Method and device for detecting performance degradation of wavelength division equipment, storage medium and electronic device

Abstract

The present disclosure provides a kind of wave division equipment performance degradation detection method and device, storage medium and electronic equipment, it is related to electric communication technical field.For example, by the way of data subscription, the preliminary performance data of wave division equipment is obtained;Preliminary performance data is consumed and is compressed in real time processing, determines real-time performance data;Real-time performance data is input into the evaluation model constructed in advance, and the performance degradation information of wave division equipment is output.The present disclosure obtains the performance data of equipment by the way of data subscription, the unified processing of performance information across vendors, cross network element is carried out performance degradation analysis, and the performance degradation process is discovered in time, can solve the problem of wave division equipment operation and maintenance difficulty.

Description

Technical Field

[0001] This disclosure relates to the field of telecommunications technology, and in particular to a method and apparatus for detecting performance degradation of wavelength division multiplexing (WDM) equipment, a storage medium, and an electronic device. Background Technology

[0002] Optical fiber communication is one of the mainstream communication technologies, and fiber optic cables have been laid to cover a wide area. Wavelength division multiplexing (WDM) equipment in optical network systems is a key component of optical network communication. Therefore, monitoring the performance degradation of WDM equipment is an important means of improving the quality of optical network communication. As the operating time of WDM equipment increases, its performance gradually decreases due to material wear, fatigue, or environmental factors such as deformation, corrosion, and aging. Initially, this performance degradation may not affect the normal operation of optical communication, but in the later stages, it can have a significant impact on the safe and stable operation of the WDM equipment, and may even affect communication quality.

[0003] In existing technologies, faults are usually located through experience or by using specialized instruments. However, this approach cannot detect the process of performance degradation, resulting in long troubleshooting times and low accuracy in performance degradation detection, which in turn leads to high maintenance difficulty and low maintenance efficiency.

[0004] It should be noted that the information disclosed in the background section above is only used to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] This disclosure provides a method and apparatus for detecting performance degradation of wavelength division multiplexing (WDM) equipment, a storage medium, and an electronic device, which at least to some extent overcomes the problem of maintenance difficulties caused by the inability to detect the performance degradation process of WDM equipment in a timely manner in related technologies.

[0006] Other features and advantages of this disclosure will become apparent from the following detailed description, or may be learned in part by practice of this disclosure.

[0007] According to one aspect of this disclosure, a method for detecting performance degradation of a wavelength division multiplexing (WDM) device is provided, comprising: acquiring preliminary performance data of the WDM device through data subscription; consuming the preliminary performance data and performing real-time compression processing to determine real-time performance data; inputting the real-time performance data into a pre-built evaluation model to output performance degradation information of the WDM device.

[0008] In some embodiments, determining the preliminary performance data of the wavelength division multiplexing (WDM) device through data subscription includes: determining the monitoring points of the WDM device, issuing subscription parameters to subscribe to the performance data of the monitoring points; and obtaining the performance data of the subscribed monitoring points as the preliminary performance data of the WDM device.

[0009] In some embodiments, consuming the preliminary performance data and performing real-time compression processing to determine the real-time performance data includes: consuming the preliminary performance data to obtain consumed data; storing the consumed data in a cache; when there are missing consumed data from different devices in different wavelength division multiplexing (WDM) devices within the same time period, using consumed data with adjacent times in the cache to complete the data; merging the consumed data from different devices in different WDM devices within the same time period into one; determining whether the current consumed data is consistent with the previous merged consumed data; if the current consumed data is consistent with the previous merged consumed data, updating the timestamp of the consumed data to determine the real-time performance data.

[0010] In some embodiments, the method further includes: if the current consumption data and the previous merged consumption data are inconsistent, then the different consumption data are recorded separately to determine the real-time performance data.

[0011] In some embodiments, the pre-built evaluation model includes: acquiring historical status monitoring data of the WDM equipment; determining the standard for the normal operating status of the WDM equipment based on the historical status monitoring data, recommended values ​​from the WDM equipment manufacturer, industry standard values, and experience values ​​from maintenance personnel; selecting performance characteristic parameters that reflect the operating status of the WDM equipment based on the standard for the normal operating status of the WDM equipment, and determining the pre-built evaluation model based on machine learning.

[0012] In some embodiments, acquiring historical status monitoring data of the wavelength division multiplexing (WDM) device includes: acquiring historical status monitoring data of the WDM device through telemetry.

[0013] In some embodiments, the preliminary performance data includes: input power information and output power information.

[0014] According to another aspect of this disclosure, a performance degradation detection device for wavelength division multiplexing (WDM) equipment is also provided, comprising: a data subscription module for acquiring preliminary performance data of the WDM equipment through data subscription; a data compression module for consuming the preliminary performance data and performing real-time compression processing to determine real-time performance data; and a performance degradation evaluation module for inputting the real-time performance data into a pre-built evaluation model and outputting performance degradation information of the WDM equipment.

[0015] According to another aspect of this disclosure, an electronic device is also provided, comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to perform the wavelength division multiplexing (WDM) device performance degradation detection method described in any of the preceding claims by executing the executable instructions.

[0016] According to another aspect of this disclosure, a computer-readable storage medium is also provided, on which a computer program is stored, which, when executed by a processor, implements the wavelength division multiplexing (WDM) device performance degradation detection method described in any of the preceding claims.

[0017] According to another aspect of this disclosure, a computer program product is also provided, including a computer program that, when executed by a processor, implements the wavelength division multiplexing (WDM) device performance degradation detection method described above.

[0018] The methods, apparatus, storage media, and electronic devices for detecting performance degradation of WDM equipment provided in the embodiments of this disclosure acquire preliminary performance data of the WDM equipment through data subscription; consume the preliminary performance data and perform real-time compression processing to determine real-time performance data; input the real-time performance data into a pre-built evaluation model, and output performance degradation information of the WDM equipment. This disclosure acquires equipment performance data through data subscription, performs unified processing and performance degradation analysis of performance information across vendors and network elements, and promptly detects performance degradation processes, thus solving the problem of difficult operation and maintenance of WDM equipment.

[0019] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0020] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure. It is obvious that the drawings described below are merely some embodiments of this disclosure, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0021] Figure 1 This diagram illustrates a flowchart of a wavelength division multiplexing (WDM) device performance degradation detection method according to an embodiment of the present disclosure.

[0022] Figure 2 This is a flowchart illustrating a specific example of a wavelength division multiplexing (WDM) equipment performance degradation detection method according to an embodiment of the present disclosure;

[0023] Figure 3 This is a flowchart illustrating a specific example of a wavelength division multiplexing (WDM) equipment performance degradation detection method according to an embodiment of the present disclosure;

[0024] Figure 4 This is a flowchart illustrating a specific example of a wavelength division multiplexing (WDM) equipment performance degradation detection method according to an embodiment of the present disclosure;

[0025] Figure 5 This is a flowchart illustrating a specific example of a wavelength division multiplexing (WDM) equipment performance degradation detection method according to an embodiment of the present disclosure;

[0026] Figure 6 This diagram illustrates a performance degradation detection device for wavelength division multiplexing (WDM) equipment according to an embodiment of the present disclosure.

[0027] Figure 7 This diagram illustrates a structural block diagram of a computer device according to an embodiment of the present disclosure;

[0028] Figure 8 A schematic diagram of a computer-readable storage medium according to an embodiment of the present disclosure is shown. Detailed Implementation

[0029] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that this disclosure will be more comprehensive and complete, and will fully convey the concept of the exemplary embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0030] Furthermore, the accompanying drawings are merely illustrative of this disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0031] The specific implementation methods of the embodiments of this disclosure will now be described in detail with reference to the accompanying drawings.

[0032] Figure 1 This diagram illustrates a flowchart of a wavelength division multiplexing (WDM) device performance degradation detection method according to an embodiment of this disclosure. Figure 1 As shown, the wavelength division multiplexing (WDM) equipment performance degradation detection method provided in this embodiment includes the following steps:

[0033] S102 obtains preliminary performance data of the wavelength division multiplexing (WDM) equipment through data subscription.

[0034] It's important to note that the aforementioned data subscription refers to retrieving key business data change information from the database, packaging this information into message objects, and pushing them to Kafka for easy subscription, retrieval, and consumption by downstream businesses. Data subscription involves real-time retrieval of incremental Binlog logs from the source instance, parsing the incremental data into Kafka Messages, and then storing them on the Kafka Server. Users can consume data through the Kafka Client. As an open-source message middleware, Kafka supports multi-data-channel consumption and various SDK languages, reducing the user's learning curve.

[0035] For example, acquiring device performance monitoring points in the topology; standard NETCONF subscriptions are distributed to the box-type wavelength division multiplexing (WDM) device.

[0036] S104 consumes the initial performance data and performs real-time compression processing to determine the real-time performance data.

[0037] It should be noted that the aforementioned initial performance data consumption can be done by consuming data from the built-in Kafka. For example, in the subscription chain, the data parsed from the source database is first written to the DTS built-in Kafka, and then consumed by the client.

[0038] For example, the box-type wavelength division multiplexing (WDM) equipment pushes key performance indicator data (equivalent to the preliminary performance data mentioned above), and real-time data compression and preprocessing are used to obtain real-time performance data.

[0039] S106 inputs real-time performance data into a pre-built evaluation model and outputs performance degradation information of the wavelength division multiplexing (WDM) equipment.

[0040] This disclosure obtains device performance data through data subscription, performs unified processing of performance information across vendors and network elements, conducts performance degradation analysis, and promptly detects performance degradation processes, thus solving the problem of difficult operation and maintenance of WDM equipment.

[0041] In one embodiment of this disclosure, such as Figure 2 As shown, the wavelength division multiplexing (WDM) equipment performance degradation detection method provided in this embodiment can determine the preliminary performance data of the WDM equipment through the following steps, enabling comprehensive and timely acquisition of the preliminary performance data of the WDM equipment:

[0042] S202, determine the monitoring points of the wavelength division multiplexing equipment, and send subscription parameters to subscribe to the performance data of the monitoring points;

[0043] S204, Obtain the preliminary performance data of the wavelength division multiplexing (WDM) equipment from the reported monitoring points.

[0044] For example, in one instance, during data subscription, the master control's TELEMETRY performance module selects the monitoring points of the devices and subscribes to the TELEMETRY performance of the optical module monitoring points by issuing subscription parameters; a PROTO file is predefined, and the devices report the performance data in PROTO format of the subscribed monitoring points (equivalent to the performance data of the aforementioned monitoring points) via gRPC according to the parameters; the analysis module of the TELEMETRY collector parses the performance data pushed by gRPC and converts it layer by layer into the performance objects required by the master control (equivalent to the preliminary performance data of the aforementioned WDM devices); the parsed data is stored in Kafka to reduce peak traffic and fill trough traffic, making the system as smooth as possible.

[0045] In one embodiment of this disclosure, such as Figure 3 As shown, the wavelength division multiplexing (WDM) equipment performance degradation detection method provided in this embodiment can determine the real-time performance data of the WDM equipment through the following steps, which can effectively compress the preliminary performance data, reduce the space occupied by the data, and improve the efficiency of processing massive amounts of data:

[0046] S302 consumes the initial performance data to obtain consumption data;

[0047] S304 stores consumed data in the cache;

[0048] S306, when there is missing consumption data of different devices between different wavelength division multiplexing (WDM) devices in the same time period, the consumption data with adjacent time in the cache is used to fill in the missing data.

[0049] S308 merges the consumption data of different devices in different wavelength division multiplexing (WDM) devices into one data entry at the same time.

[0050] S310, determine whether the current consumption data is consistent with the previous merged consumption data;

[0051] S312, if the current consumption data is consistent with the previous merged consumption data, then update the consumption data timestamp to determine the real-time performance data.

[0052] In one embodiment of this disclosure, such as Figure 4 As shown, the wavelength division multiplexing (WDM) equipment performance degradation detection method provided in this embodiment can determine the real-time performance data of the WDM equipment through the following steps, which can avoid the overwriting of effective information:

[0053] S402, if the current consumption data is inconsistent with the previous merged consumption data, then the different consumption data will be recorded separately to determine the real-time performance data.

[0054] For example, in one instance, during data compression, the data is collected from multiple devices and multiple performance metrics. Telemultry's data collection period can be accurate to the second. Before the data is stored in the Elasticsearch database, it is first compressed through the following steps:

[0055] First, read data from different Kafka topics (topic1, ..., topicn) and consume the data from topics on different devices.

[0056] Then, the performance data of multiple optical devices from different devices after consumption is stored in the cache, which stores the 20 most recent performance data entries.

[0057] Next, it checks whether there are any missing performance data for different components across different devices at the same time. If missing data is found, it is filled in using the nearest data from the cache.

[0058] Finally, the performance data of different devices within the same time period are merged into a single record. The system then checks if the current data matches the previously merged data. If they match, the timestamp is updated; otherwise, the different data are recorded separately and stored in the Elasticsearch database.

[0059] This disclosure can be introduced into a box-type WDM management system, providing it with methods for cross-vendor and cross-network element performance degradation analysis, eliminating the need to rely on traditional network management or vendor-specific network management to obtain device information and then manually determine device performance degradation. Its flexibility allows it to adapt to box-type WDM interconnection scenarios with multiple vendors.

[0060] The practicality of this disclosure can be reflected in the following aspects: enabling performance degradation analysis and prediction of box-type wavelength division multiplexing (WDM) control equipment; laying a solid foundation for performance degradation prediction when the control system is connected to equipment from multiple manufacturers; and being compatible with optoelectronic equipment from the same manufacturer and optical equipment from the same manufacturer with electrical equipment from other manufacturers.

[0061] In one embodiment of this disclosure, such as Figure 5 As shown, the wavelength division multiplexing (WDM) equipment performance degradation detection method provided in this embodiment can construct an evaluation model through the following steps to obtain the current degree of degradation of the WDM equipment:

[0062] S502, acquire historical status monitoring data of the wavelength division multiplexing (WDM) equipment;

[0063] S504, based on historical status monitoring data of the wavelength division multiplexing (WDM) equipment, recommended values ​​from the WDM equipment manufacturer, industry standard values, and experience values ​​from maintenance personnel, determines the standard for the normal operating status of the WDM equipment;

[0064] S506, based on the standard of normal operation of the wavelength division multiplexing (WDM) equipment, selects performance characteristic parameters that reflect the operating status of the WDM equipment, and determines the pre-built evaluation model based on machine learning.

[0065] In one example of this disclosure, acquiring historical status monitoring data of a wavelength division multiplexing (WDM) device includes: acquiring historical status monitoring data of the WDM device through telemetry.

[0066] In one example of this disclosure, preliminary performance data includes: input power information and output power information.

[0067] For example, in one instance, when constructing a degradation assessment model (equivalent to the assessment model mentioned above), the input power and output power of different devices and components affect the performance of the box-type wavelength division multiplexing (WDM) equipment (equivalent to the WDM equipment mentioned above), and can also truly reflect the performance degradation of the hardware. The steps to construct a performance degradation assessment model based on support vector machines are as follows:

[0068] First, TELEMTRY collects massive amounts of status monitoring data, and combines the recommended values ​​from equipment manufacturers, industry standard values, and the experience values ​​of front-line operation and maintenance personnel to determine the standard for the operational health status of the box-type wavelength division multiplexing (WDM) equipment.

[0069] Then, performance characteristic parameters that reflect the operating status of the box-type wavelength division multiplexing (WDM) equipment are selected to establish and verify a health model based on support vector machines. The mean absolute error (MAE) (Formula 1 below), mean square error (MSE) (Formula 2 below), and root mean square error (RMSE) (Formula 3 below) are compared between the acquired real-time values ​​and the model calculated values. The formulas are as follows:

[0070]

[0071]

[0072]

[0073] Where, y i Indicates the real-time value at the current moment, x i This represents the standard value calculated by the abnormal state detection model, and n represents the number of equipment performance sampling points.

[0074] Finally, performance data for a certain period of time is collected and input into the health model (equivalent to the evaluation model mentioned above) to calculate the standard health value and measured value of the parameters of the box-type wavelength division multiplexing (WDM) equipment under the current state, and to obtain the current degree of degradation of the box-type WDM equipment.

[0075] This disclosure considers the impact of different topologies on model training, and introduces topology structures to introduce different training models for different topology networks.

[0076] This disclosure takes into account the impact of real-time data on performance degradation and adopts Telemetry technology to monitor device performance in real time, thereby solving the problem of untimely performance analysis caused by untimely data acquisition.

[0077] This disclosure reports the input and output power information of key components as performance data to the main controller. This data is pre-subscribed to the box-type WDM equipment via the main controller's Telemetry performance module according to the standard NETCONF protocol. The equipment then pushes messages to the Telemetry acquisition unit based on the subscription information. By implementing TELEMETRY technology for second-level acquisition performance and using real-time compression technology to process massive amounts of data, space costs are saved. Based on this data acquisition, a performance degradation evaluation model based on support vector machines is constructed. This model can effectively evaluate and predict the performance degradation of the box-type WDM equipment.

[0078] This method can perform performance degradation analysis across vendors and network elements, improving the efficiency of network element anomaly maintenance while significantly reducing maintenance labor costs and the risk of misoperation.

[0079] This disclosure utilizes TELEMETRY technology to push status data, achieving second-level status monitoring. TELEMETRY technology allows devices to proactively push data at high speed in push mode, avoiding the inefficiency of traditional pull methods. Without requiring manual fault location, performance degradation can be analyzed in real time and reports provided by the second-level reporting of performance data, offering a convenient tool for operations and maintenance personnel.

[0080] Unlike traditional WDM equipment, the unique optical-to-electrical separation of box-type WDM equipment makes performance degradation localization more difficult. This disclosure enables unified processing and performance degradation analysis of performance information across vendors and network elements, solving problems such as long manual fault location time and low efficiency in handling massive amounts of data.

[0081] This disclosure reduces operation and maintenance costs, enables rapid location and repair of anomalies in the existing network, reduces the workload of manual intervention, and improves the efficiency of operation and maintenance of box-type wavelength division multiplexing (WDM) equipment.

[0082] This disclosure provides a strong guarantee for the rapid commissioning and anomaly handling of China Telecom's wavelength division multiplexing (WDM) services, based on performance degradation analysis using time-series information, real-time performance data acquisition, and the ability to perform degradation analysis on this data.

[0083] Based on the same inventive concept, this disclosure also provides a wavelength division multiplexing (WDM) equipment performance degradation detection device, as described in the following embodiments. Since the principle by which this device solves the problem is similar to that of the method embodiments described above, the implementation of this device embodiment can refer to the implementation of the method embodiments described above, and repeated details will not be elaborated further.

[0084] Figure 6This diagram illustrates a performance degradation detection device for wavelength division multiplexing (WDM) equipment according to an embodiment of the present disclosure. Figure 6 As shown, the device includes: a data subscription module 61, a data compression module 62, a performance degradation assessment module 63, and an assessment model module 64.

[0085] The data subscription module is used to obtain preliminary performance data of the wavelength division multiplexing (WDM) equipment through data subscription.

[0086] The data compression module is used to consume preliminary performance data and perform real-time compression processing to determine real-time performance data;

[0087] The performance degradation assessment module is used to input real-time performance data into a pre-built assessment model and output performance degradation information of the wavelength division multiplexing (WDM) equipment.

[0088] In one embodiment of this disclosure, the data subscription module is further configured to: determine the monitoring points of the wavelength division multiplexing (WDM) device, and send subscription parameters to subscribe to the performance data of the monitoring points; and obtain the performance data of the reported monitoring points as preliminary performance data of the WDM device.

[0089] In one embodiment of this disclosure, the data compression module is further configured to: consume preliminary performance data to obtain consumed data; store the consumed data in a cache; when there are missing consumed data from different devices of different wavelength division multiplexing (WDM) devices within the same time period, use consumed data with adjacent times in the cache to complete the data; merge the consumed data from different devices of different WDM devices within the same time period into one data entry; determine whether the current consumed data is consistent with the previous merged consumed data entry; if the current consumed data is consistent with the previous merged consumed data entry, update the timestamp of the consumed data to determine the real-time performance data.

[0090] In one embodiment of this disclosure, the data compression module is further configured to: if the current consumption data and the previous merged consumption data are inconsistent, record the different consumption data separately to determine the real-time performance data.

[0091] In one embodiment of this disclosure, the aforementioned wavelength division multiplexing (WDM) equipment performance degradation detection device further includes an evaluation model module 64, used for: acquiring historical status monitoring data of the WDM equipment; determining the standard for the normal operating status of the WDM equipment based on the historical status monitoring data, recommended values ​​from the WDM equipment manufacturer, industry standard values, and experience values ​​from maintenance personnel; selecting performance characteristic parameters reflecting the operating status of the WDM equipment based on the standard for the normal operating status of the WDM equipment, and determining a pre-built evaluation model based on machine learning.

[0092] In one embodiment of this disclosure, the evaluation model module 64 is further configured to: acquire historical status monitoring data of the wavelength division multiplexing (WDM) equipment through telemetry acquisition.

[0093] In one embodiment of this disclosure, the preliminary performance data in the data subscription module includes: input power information and output power information.

[0094] In a specific example, when the wavelength division multiplexing (WDM) equipment performance degradation detection device is running, the network management of the data subscription module sends subscription information to the device through the northbound interface. The TELEMETRY collector receives the Proto format data pushed by the device via the gRPC protocol and pushes it to Kafka. The data compression module consumes the performance data in Kafka and compresses the data in real time, greatly reducing the space occupied by the data. The performance degradation assessment module establishes a playback health standard that comprehensively considers multi-source information such as the input power and output power of optical devices, and constructs a support vector machine-based performance degradation assessment model for box-type WDM equipment.

[0095] It should be noted that the data subscription module 61, data compression module 62, and performance degradation assessment module 63 mentioned above correspond to S102 to S106 in the method embodiments. The examples and application scenarios implemented by these modules and their corresponding steps are the same, but they are not limited to the content disclosed in the above method embodiments. It should be noted that the above modules, as part of the apparatus, can be executed in a computer system such as a set of computer-executable instructions.

[0096] Those skilled in the art will understand that various aspects of this disclosure can be implemented as systems, methods, or program products. Therefore, various aspects of this disclosure can be specifically implemented in the following forms: entirely in hardware, entirely in software (including firmware, microcode, etc.), or in a combination of hardware and software, collectively referred to herein as “circuit,” “module,” or “system.”

[0097] The following reference Figure 7 To describe an electronic device 700 according to such an embodiment of the present disclosure. Figure 7 The electronic device 700 shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments disclosed herein.

[0098] like Figure 7 As shown, the electronic device 700 is manifested in the form of a general-purpose computing device. The components of the electronic device 700 may include, but are not limited to: at least one processing unit 710, at least one storage unit 720, and a bus 730 connecting different system components (including storage unit 720 and processing unit 710).

[0099] The storage unit stores program code that can be executed by the processing unit 710, causing the processing unit 710 to perform the steps described in the "Exemplary Methods" section above according to various exemplary embodiments of this disclosure.

[0100] For example, the processing unit 710 can perform the following steps of the above method embodiment:

[0101] Preliminary performance data of the wavelength division multiplexing (WDM) equipment can be obtained through data subscription.

[0102] The initial performance data is consumed and compressed in real time to determine the real-time performance data.

[0103] Real-time performance data is input into a pre-built evaluation model, which outputs performance degradation information of the wavelength division multiplexing (WDM) equipment.

[0104] For example, the processing unit 710 can perform the following steps of the above method embodiment:

[0105] Determine the monitoring points of the wavelength division multiplexing (WDM) equipment and send subscription parameters to subscribe to the performance data of the monitoring points.

[0106] The performance data obtained from the reported monitoring points is the preliminary performance data of the wavelength division multiplexing (WDM) equipment.

[0107] For example, the processing unit 710 can perform the following steps of the above method embodiment:

[0108] Consume the initial performance data to obtain consumption data;

[0109] Store consumed data in a cache;

[0110] If there is missing consumption data for different devices in different wavelength division multiplexing (WDM) devices within the same time period, then the consumption data with adjacent times in the cache will be used to fill in the missing data.

[0111] Consumption data from different devices in different wavelength division multiplexing (WDM) equipment are merged into one data entry at the same time.

[0112] Determine if the current consumption data is consistent with the previous merged consumption data;

[0113] If the current consumption data is consistent with the previous merged consumption data, then update the consumption data timestamp to determine the real-time performance data.

[0114] For example, the processing unit 710 can perform the following steps of the above method embodiment:

[0115] If the current consumption data is inconsistent with the previous merged consumption data, the different consumption data will be recorded separately to determine the real-time performance data.

[0116] For example, the processing unit 710 can perform the following steps of the above method embodiment:

[0117] Acquire historical status monitoring data of the wavelength division multiplexing (WDM) equipment;

[0118] Based on historical status monitoring data of the wavelength division multiplexing (WDM) equipment, recommended values ​​from the WDM equipment manufacturer, industry standard values, and experience values ​​from maintenance personnel, the standard for the normal operating status of the WDM equipment is determined.

[0119] Based on the standard of normal operation of the wavelength division multiplexing (WDM) equipment, performance characteristic parameters reflecting the operating status of the WDM equipment are selected, and a pre-built evaluation model is determined based on machine learning.

[0120] For example, the processing unit 710 can perform the following steps of the above method embodiment:

[0121] Historical status monitoring data of wavelength division multiplexing (WDM) equipment is acquired through telemetry.

[0122] For example, the preliminary performance data in the steps of the above method embodiment executed by the processing unit 710 includes: input power information and output power information.

[0123] Storage unit 720 may include a readable medium in the form of a volatile storage unit, such as random access memory (RAM) 7201 and / or cache memory 7202, and may further include a read-only memory (ROM) 7203.

[0124] The storage unit 720 may also include a program / utility 7204 having a set (at least one) program module 7205, such program module 7205 including but not limited to: an operating system, one or more application programs, other program modules and program data, each or some combination of these examples may include an implementation of a network environment.

[0125] Bus 730 can represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of the various bus structures.

[0126] Electronic device 700 can also communicate with one or more external devices 740 (e.g., keyboard, pointing device, Bluetooth device, etc.), and with one or more devices that enable a user to interact with electronic device 700, and / or with any device that enables electronic device 700 to communicate with one or more other computing devices (e.g., router, modem, etc.). This communication can be performed via input / output (I / O) interface 750. Furthermore, electronic device 700 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 760. As shown, network adapter 760 communicates with other modules of electronic device 700 via bus 730. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with electronic device 700, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0127] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, terminal device, or network device, etc.) to execute the methods according to the embodiments of this disclosure.

[0128] In particular, according to embodiments of this disclosure, the process described above with reference to the flowchart can be implemented as a computer program product, which includes a computer program that, when executed by a processor, implements the above-described wavelength division multiplexing (WDM) device performance degradation detection method.

[0129] In exemplary embodiments of this disclosure, a computer-readable storage medium is also provided, which may be a readable signal medium or a readable storage medium. Figure 8 This diagram illustrates a computer-readable storage medium according to an embodiment of the present disclosure, such as... Figure 8 As shown, the computer-readable storage medium 800 stores a program product capable of implementing the methods described above in this disclosure. In some possible embodiments, various aspects of this disclosure may also be implemented as a program product comprising program code that, when run on a terminal device, causes the terminal device to perform the steps described in the "Exemplary Methods" section of this specification according to various exemplary embodiments of this disclosure.

[0130] For example, when the program product in this embodiment is executed by a processor, it implements the following steps:

[0131] Preliminary performance data of the wavelength division multiplexing (WDM) equipment can be obtained through data subscription.

[0132] The initial performance data is consumed and compressed in real time to determine the real-time performance data.

[0133] Real-time performance data is input into a pre-built evaluation model, which outputs performance degradation information of the wavelength division multiplexing (WDM) equipment.

[0134] For example, when the program product in this embodiment is executed by a processor, it implements the following steps:

[0135] Determine the monitoring points of the wavelength division multiplexing (WDM) equipment and send subscription parameters to subscribe to the performance data of the monitoring points.

[0136] The performance data obtained from the reported monitoring points is the preliminary performance data of the wavelength division multiplexing (WDM) equipment.

[0137] For example, when the program product in this embodiment is executed by a processor, it implements the following steps:

[0138] Consume the initial performance data to obtain consumption data;

[0139] Store consumed data in a cache;

[0140] If there is missing consumption data for different devices in different wavelength division multiplexing (WDM) devices within the same time period, then the consumption data with adjacent times in the cache will be used to fill in the missing data.

[0141] Consumption data from different devices in different wavelength division multiplexing (WDM) equipment are merged into one data entry at the same time.

[0142] Determine if the current consumption data is consistent with the previous merged consumption data;

[0143] If the current consumption data is consistent with the previous merged consumption data, then update the consumption data timestamp to determine the real-time performance data.

[0144] For example, when the program product in this embodiment is executed by a processor, it implements the following steps:

[0145] If the current consumption data is inconsistent with the previous merged consumption data, the different consumption data will be recorded separately to determine the real-time performance data.

[0146] For example, when the program product in this embodiment is executed by a processor, it implements the following steps:

[0147] Acquire historical status monitoring data of the wavelength division multiplexing (WDM) equipment;

[0148] Based on historical status monitoring data of the wavelength division multiplexing (WDM) equipment, recommended values ​​from the WDM equipment manufacturer, industry standard values, and experience values ​​from maintenance personnel, the standard for the normal operating status of the WDM equipment is determined.

[0149] Based on the standard of normal operation of the wavelength division multiplexing (WDM) equipment, performance characteristic parameters reflecting the operating status of the WDM equipment are selected, and a pre-built evaluation model is determined based on machine learning.

[0150] For example, when the program product in this embodiment is executed by a processor, it implements the following steps:

[0151] Historical status monitoring data of wavelength division multiplexing (WDM) equipment is acquired through telemetry.

[0152] For example, preliminary performance data of the program product when executed by the processor in this embodiment of the disclosure includes: input power information and output power information.

[0153] More specific examples of computer-readable storage media in this disclosure may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0154] In this disclosure, a computer-readable storage medium may include a data signal propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium, capable of transmitting, propagating, or transmitting a program for use by or in connection with an instruction execution system, apparatus, or device.

[0155] Optionally, the program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof.

[0156] In practical implementation, program code for performing the operations of this disclosure can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0157] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to embodiments of this disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0158] Furthermore, although the steps of the method in this disclosure are described in a specific order in the accompanying drawings, this does not require or imply that the steps must be performed in that specific order, or that all the steps shown must be performed to achieve the desired result. Additional or alternative steps may be omitted, multiple steps may be combined into one step, and / or a step may be broken down into multiple steps.

[0159] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, mobile terminal, or network device, etc.) to execute the methods according to the embodiments of this disclosure.

[0160] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the appended claims.

Claims

1. A method for detecting performance degradation of wavelength division multiplexing (WDM) equipment, characterized in that, include: Preliminary performance data of the wavelength division multiplexing (WDM) equipment can be obtained through data subscription. The preliminary performance data is consumed and compressed in real time to determine the real-time performance data. The real-time performance data is input into a pre-built evaluation model, which outputs the performance degradation information of the wavelength division multiplexing (WDM) device. The step of consuming the preliminary performance data and performing real-time compression processing to determine the real-time performance data includes: consuming the preliminary performance data to obtain consumed data; storing the consumed data in a cache; when there are missing consumed data from different devices in different wavelength division multiplexing (WDM) devices within the same time period, using consumed data with adjacent times in the cache to fill in the gaps; merging the consumed data from different devices in different WDM devices within the same time period into one entry; determining whether the current consumed data is consistent with the previous merged consumed data; if the current consumed data is consistent with the previous merged consumed data, updating the timestamp of the consumed data to determine the real-time performance data. The step of storing the consumed data in a cache includes: storing the consumed performance data of multiple optical devices from different devices in a cache.

2. The method for detecting performance degradation of wavelength division multiplexing (WDM) equipment according to claim 1, characterized in that, The preliminary performance data of the wavelength division multiplexing (WDM) equipment determined through data subscription includes: Determine the monitoring points of the wavelength division multiplexing (WDM) equipment, and send subscription parameters to subscribe to the performance data of the monitoring points; The performance data of the monitoring points that are reported and subscribed to are obtained as the preliminary performance data of the wavelength division multiplexing (WDM) device.

3. The method for detecting performance degradation of wavelength division multiplexing (WDM) equipment according to claim 1, characterized in that, The method further includes: If the current consumption data is inconsistent with the previous merged consumption data, the different consumption data will be recorded separately to determine the real-time performance data.

4. The method for detecting performance degradation of wavelength division multiplexing (WDM) equipment according to claim 1, characterized in that, The pre-built evaluation model includes: Acquire historical status monitoring data of the wavelength division multiplexing (WDM) equipment; Based on the historical status monitoring data of the wavelength division multiplexing (WDM) equipment, the recommended values ​​of the WDM equipment manufacturer, the industry standard values, and the experience values ​​of the operation and maintenance personnel, the standard for the normal operating status of the WDM equipment is determined. Based on the standard of normal operation of the wavelength division multiplexing (WDM) equipment, performance characteristic parameters reflecting the operating status of the WDM equipment are selected, and a pre-built evaluation model is determined based on machine learning.

5. The method for detecting performance degradation of wavelength division multiplexing (WDM) equipment according to claim 4, characterized in that, The historical status monitoring data of the wavelength division multiplexing (WDM) equipment includes: Historical status monitoring data of wavelength division multiplexing (WDM) equipment is acquired through telemetry.

6. The method for detecting performance degradation of wavelength division multiplexing (WDM) equipment according to claim 1, characterized in that, The preliminary performance data includes: Input power information and output power information.

7. A device for detecting performance degradation of wavelength division multiplexing (WDM) equipment, characterized in that, include: The data subscription module is used to obtain preliminary performance data of the wavelength division multiplexing (WDM) equipment through data subscription. The data compression module is used to consume the preliminary performance data and perform real-time compression processing to determine the real-time performance data; The performance degradation assessment module is used to input the real-time performance data into a pre-built assessment model and output the performance degradation information of the wavelength division multiplexing (WDM) device. The data compression module is further configured to: consume the preliminary performance data to obtain consumed data; store the consumed data in a cache; when there are missing consumed data from different devices in different wavelength division multiplexing (WDM) devices within the same time period, use adjacent consumed data from the cache to complete the data; merge the consumed data from different devices in different WDM devices within the same time period into one data entry; determine whether the current consumed data and the previous merged consumed data are consistent; if the current consumed data and the previous merged consumed data are consistent, update the timestamp of the consumed data to determine the real-time performance data. The step of storing the consumed data in a cache includes: storing the consumed performance data of multiple optical devices from different devices in a cache.

8. An electronic device, characterized in that, include: processor; as well as Memory for storing the executable instructions of the processor; The processor is configured to execute the wavelength division multiplexing (WDM) device performance degradation detection method according to any one of claims 1 to 6 by executing the executable instructions.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the wavelength division multiplexing (WDM) equipment performance degradation detection method according to any one of claims 1 to 6.

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