ±1.0 mW, and according to the difference of +0.5 mW, the compensation parameter is +0.5 mW. Here, the node compensation space defines the adjustable range of each gradient node, that is, it reflects the compensation ability of each gradient node, and at the same time ensures that the compensation result after execution meets the regulations in the area where the gradient node is located (such as the signal strength upper limit requirement, etc.); further, according to the position positioning relationship between the gradient node and the demand difference data chain, adjust the demand data according to the compensation parameter at the compensation position of each node, reconstruct the demand difference data chain, and generate the compensation data chain.

[0074] The above-mentioned compensation data chain generation process can accurately determine the compensation position and compensation value of each node through the combination of difference projection and node compensation space, ensuring the accuracy and effectiveness of the compensation. Among them, the generation of the compensation data chain enables the system to accurately and dynamically adjust the optical module parameters during the transmission process, adapt to the performance changes on the transmission path, and at the same time ensure the low-power operation of the system.

[0075] In some implementation manners, according to the node attributes and performance characteristics of the gradient monitoring node, configure the node compensation space. The execution steps of the demand data trend chart construction sub-unit include: Perform node attribute recognition on the gradient monitoring node. The node attributes include network difference nodes and attenuation distance nodes. When the node attribute is a network difference node, identify the fiber optic terrain type and service provider rules of the node. Perform performance change analysis based on the fiber optic terrain type and service provider rules, and configure the node compensation space according to the performance change relationship of the gradient node.

[0076] Specifically, the node attribute refers to the characteristics of the gradient monitoring node, including network difference nodes and attenuation distance nodes. The fiber optic terrain type refers to the geographical environment where the fiber optic is laid (such as mountainous areas, plains, seabed, etc.). Different terrains have different impacts on the performance of the fiber optic, and corresponding adjustments are required. The service provider rules refer to the restrictions and requirements of different network service providers on optical module parameters (such as transmit power, modulation format, etc.).

[0077] Exemplarily, in mountainous areas, the terrain undulates greatly and the construction difficulty is high, which may cause problems such as fiber optic bending and micro-bending during the laying process, and a wider power adjustment and dispersion compensation range are required; the plain environment is relatively uniform, and the impact on the fiber optic is relatively small, and the compensation requirements are relatively mild; the seabed requires extremely high transmission stability, and the compensation space is often set more conservatively while meeting strict stability requirements.

[0078] Specifically, the node compensation space is the adjustment range reserved for parameter compensation on each monitoring node determined according to the node attributes and performance characteristics. Its design goal is to enable the system to always maintain the satisfaction of transmission performance requirements by appropriately adjusting parameters such as transmit power, modulation format, signal gain, dispersion compensation, and redundancy when facing the comprehensive influence of multiple factors such as network differences, attenuation distance, and terrain environment, so as to achieve the stable operation of the entire link. Exemplarily, Table 1 shows the compensation space configuration corresponding to different node attributes: Table 1 Exemplary Node Attribute and Compensation Space Configuration Rules

[0079] The optimization and scheduling optimization unit 14 is used to perform optimization of regulation parameters based on the compensation data link with the goal of minimizing power consumption and maximizing transmission stability, and obtain an optimized parameter scheduling scheme.

[0080] In some embodiments, the optimization and scheduling optimization unit 14 includes: A compensation position location analysis subunit, which is used to perform compensation position location analysis according to the compensation data chain to obtain compensation variables that affect node spectrum resource scheduling; a compensation relationship establishment subunit, which is used to establish a compensation relationship according to the adjustment influence relationship between the compensation variables and the channel transmission performance; a compensation evaluation function establishment subunit, which is used to perform power consumption evaluation and transmission stability evaluation based on the compensation relationship and establish a compensation evaluation function; an optimization parameter scheduling scheme generation subunit, which is used to search for spectrum resource allocation strategies and their channel regulation parameters for each compensation requirement in the compensation data chain with the goal of minimizing power consumption and maximizing transmission stability according to the compensation evaluation function, and obtain the optimization parameter scheduling scheme, where the optimization parameter scheduling scheme is the spectrum resource allocation strategy and its channel regulation parameters with the highest compensation evaluation result when the search end condition is reached.

[0081] Specifically, first, the compensation position location analysis subunit analyzes the data chain according to the historical data and real-time status information corresponding to the compensation data chain, and uses predefined location algorithms or rules, such as principal component analysis or correlation analysis method, to extract compensation variables that affect scheduling, such as physical layer parameters such as power and modulation format, and network layer parameters such as wavelength and path.

[0082] Specifically, the compensation relationship establishment subunit establishes a compensation relationship between the two according to the preset adjustment influence relationship (such as a mathematical model or an empirical model) between the compensation variables obtained in the previous step and the channel transmission performance, such as exchanging the definitions of the independent variable and the dependent variable in the adjustment influence relationship.

[0083] Furthermore, according to the established compensation relationship, power consumption evaluation is performed for each candidate scheduling scheme, that is, the expected energy consumption under each scheme is calculated; at the same time, the transmission stability is evaluated, considering key indicators such as link quality, bit error rate, and signal-to-noise ratio; finally, different evaluation indicators are integrated (for example, based on weighted summation) to form a compensation evaluation function; preferably, this compensation evaluation function can be expressed as a multi-objective optimization function with the goals of "minimizing power consumption and maximizing transmission stability".

[0084] Furthermore, in combination with an optimization algorithm (such as a genetic algorithm, a particle swarm algorithm, or other heuristic search algorithms), the spectrum resource allocation strategy and channel regulation parameters are globally or locally searched with the compensation evaluation function as the objective function; during the search process, the comprehensive compensation evaluation results of each candidate scheme are evaluated and the optimal record is continuously updated; until the search end condition (such as a predetermined number of searches, the evaluation results converge, or a certain performance index is met), the spectrum resource allocation strategy with the highest compensation evaluation result during the optimization process and its corresponding channel regulation parameters are output as the final optimization parameter scheduling scheme.

[0085] By collaborating with each sub-unit of the optimization and scheduling optimization unit 14, the compensation data link information is dynamically and accurately analyzed to capture the resource scheduling requirements of key nodes in the link; a corresponding compensation relationship is established, and an evaluation function is constructed with power consumption and transmission stability as the main optimization objectives; an optimization algorithm is used to search for the optimal resource allocation and parameter regulation strategy, thereby achieving a comprehensive improvement in power consumption reduction and transmission efficiency.

[0086] In some implementation manners, the compensation variables include: physical layer compensation parameters and network layer compensation parameters. The physical layer compensation parameters include power, modulation format, signal gain, dispersion compensation, redundancy, and the network layer compensation parameters include wavelength, path, node sleep policy, and network service provider selection.

[0087] Specifically, the compensation variables can be further refined into physical layer compensation parameters and network layer compensation parameters. Among them, the physical layer compensation parameters include parameters such as power, modulation format, signal gain, dispersion compensation, and redundancy, which mainly reflect the physical characteristics and correction measures of the transmitted signal and can be used to adjust the device output and the optical signal transmission quality. The network layer compensation parameters include wavelength, path, node sleep policy, network service provider selection, etc., which are mainly used to optimize the network topology structure, transmission path, and node scheduling strategy to achieve dynamic resource allocation and scheduling across network domains.

[0088] In summary, the intelligent scheduling and optimization system for a low-power long-distance 400G coherent optical module provided by the present invention has the following technical effects: Through the link performance monitoring and prediction unit, the optical module parameters are monitored in real time and the link performance is predicted to construct a performance data link; the monitoring node configuration unit analyzes the transmission target parameters and configures multi-gradient monitoring nodes according to the distance; the parameter compensation unit compensates the optical module parameters based on the performance data link and the monitoring nodes to generate a compensation data link; the optimization and scheduling optimization unit optimizes and regulates the parameters with the minimum power consumption and the maximum stability as the goals based on the compensation data link to generate a scheduling plan, thereby achieving the technical effects of dynamically adjusting and optimizing the transmission parameters of the optical module, reducing power consumption, and improving transmission stability.

[0089] It should be understood that the disclosed embodiments of the present invention and the above descriptions can enable those skilled in the art to implement the present invention using the present invention. At the same time, the present invention is not limited to the above-mentioned part of the embodiments. It should be understood that those of ordinary skill in the art can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. Low-power long-distance 400G coherent optical module intelligent scheduling and optimization system, characterized by: include: A link performance monitoring and prediction unit is used to monitor the optical module parameters in real time through the optical module assembly, predict the link performance according to the optical module parameters monitored in real time, and build a link performance data link; A monitoring node configuration unit, used to parse the transmission target parameters of the transmission task and configure multi-gradient monitoring nodes according to the distance of the transmission task; A parameter compensation unit, configured to perform optical module parameter compensation according to the link performance data link, the transmission target parameter and its multi-gradient monitoring node, and obtain a compensation data link; The optimization and scheduling optimization unit is used to optimize the control parameters based on the compensation data link with the goal of minimizing power consumption and maximizing transmission stability, and obtain an optimized parameter scheduling plan.

2. The low-power long-distance 400G coherent optical module intelligent scheduling and optimization system according to claim 1 is characterized in that: Link performance monitoring and prediction unit, including: The performance change trend prediction subunit, wherein the optical module parameters include temperature, voltage, transmitted optical power, received optical power, and bias current, is used to use the optical module parameters as input parameters, perform performance change trend prediction through a performance prediction module that fits historical data, and obtain performance prediction data corresponding to the prediction time frequency; The link performance data chain construction subunit is used to connect the performance prediction data in series according to a time series relationship to construct the link performance data chain.

3. The low-power long-distance 400G coherent optical module intelligent scheduling and optimization system according to claim 1 is characterized in that: The monitoring node configuration unit includes: The transmission task parameter acquisition subunit is used to obtain the transmission distance, transmission time, transmission data type and data volume of the transmission task; A bandwidth requirement and maximum tolerable delay analysis subunit, used to analyze bandwidth requirements and maximum tolerable delay according to the transmission distance, transmission time, transmission data type and data volume; A node spacing calculation subunit is used to calculate the node spacing according to the transmission performance and transmission distance of the optical module channel; The multi-gradient monitoring node division subunit is used to divide the transmission distance according to the node spacing to obtain multiple gradient monitoring nodes.

4. The low-power long-distance 400G coherent optical module intelligent scheduling and optimization system according to claim 3 is characterized in that: According to the transmission performance and transmission distance of the optical module channel, the node spacing is calculated. The execution steps of the node spacing calculation subunit include: According to the transmission performance of the optical module channel, the optical fiber attenuation relationship between the channel transmission performance and the transmission distance is calculated to obtain the transmission attenuation coefficient; The node spacing is obtained by calculation according to the transmission distance, the transmission attenuation coefficient and the initial OSNR data.

5. The low-power long-distance 400G coherent optical module intelligent scheduling and optimization system according to claim 3 is characterized in that: A plurality of gradient monitoring nodes are obtained, and the execution step of dividing the plurality of gradient monitoring nodes into sub-units further includes: Establish a long-distance transmission path according to the transmission origin and transmission destination of the transmission task; Performing cross-regional regional transmission network difference analysis based on the long-distance transmission path to obtain network difference nodes; Gradient monitoring nodes are added according to the network difference nodes.

6. The low-power long-distance 400G coherent optical module intelligent scheduling and optimization system according to claim 5 is characterized in that: Parameter compensation unit, including: A performance parameter trend chart establishing subunit, used to establish a performance parameter trend chart according to the link performance data link; A demand data trend chart construction subunit is used to construct a demand data trend chart according to the transmission target parameters and its multi-gradient monitoring nodes, and configure the node compensation space according to the node attributes and performance characteristics of the gradient monitoring nodes; A supply-demand difference acquisition subunit is used to align the performance parameter trend chart with the demand data trend chart to obtain the supply-demand difference; The compensation data link generation subunit is used to use the node compensation space to compensate for the supply-demand difference and locate and fuse it to obtain the compensation data link.

7. The low-power long-distance 400G coherent optical module intelligent scheduling and optimization system according to claim 6 is characterized in that: The node compensation space is used to perform compensation positioning fusion on the supply-demand difference to obtain the compensation data chain. The execution steps of the compensation data chain generation subunit include: Perform differential projection according to the corresponding relationship between the supply-demand difference and the transmission position to obtain a demand differential data link; Compensating the channel performance parameters at the node position according to the node compensation space of the gradient node to obtain compensation parameters; According to the positional positioning relationship between the gradient node and the demand differential data chain, corresponding demand compensation adjustment is performed, the demand data of the nodes in the demand differential data chain is reconstructed, and the compensation data chain is obtained.

8. The low-power long-distance 400G coherent optical module intelligent scheduling and optimization system according to claim 6 is characterized in that: According to the node attributes and performance characteristics of the gradient monitoring node, the node compensation space is configured, and the execution steps of the demand data trend chart construction subunit include: Performing node attribute identification on the gradient monitoring node, wherein the node attributes include a network difference node and an attenuation distance node; When the node attribute is the network difference node, identifying the fiber terrain type and service provider rules of the node; The performance change analysis is performed according to the optical fiber terrain type and service provider rules, and the node compensation space is configured according to the performance change relationship of the gradient node.

9. The low-power long-distance 400G coherent optical module intelligent scheduling and optimization system according to claim 1, characterized in that: Optimization and scheduling optimization unit, including: A compensation position location analysis subunit, configured to perform compensation position location analysis according to the compensation data link to obtain compensation variables affecting node spectrum resource scheduling; A compensation relationship establishing subunit, used to establish a compensation relationship according to the adjustment influence relationship between the compensation variable and the channel transmission performance; A compensation evaluation function establishment subunit, used to perform power consumption evaluation and transmission stability evaluation based on the compensation relationship, and establish a compensation evaluation function; The optimized parameter scheduling scheme generation subunit is used to search the spectrum resource allocation strategy and its channel control parameters for each compensation demand in the compensation data link according to the compensation evaluation function with the goal of minimizing power consumption and maximizing transmission stability, and obtain the optimized parameter scheduling scheme. The optimized parameter scheduling scheme is the spectrum resource allocation strategy and its channel control parameters with the highest compensation evaluation result when the search end condition is met.

10. The low-power long-distance 400G coherent optical module intelligent scheduling and optimization system according to claim 9, characterized in that: The compensation variables include: physical layer compensation parameters and network layer compensation parameters, wherein the physical layer compensation parameters include power, modulation format, signal gain, dispersion compensation, and redundancy; and the network layer compensation parameters include wavelength, path, node sleep policy, and network service provider selection.

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