Data acquisition method, electronic device, and storage medium

Abstract

The present application discloses a data acquisition method, an electronic device, and a storage medium. The data acquisition method comprises: using an acquisition value of an acquirable twin attribute in a twin as a twin value when the acquirable twin attribute is constructed; simulating the twin value on the basis of a twin simulation algorithm to obtain a simulation value of a simulatable twin attribute; when the simulation value satisfies a preset condition, using the simulation value as a twin value when the simulatable twin attribute is constructed; and modifying an acquisition configuration so as to reduce or cancel acquisition of the acquisition value of the simulatable twin attribute that is performed by an optical network device.

Description

Data collection method, electronic device and storage medium

[0001] Cross-reference to related applications

[0002] The present application claims priority to the Chinese patent application No. 202410864114.4, filed on June 30, 2024, and entitled "Data collection method, electronic device and storage medium", the content of which is incorporated herein by reference in its entirety. TECHNICAL FIELD

[0003] The present application belongs to the technical field of data collection, and specifically relates to a data collection method, an electronic device and a storage medium. BACKGROUND

[0004] A twin has attributes and behaviors corresponding to a physical entity one by one to realize a twin effect, and the construction of the twin needs data collection and simulation algorithms to realize. The twin attributes have data collection of the corresponding physical attributes, and the collected collection values are taken as twin values of the twin attributes. In related technologies, data collection is performed by a device for supported performance items at regular intervals, and the device can also actively push collected data according to task requirements through a data subscription method.

[0005] No matter which of the above data collection methods, a large amount of data needs to be collected, and the reported data may be repeated, resulting in low efficiency of device collection and reporting. SUMMARY

[0006] The present application aims to provide a data collection method, an electronic device and a storage medium, and at least solve the problem of low efficiency of device collection and reporting caused by large amount of data collection and data repetition in related technologies.

[0007] In a first aspect, an embodiment of the present application provides a data collection method, comprising: taking a collection value of a collectable twin attribute in a twin as a twin value for constructing the collectable twin attribute; simulating the twin value based on a twin simulation algorithm to obtain a simulation value of a simulatable twin attribute; in a case where the simulation value meets a preset condition, taking the simulation value as a twin value for constructing the simulatable twin attribute; and modifying a collection configuration to reduce or cancel collection of the collection value of the simulatable twin attribute by an optical network device.

[0008] In a second aspect, an embodiment of the present application provides an electronic device, comprising a processor, a memory and a program or instructions stored in the memory and executable on the processor, and the program or instructions are executed by the processor to implement the steps of the method according to the first aspect.

[0009] In a third aspect, an embodiment of the present application provides a storage medium, wherein the storage medium stores a program or instructions, and the program or instructions, when executed by a processor, implement the steps of the method according to the first aspect.

[0010] In a fourth aspect, an embodiment of the present application provides a program product, wherein the program product is stored in a storage medium, and the program product, when executed by at least one processor, implements the steps of the method according to the first aspect. BRIEF DESCRIPTION OF DRAWINGS

[0011] The above and / or additional aspects and advantages of the present application will become apparent and be readily appreciated from the description of the embodiments, given with reference to the following drawings, wherein:

[0012] FIG. 1 is a flowchart of a data collection method according to an embodiment of the present application;

[0013] FIG. 2 is a schematic diagram of twin attribute division according to an embodiment of the present application;

[0014] FIG. 3 is a schematic diagram of the same imitable twin attribute existing between multiple sets of twin attribute sets according to an embodiment of the present application;

[0015] FIG. 4 is a schematic diagram of step-by-step simulation of multiple levels of twin attributes according to an embodiment of the present application;

[0016] FIG. 5 is a schematic diagram of a data collection device according to an embodiment of the present application;

[0017] FIG. 6 is a schematic diagram of a terminal device according to an embodiment of the present application. DETAILED DESCRIPTION

[0018] Embodiments of the present application will be described in detail below with reference to the drawings, wherein the same or similar components are denoted by the same or similar reference numerals throughout the drawings, and the embodiments described below are exemplary and are only used to explain the present application, and cannot be understood as limiting the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application.

[0019] The terms "first", "second" in the description and claims of the present application can explicitly or implicitly include one or more of the features. In the description of the present application, unless otherwise specified, the meaning of "a plurality of" is two or more. In addition, "and / or" in the specification and claims means at least one of the connected objects, and the character " / ", generally means that the front and rear associated objects are in an "or" relationship.

[0020] In the description of the present application, it should be understood that the orientation or positional relationship indicated by the terms "center", "longitudinal", "transverse", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", "axial", "radial", "circumferential" and the like are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, and therefore cannot be understood as indicating or implying that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the present application.

[0021] In the description of the present application, it should be noted that unless otherwise explicitly specified and limited, the terms "mounting", "connection", "connection" should be understood in a broad sense, for example, it can be fixed connection, or detachable connection, or integrally connected; it can be mechanical connection, or electrical connection; it can be directly connected, or indirectly connected through intermediate medium, or it can be the communication inside two elements. For those skilled in the art, the meaning of the above terms in the present application can be understood according to the situation.

[0022] In the following, combined with FIG. 1 to FIG. 6, the data acquisition method, electronic device and storage medium provided by the embodiments of the present application are described in detail through embodiments and application scenarios.

[0023] FIG. 1 is a flowchart of a data acquisition method provided by an embodiment of the present application. As shown in FIG. 1, the data acquisition method can include the contents shown in steps 101 to 104.

[0024] In S101, the acquisition value of the adoptable twin attribute in the twin is taken as the twin value when the adoptable twin attribute is constructed.

[0025] Among them, the adoptable twin attribute refers to the twin attribute in the twin whose data source is acquisition data, and its acquisition value is its twin value.

[0026] In S102, the twin value is simulated based on a twin simulation algorithm to obtain a simulation value of the simulative twin attribute.

[0027] Among them, the simulative twin attribute refers to the twin attribute in the twin whose data source is simulation acquisition, and in the case that the simulation value meets the preset condition, its simulation value is its twin value, and if the simulation value cannot meet the preset condition, its twin value is its acquisition value.

[0028] In S103, in the case that the simulation value meets the preset condition, the simulation value is taken as the twin value when the simulative twin attribute is constructed.

[0029] In S104, the collection configuration is modified to reduce or cancel the collection of the collection value of the emulatable twin attribute by the optical network device.

[0030] That is, in the case that the simulation value can be used as the twin value when the emulatable twin attribute is constructed, the collection configuration can be modified to reduce or cancel the collection of the collection value of the emulatable twin attribute by the physical device, such as the optical network device.

[0031] In an embodiment of the present application, first, the collection value of the collectable twin attribute in the twin is used as the twin value when the emulatable twin attribute is constructed, then the simulation value of the emulatable twin attribute is obtained by simulating the twin value based on a twin simulation algorithm, in the case that the simulation value meets a preset condition, the simulation value is used as the twin value when the emulatable twin attribute is constructed, and finally the collection configuration is modified to reduce or cancel the collection of the collection value of the emulatable twin attribute by the optical network device. The simulation value of the emulatable twin attribute is replaced by the original collection value as the source of the twin value in the embodiment of the present application, which can reduce the collection data of the physical device, alleviate the collection pressure, and improve the data collection efficiency. In the case that the simulation value does not meet the requirement, the collection value is used to ensure that the requirement of the twin construction is met.

[0032] In a possible implementation of the present application, in the case that the simulation value meets the preset condition, the simulation value is used as the twin value when the emulatable twin attribute is constructed, which can include: calculating a first error between the simulation value and an actual value of the emulatable twin attribute, and a second error between the collection value and the actual value of the emulatable twin attribute; in the case that the first error is less than or equal to the second error, the simulation value is used as the twin value when the emulatable twin attribute is constructed.

[0033] The actual value refers to the real data value corresponding to the emulatable twin attribute, which can be determined by averaging the collection values obtained by multiple collections, or by other methods, which are not limited in the present embodiment, and are subject to actual application.

[0034] In the present embodiment, by calculating the first error between the simulation value and the actual value of the emulatable twin attribute, and the second error between the collection value and the actual value, it can be determined whether the simulation value is closer to the actual value or the collection value is closer to the actual value. In the case that the first error is less than or equal to the second error, that is, the simulation value is closer to the actual value, the simulation value is used as the twin value when the emulatable twin attribute is constructed, which can further reduce the collection data of the physical device, and alleviate the pressure of data collection and processing.

[0035] In another embodiment of the present application, in the case that the simulation value meets the preset condition, the simulation value is used as the twin value when the emulatable twin attribute is constructed, which can include: in the case that the error between the simulation value and the collection value of the emulatable twin attribute is less than a first threshold, the simulation value is used as the twin value when the emulatable twin attribute is constructed.

[0036] The first threshold can be 0.1, the first threshold can also be 0.01, the first threshold can also be another smaller value, which can be determined according to historical data or the experience of a technician, and the actual application is used as the criterion, and the embodiment is not limited.

[0037] That is, the simulation value and the collected value can be directly compared, and in the case that the error between the simulation value and the collected value is small enough, that is, the simulation value is close to the collected value, the simulation value can be used as the twin value for constructing the imitable twin attribute. The collection of the collected data of the imitable twin attribute by the device is reduced.

[0038] In one possible implementation of the present application, modifying the collection configuration includes at least one of the following: shielding performance alarms; canceling subscription operations for telemetry collection reporting; prolonging the period of data collection reporting; and changing the reporting form of the collection items.

[0039] That is, in the case that the simulation value can replace the collected value, the collection of the collected value of the imitable twin attribute by the optical network device can be reduced or canceled by modifying the collection configuration, thereby reducing the data collection pressure of the optical network device and saving the reporting bandwidth.

[0040] It is worth noting that telemetry is a new type of collection technology, which sets a collection task through a data subscription method, and the device actively pushes the collected data according to the task requirements.

[0041] Reducing or canceling the data collection of the optical network device can include shielding operations for traditional performance alarms to reduce performance alarms; for telemetry collection, the data collection of the optical network device can be canceled by canceling the subscription operation; the data collection of the optical network device can also be reduced by prolonging the period of data collection reporting or changing the reporting form of the collection items, such as lengthening the time interval of data reporting, or delaying the off-peak reporting to reduce the communication pressure, or the collection items no longer actively report, waiting for query to synchronize data, or actively reporting in the case of large changes in data, and the like. The actual application is used as the criterion, and the embodiment is not limited.

[0042] In one possible implementation of the present application, after the simulation value is used as the twin value for constructing the imitable twin attribute, the data collection method can further include: in the case that an abnormal event is detected, using the collected value as the twin value for constructing the imitable twin attribute; and modifying the collection configuration again to restore the collection of the collected value of the imitable twin attribute by the optical network device.

[0043] That is, in the case of detecting an abnormal event, the simulation value cannot meet the requirement, that is, the simulation value cannot replace the collected data of the optical network device, at this time, the collected value of the imitable twin attribute is used as the twin value when the imitable twin attribute is constructed, so as to ensure that the collected data meets the requirement. In the case of needing to use the collected value as the twin value when the imitable twin attribute is constructed, the collection configuration needs to be modified again to restore the collection of the collected value of the imitable twin attribute by the optical network device.

[0044] The abnormal event at least includes one of the following: an exception occurs in the process of simulating based on the twin simulation algorithm; an alarm report affecting data collection is received; the performance of the twin value used for simulation abnormally jumps.

[0045] The abnormal event can be that the error between the simulation value obtained by simulation and the actual value is greater than the error between the collected value and the actual value, that is, the simulation result does not meet the requirement, and the abnormal event can also be that other abnormalities occur in the simulation process; the abnormal event can also be that an alarm report that can affect data collection is found; the abnormal event can also be that the twin value used for simulation is abnormal, so that the simulation result is not credible, and the like. Actual application is for reference, and the embodiment is not limited. It is worth noting that the alarm report that can affect data collection can be that a large change occurs in the hardware level of the device, or an alarm report can be reported due to the discovery of other factors that can affect data collection; the reason why the twin value is abnormal can be that the collected value corresponding to the twin value is abnormal, for example, the collected data is abnormal due to device change, or the upstream simulation value is abnormal, and the like. Actual application is for reference, and the embodiment is not limited.

[0046] In the embodiment, in the case that the simulation value cannot meet the requirement of twin construction, physical collection can be restored, that is, the collection of the collected value of the imitable twin attribute by the optical network device is restored, so as to ensure that the data used for constructing the twin meets the requirement. That is, in the case that the simulation value cannot meet the requirement and physical collection is needed, the collection of the collected value of the imitable twin attribute by the optical network device can be restored by modifying the collection configuration again, so as to ensure the reliability of the data.

[0047] In a possible implementation of the present application, modifying the collection configuration again includes at least one of the following: issuing a query command to update the current state; canceling the shielding of the performance alarm; and shortening the period of data collection report.

[0048] Restoring the collection of the optical network device can be issuing a query command to update the current state in real time, or can be canceling the shielding of the performance alarm in the above embodiment, so that the performance alarm can be received, or can be shortening the period of data collection report, so that the collected data is reported faster to achieve the purpose of updating the data in time. There are various ways to restore the collection of the optical network device, and the embodiment will not be described one by one, and actual application is for reference.

[0049] In a possible implementation of the present application, a plurality of twin attributes are included in a twin, forming a twin attribute set, a part of the twin attribute set is a collectable twin attribute, and the remaining twin attributes are imitable twin attributes, forming a construction scheme of the twin attribute set.

[0050] That is, a twin attribute set including collectable twin attributes can be selected from a twin, and the collected values are used as twin values and for simulation, and the remaining twin attributes are imitable twin attributes, and the simulation values are used as the source of twin values instead of collected values to reduce the data collected by the device and the pressure on the device.

[0051] In the case where the simulation value meets the preset condition, the simulation value is used as the twin value when constructing the imitable twin attribute, which can include: dividing different twin attributes into collectable twin attributes, and the remaining twin attributes are imitable twin attributes, to obtain different construction schemes of the twin attribute set; determining the simulation values of the imitable twin attributes corresponding to all construction schemes; evaluating the plurality of construction schemes to determine the optimal construction scheme; in the case where the simulation value of the optimal construction scheme meets the preset condition, applying the optimal construction scheme, and using the simulation values of all imitable twin attributes in the optimal construction scheme as the twin values when constructing the imitable twin attribute.

[0052] It is worth noting that different construction schemes can be realized by existing twin simulation algorithms in the system, and in an instance, different twin simulation algorithms correspond to different inputs and outputs, the input is a collectable twin attribute, and the output is an imitable twin attribute obtained by simulating the collectable twin attribute using the twin simulation algorithm. For a twin attribute set, as long as there are multiple twin simulation algorithms with different inputs and outputs, different construction schemes can be found by switching the twin simulation algorithm. Among them, the twin attributes that cannot be simulated by each twin simulation algorithm are used as collectable twin attributes. At the same time, multiple existing twin attribute algorithms can also be combined to form a new twin attribute algorithm.

[0053] In the embodiment, different construction schemes can be obtained by dividing different twin attributes, i.e., dividing different twin attributes into adoptable twin attributes, and the rest into imitable twin attributes. Simulation is performed for each construction scheme to determine the simulation values of all imitable twin attributes in each construction scheme. Different construction schemes are evaluated to determine the optimal construction scheme. In a case where the simulation values of the optimal construction scheme meet preset conditions, the optimal construction scheme is applied, and the simulation values of all imitable twin attributes in the optimal construction scheme are used as the twin values when the imitable twin attributes are constructed. That is, different construction schemes can be determined by division, and the optimal construction scheme can be determined. Simulation is performed by using the optimal construction scheme, i.e., using the simulation values of all imitable twin attributes in the optimal construction scheme as the twin values when the imitable twin attributes are constructed. The demand for twin body construction can be met under the premise of reducing the data collected by physical devices and reducing the device data pressure.

[0054] In a possible implementation of the present application, if the simulation values of the optimal construction scheme do not meet the preset conditions, all twin attributes in the twin attribute set are adoptable twin attributes.

[0055] In a possible implementation of the present application, evaluating the multiple construction schemes can include evaluating the multiple construction schemes according to one or more of the number of adoptable twin attributes, the collection value accuracy, the number of imitable twin attributes, the simulation value accuracy, and the simulation calculation resource.

[0056] That is, one or more of the collection number, the collection accuracy, the simulation calculation resource, the simulation result accuracy, and the simulation calculation resource can be used for unified evaluation to select a simulation algorithm to determine the optimal construction scheme. The twin body constructed by using the optimal construction scheme can make the data collection of the twin body relatively minimal, the simulation values obtained by simulation relatively most accurate, better meet the twin body construction demand, and reduce the device data collection pressure to a greater extent.

[0057] In a possible implementation of the present application, determining the optimal construction scheme can include: selecting one construction scheme as the optimal construction scheme from the multiple construction schemes according to the evaluation result; in a case where the optimal construction scheme is abnormal, reevaluating the multiple construction schemes to determine a new optimal construction scheme, and switching the optimal construction scheme to the new optimal construction scheme.

[0058] In this embodiment, one of the multiple construction schemes can be selected as the optimal construction scheme based on the evaluation requirements, and the digital twin is constructed based on the optimal construction scheme. If the optimal construction scheme is abnormal, for example, the data required for simulation is abnormal, which affects the simulation calculation, so that the optimal construction scheme is no longer optimal. At this time, the multiple construction schemes need to be re-evaluated to determine a new optimal construction scheme, and the new optimal construction scheme is used to replace the original optimal construction scheme, so that the construction scheme used is always optimal.

[0059] In one possible implementation of the present application, the twin attribute set includes a first twin attribute and a second twin attribute, and the construction scheme of the twin attribute set includes one of the following: the first twin attribute is a collectable twin attribute; and the second twin attribute is a collectable twin attribute.

[0060] In this embodiment, two twin attributes are taken as an example. The construction scheme of the twin attribute set can have two types, one of which is that the first twin attribute is a collectable twin attribute and the second twin attribute is a simulation twin attribute; and the other of which is that the first twin attribute is a simulation twin attribute and the second twin attribute is a collectable twin attribute.

[0061] FIG. 2 shows a case where the twin attribute set includes a first twin attribute and a second twin attribute. As shown in FIG. 2, the twin attribute A is the first twin attribute, and the twin attribute B is the second twin attribute.

[0062] When constructing the twin, the data A can be collected to simulate the twin attribute B, or the data B can be collected to simulate the twin attribute A. Therefore, two different twin simulation algorithms can be loaded respectively, and the simulation calculation results and the actual data are compared to select a more suitable construction scheme, for example, a construction scheme with higher simulation value accuracy. The simulation value of the collectable twin attribute is used as the twin value of the collectable twin attribute when the collectable twin attribute is constructed, and the simulation value of the simulation twin attribute is used as the twin value of the simulation twin attribute when the simulation twin attribute is constructed, so as to reduce the data collected by the device.

[0063] In this embodiment, two twin attributes are taken as an example. The construction scheme of the twin attribute set can have two types, one of which is that the first twin attribute is a collectable twin attribute and the second twin attribute is a simulation twin attribute; and the other of which is that the first twin attribute is a simulation twin attribute and the second twin attribute is a collectable twin attribute. In this embodiment, two twin attributes are taken as an example. The construction scheme of the twin attribute set can have two types, one of which is that the first twin attribute is a collectable twin attribute and the second twin attribute is a simulation twin attribute; and the other of which is that the first twin attribute is a simulation twin attribute and the second twin attribute is a collectable twin attribute. In this embodiment, two twin attributes are taken as an example. The construction scheme of the twin attribute set can have two types, one of which is that the first twin attribute is a collectable twin attribute and the second twin attribute is a simulation twin attribute; and the other of which is that the first twin attribute is a simulation twin attribute and the second twin attribute is a collectable twin attribute. In this embodiment, two twin attributes are taken as an example. The construction scheme of the twin attribute set can have two types, one of which is that the first twin attribute is a collectable twin attribute and the second twin attribute is a simulation twin attribute; and the other of which is that the first twin attribute is a simulation twin attribute and the second twin attribute is a collectable twin attribute. In this embodiment, two twin attributes are taken as an example. The construction scheme of the twin attribute set can have two types, one of which is that the first twin attribute is a collectable twin attribute and the second twin attribute is a simulation twin attribute; and the other of which is that the first twin attribute is a simulation twin attribute and the second twin attribute is a collectable twin attribute.

[0064] In an example, the twin attribute A can be taken as a collectable twin attribute, and the twin attribute B can be taken as a simulatable twin attribute. The collected value of the twin attribute A is obtained through data collection, and the collected value is taken as the twin value. The twin attribute A is simulated based on the twin simulation algorithm to obtain the simulation value of the twin attribute B. When the error between the simulation value and the actual value of the twin attribute B is less than or equal to the error between the collected value and the actual value of the twin attribute B, the simulation value of the twin attribute B can be taken as the twin value when the twin attribute B is constructed. Correspondingly, the twin attribute B can be taken as a collectable twin attribute, and the twin attribute A can be taken as a simulatable twin attribute. The collected value of the twin attribute B is obtained through data collection, and the collected value is taken as the twin value. The twin attribute B is simulated based on the twin simulation algorithm to obtain the simulation value of the twin attribute A. When the error between the simulation value and the actual value of the twin attribute A is less than or equal to the error between the collected value and the actual value of the twin attribute A, the simulation value of the twin attribute A can be taken as the twin value when the twin attribute A is constructed. Then, one or more of the accuracy of data collection A, the accuracy of data collection B, the accuracy of the simulation value of the twin attribute B, the accuracy of the simulation value of the twin attribute A, and the simulation calculation resource are used to evaluate the two construction schemes to determine the optimal construction scheme, and the construction scheme is applied to collect corresponding data. The simulation value of the simulatable twin attribute is taken as the twin value when the simulatable twin attribute is constructed, so that the twin body constructed according to the optimal construction scheme has higher data accuracy.

[0065] In a possible implementation of the present application, the twin body includes multiple sets of twin attribute sets, and taking the simulation value as the twin value when constructing the simulatable twin attribute can include: in the case that there is a same simulatable twin attribute between the multiple sets of twin attribute sets, determining an optimal twin attribute set based on the simulation value of the simulatable twin attribute in each set of twin attribute sets; and taking the simulation value of the simulatable twin attribute in the optimal twin attribute set as the twin value when constructing the simulatable twin attribute.

[0066] That is, the twin body can include multiple sets of twin attribute sets, each set of twin attribute sets can include multiple twin attributes, and the multiple twin attributes can include both collectable twin attributes for simulation and simulatable twin attributes, so that the simulation value of the simulatable twin attribute replaces the collected value to reduce the data collected by the device and reduce the pressure on the device.

[0067] In the case that there is a same imitable twin attribute between multiple sets of twin attribute sets, for example, in one set of twin attribute sets, twin attribute B can be imitated by data A, and in another set of twin attribute sets, twin attribute B can be imitated by data C, wherein the same imitable twin attribute between the two sets of twin attribute sets is twin attribute B. In this case, the simulation value of the imitable twin attribute in each set of twin attribute sets can be used to determine the optimal set of twin attribute sets, and then the simulation value of the imitable twin attribute in the optimal set of twin attribute sets can be used as the twin value when constructing the imitable twin attribute, that is, the simulation value of twin attribute B in the optimal set of twin attribute sets is used as the simulation value of all twin attribute B in the whole twin body.

[0068] FIG. 3 is a case where there is a same imitable twin attribute between multiple sets of twin attribute sets. As shown in FIG. 3, the two sets of twin attribute sets are a first set of twin attribute sets and a second set of twin attribute sets. The first set of twin attribute sets includes twin attribute A and twin attribute B, wherein twin attribute A is a collectable twin attribute and twin attribute B is an imitable twin attribute. The second set of twin attribute sets includes twin attribute B and twin attribute C, wherein twin attribute C is a collectable twin attribute and twin attribute B is an imitable twin attribute. The same imitable twin attribute between the two sets of twin attribute sets is twin attribute B.

[0069] In an example, in the first set of twin attribute sets, data collection A can be collected, data collection A has a corresponding twin attribute A in the twin body, the collection value of data collection A is used as the twin value of twin attribute A, and based on the twin simulation algorithm, twin attribute A is simulated to obtain the simulation value of twin attribute B. If the error between the simulation value of twin attribute B and the actual value is less than or equal to the error between the collection value of twin attribute B and the actual value, the simulation value of twin attribute B can be used as the twin value when constructing twin attribute B. Correspondingly, in another set of twin attribute sets, data collection C can be collected, data collection C has a corresponding twin attribute C in the twin body, the collection value of data collection C is used as the twin value of twin attribute C, and based on the twin simulation algorithm, twin attribute C is simulated to obtain the simulation value of twin attribute B. If the error between the simulation value of twin attribute B and the actual value is less than or equal to the error between the collection value of twin attribute B and the actual value, the simulation value of twin attribute B can be used as the twin value when constructing twin attribute B. Therefore, the same imitable twin attribute between the two sets of twin attribute sets is twin attribute B.

[0070] In constructing the twin, two different twin simulation algorithms can be loaded respectively based on different twin attribute sets, and the simulation values of the imitable twin attributes B in each set of twin attributes are calculated respectively. Based on the simulation values of the imitable twin attributes B in each set, an optimal twin attribute set is selected, and the simulation values of the imitable twin attributes in the optimal twin attribute set are taken as the twin values when constructing the imitable twin attributes, i.e., the simulation values of the twin attributes B in the optimal twin attribute set are taken as the simulation values of all the twin attributes B in the entire twin.

[0071] In an example, according to one or more of the accuracy of data collection A, the accuracy of data collection C, the accuracy of the simulation values of the twin attributes B in the first twin attribute set, the accuracy of the simulation values of the twin attributes B in the second twin attribute set, and the simulation calculation resource, the two sets of twin attributes are evaluated to determine the optimal twin attribute set. It can be considered that the accuracy of the simulation values of the twin attributes B based on the optimal twin attribute set is higher.

[0072] In a possible implementation of the present application, the twin attribute set includes a first twin attribute, a last twin attribute, and a plurality of intermediate twin attributes, the simulation algorithm is to simulate the simulation values of the intermediate twin attributes according to the collection values of the first twin attribute, and the simulation values of the last twin attribute are obtained by multi-level simulation among the plurality of intermediate twin attributes. That is, the service is transmitted level by level, such as end-to-end service.

[0073] The construction scheme of the twin attribute set includes one of the following: the first twin attribute and the last twin attribute are imitable twin attributes; the first twin attribute, the last twin attribute, and at least one intermediate twin attribute are imitable twin attributes.

[0074] In an example, in the case where the construction scheme is that the first twin attribute and the last twin attribute are imitable twin attributes, for example, the twin attribute A and the twin attribute X are imitable twin attributes, the intermediate twin attributes between the twin attribute A and the twin attribute X are imitable twin attributes, the simulation value of the twin attribute B is simulated by collecting the collection value of the twin attribute A, the simulation value of the twin attribute C is simulated by the twin attribute B, the simulation value of the twin attribute D is simulated by the twin attribute C, and so on until the simulation value of the twin attribute X is simulated. Finally, the error between the simulation value of the twin attribute X and the actual value, and the error between the collection value of the twin attribute X and the actual value are compared to determine whether the simulation value of the twin attribute X meets the preset condition. In the case where the error between the simulation value of the twin attribute X and the actual value is less than or equal to the error between the collection value of the twin attribute X and the actual value, the simulation values of the intermediate twin attributes between the twin attribute A and the twin attribute X are taken as the twin values when constructing the intermediate twin attributes.

[0075] In an example, in a case where the construction scheme is that the first twin attribute, the last twin attribute and at least one intermediate twin attribute are adoptable twin attributes, for example, the twin attribute A, the twin attribute C and the twin attribute X are adoptable twin attributes, and the intermediate twin attributes between the twin attribute B, the twin attribute C and the twin attribute X are imitable twin attributes. The simulation value of the twin attribute B is obtained by simulation based on the collection value of the twin attribute A, the collection value of the twin attribute C is taken as the twin value when the twin attribute C is constructed, and then the simulation value of the twin attribute D is obtained by simulation based on the twin attribute C, and so on until the simulation value of the twin attribute X is obtained. The error between the simulation value and the actual value of the twin attribute X is compared with the error between the collection value and the actual value of the twin attribute X, and it is determined whether the simulation value of the twin attribute X meets the preset condition. In a case where the error between the simulation value and the actual value of the twin attribute X is less than or equal to the error between the collection value and the actual value of the twin attribute X, the intermediate twin attributes between the twin attribute B, the twin attribute C and the twin attribute X can be taken as imitable twin attributes.

[0076] In a possible implementation of the present application, the data collection method can further include: in a case where the simulation value of the last twin attribute is abnormal, determining that the simulation values of the intermediate twin attributes are abnormal; locating the intermediate twin attribute with the abnormal simulation value, and taking the first twin attribute, the last twin attribute and the located intermediate twin attribute as adoptable twin attributes.

[0077] That is, if the simulation value of the last twin attribute, i.e., the last twin attribute, is abnormal, it is determined that the simulation values of the intermediate twin attributes are abnormal, and the abnormal intermediate twin attribute needs to be located. The intermediate twin attribute with the abnormal simulation value is determined, and the collection value is taken as the twin value of the intermediate twin attribute to perform subsequent simulation, so as to eliminate the abnormality and ensure that the simulation value of the last twin attribute meets the preset condition. For example, the simulation values can be compared with the actual values level by level to determine the abnormal intermediate twin attribute. Alternatively, several intermediate twin attributes can be checked according to experience. The actual application is used as the criterion, and the present embodiment is not limited. That is, in a case where the intermediate twin attribute with the abnormal simulation value is located, the first twin attribute, the last twin attribute and the located intermediate twin attribute are taken as adoptable twin attributes, i.e., the collection value is taken as the twin value of these twin attributes, and the other intermediate twin attributes are imitable twin attributes, i.e., the simulation value is taken as the twin value.

[0078] FIG. 4 is a schematic diagram of level-by-level simulation of multiple-level twin attributes. Multiple devices in series can transmit services level by level.

[0079] That is, the simulation result can be compared at the last stage, for example, the data of device A is collected, the twin value of twin attribute A in the twin body is obtained, the simulation of the twin attribute A is performed by the twin simulation algorithm, the simulation value of the twin attribute B of device B in the twin body is obtained, the simulation of the twin attribute B is performed by the twin simulation algorithm, the simulation value of the twin attribute C of device C in the twin body is obtained, the error between the simulation value and the actual value is compared with the error between the collected value and the actual value of the twin attribute C, if the error between the simulation value and the actual value is less than or equal to the error between the collected value and the actual value, it is indicated that the simulation value of the twin attribute C obtained by simulating the data of device A is feasible, and the data collected by device B can be cancelled, that is, only the data of device A and device C needs to be collected.

[0080] The simulation can also be performed in the middle stage, and the simulation result can be compared at the last stage, for example, the data of device A is collected, the twin value of twin attribute A in the twin body is obtained, the simulation of the twin attribute A is performed by the twin simulation algorithm, the first simulation value of the twin attribute B of device B in the twin body is obtained, the data of device C is collected, the twin value of twin attribute C in the twin body is obtained, the simulation of the twin attribute C is performed by the twin simulation algorithm, the second simulation value of the twin attribute B of device B in the twin body is obtained, the error between the first simulation value and the actual value of the twin attribute B is compared with the error between the collected value and the actual value of the twin attribute B, if the error between the first simulation value and the actual value is less than the error between the collected value and the actual value, and the error between the first simulation value and the actual value is less than the error between the second simulation value and the actual value, the simulation value of the twin attribute B obtained by simulating the data of device A is used as the twin value of the twin attribute B, and the data of device C is collected, that is, the data collected by device B can be cancelled, and the simulation value of the twin attribute B in the twin body corresponding to device B is obtained by simulating the twin value of the twin attribute A; if the error between the second simulation value and the actual value is less than the error between the collected value and the actual value, and the error between the second simulation value and the actual value is less than the error between the first simulation value and the actual value, the simulation value of the twin attribute B obtained by simulating the data of device C is used as the twin value of the twin attribute B, and the data of device A is collected, that is, the data collected by device B can be cancelled, and the simulation value of the twin attribute B in the twin body corresponding to device B is obtained by simulating the twin value of the twin attribute C. In this embodiment, the twin value of the twin attribute B is more accurate.

[0081] The first level can also be simulated in reverse for comparison, for example, collecting data of device C, corresponding to the twin value of twin attribute C in the twin body, simulating the twin value of twin attribute C through the twin simulation algorithm, obtaining the simulation value of twin attribute B of device B in the twin body, simulating twin attribute B through the twin simulation algorithm, obtaining the simulation value of twin attribute A of device A in the twin body, comparing the error between the simulation value and the actual value, and the error between the collected value and the actual value of twin attribute A, if the error between the simulation value and the actual value is less than or equal to the error between the collected value and the actual value, it is feasible to simulate the simulation value of twin attribute A by collecting the data of device C, at this time, the data collected by device B can be cancelled, that is, only the data of device A and device C need to be collected.

[0082] The above three schemes can also be evaluated by one or more of the accuracy of the collected data, the accuracy of the simulation value, and the simulation calculation resources in the above scheme to determine the best scheme. That is, when there are multiple candidate schemes, the selected scheme can be comprehensively evaluated from the collection difficulty, the required resources and calculation accuracy of simulation calculation, data collection accuracy, and the like, and selected according to the evaluation result.

[0083] FIG. 5 is a schematic diagram of a data collection device provided by an embodiment of the present application. As shown in FIG. 5, the data collection device can include a first determination module 501, a simulation module 502, a second determination module 503, and a first modification module 504.

[0084] The first determination module 501 is configured to collect the value of the collectable twin attribute in the twin body as the twin value when constructing the collectable twin attribute. The simulation module 502 is configured to simulate the twin value based on the twin simulation algorithm to obtain the simulation value of the simulatable twin attribute. The second determination module 503 is configured to, in a case where the simulation value meets a preset condition, use the simulation value as the twin value when constructing the simulatable twin attribute. The first modification module 504 is configured to modify the collection configuration to reduce or cancel the collection of the collected value of the simulatable twin attribute by the optical network device.

[0085] In the embodiments of the present application, the first determining module 501 first takes the collected value of the collectable twin attribute in the twin as the twin value when the collectable twin attribute is constructed, then the simulation module 502 simulates the twin value based on the twin simulation algorithm to obtain a simulation value of the simulatable twin attribute, the second determining module 503 takes the simulation value as the twin value when the simulatable twin attribute is constructed in the case that the simulation value meets the preset condition, and finally the first modifying module 504 modifies the collection configuration to reduce or cancel the collection of the collected value of the simulatable twin attribute by the optical network device. The simulation value of the simulatable twin attribute is replaced with the original collected value as the source of the twin value in the embodiments of the present application, so that the collected data of the physical device can be reduced, the collection pressure can be relieved, and the data collection efficiency can be improved. In the case that the simulation value does not meet the requirement, the collected value is used to ensure that the requirement of the twin construction is met.

[0086] In a possible implementation of the present application, the second determining module 503 is configured to calculate a first error between the simulation value of the simulatable twin attribute and the actual value, and a second error between the collected value of the simulatable twin attribute and the actual value; and take the simulation value as the twin value when the simulatable twin attribute is constructed in the case that the first error is less than or equal to the second error.

[0087] In a possible implementation of the present application, the second determining module 503 is configured to take the simulation value as the twin value when the simulatable twin attribute is constructed in the case that the error between the simulation value and the collected value of the simulatable twin attribute is less than a first threshold.

[0088] In a possible implementation of the present application, the modification of the collection configuration includes at least one of the following: shielding performance alarms; canceling the subscription operation for telemetry collection reporting; prolonging the period of data collection reporting; and changing the reporting form of the collection item.

[0089] In a possible implementation of the present application, the data collection device can further include a third determining module and a second modifying module.

[0090] The third determining module is configured to take the collected value as the twin value when the simulatable twin attribute is constructed in the case that an abnormal event is detected; and the second modifying module is configured to modify the collection configuration again to restore the collection of the collected value of the simulatable twin attribute by the optical network device. The abnormal event includes at least one of the following: an abnormality occurs in the process of simulation based on the twin simulation algorithm; an alarm report affecting data collection is received; and the performance of the twin value used for simulation abnormally jumps.

[0091] In a possible implementation of the present application, the modification of the collection configuration again includes at least one of the following: issuing a query command to update the current state; canceling the shielding of performance alarms; and shortening the period of data collection reporting.

[0092] In a possible implementation of the present application, the twin body includes a plurality of twin attributes, which form a twin attribute set. A part of the twin attribute set is a collectable twin attribute, and the remaining twin attributes are imitable twin attributes, which form a construction scheme of the twin attribute set.

[0093] The second determining module 503 is configured to: obtain different construction schemes of the twin attribute set by dividing different twin attributes into collectable twin attributes and taking the remaining twin attributes as imitable twin attributes; determine simulation values of the imitable twin attributes corresponding to all the construction schemes; evaluate the plurality of construction schemes to determine an optimal construction scheme; and in a case where a simulation value of the optimal construction scheme meets a preset condition, apply the optimal construction scheme and take the simulation values of all the imitable twin attributes in the optimal construction scheme as twin values for constructing the imitable twin attributes.

[0094] In a possible implementation of the present application, the second determining module 503 is configured to evaluate the plurality of construction schemes according to one or more of the following: a number of the collectable twin attributes, a collection value precision, a number of the imitable twin attributes, a simulation value precision, and a simulation calculation resource.

[0095] In a possible implementation of the present application, the second determining module 503 is configured to: select one construction scheme from the plurality of construction schemes as the optimal construction scheme according to an evaluation result; and in a case where the optimal construction scheme is abnormal, re-evaluate the plurality of construction schemes to determine a new optimal construction scheme, and switch the optimal construction scheme to the new optimal construction scheme.

[0096] In a possible implementation of the present application, the twin attribute set includes a first twin attribute and a second twin attribute, and the construction scheme of the twin attribute set includes one of the following: the first twin attribute is a collectable twin attribute; and the second twin attribute is a collectable twin attribute.

[0097] In a possible implementation of the present application, the twin body includes a plurality of twin attribute sets. The second determining module 503 is configured to: in a case where there is a same imitable twin attribute between the plurality of twin attribute sets, determine an optimal twin attribute set based on simulation values of the imitable twin attributes in each twin attribute set; and take the simulation values of the imitable twin attributes in the optimal twin attribute set as twin values for constructing the imitable twin attributes.

[0098] In a possible implementation of the present application, the set of twin attributes includes a first twin attribute, a last twin attribute, and a plurality of intermediate twin attributes, the twin simulation algorithm is to obtain a simulation value of the last twin attribute according to multi-level simulation of a collection value of the first twin attribute, and the construction scheme of the set of twin attributes includes one of the following: the first twin attribute and the last twin attribute are collectable twin attributes; the first twin attribute, the last twin attribute, and at least one intermediate twin attribute are collectable twin attributes.

[0099] In a possible implementation of the present application, the data collection device can further include a positioning module.

[0100] The positioning module is configured to determine that there is an abnormal simulation value of an intermediate twin attribute in a case where the simulation value of the last twin attribute is abnormal, position the intermediate twin attribute with the abnormal simulation value, and take the first twin attribute, the last twin attribute, and the positioned intermediate twin attribute as collectable twin attributes.

[0101] The data collection device provided by the embodiments of the present application can implement each process implemented by the method embodiments of FIGS. 1-4, and achieve the same technical effects. To avoid repetition, details are not described herein.

[0102] As shown in FIG. 6, the embodiments of the present application further provide an electronic device 600, which includes a processor 601, a memory 602, a program or instruction stored in the memory 602 and executable on the processor 601. When the program or instruction is executed by the processor 601, each process of the above-mentioned data collection method embodiments is implemented, and the same technical effects can be achieved. To avoid repetition, details are not described herein.

[0103] The embodiments of the present application further provide a storage medium, which stores a program or instruction. When the program or instruction is executed by a processor, each process of the data collection method embodiments provided by any of the above-mentioned embodiments is implemented. The same technical effects can be achieved. To avoid repetition, details are not described herein.

[0104] The processor is the processor in the electronic device described in the above-mentioned embodiments. The storage medium includes a computer storage medium, such as a computer read-only memory (Read-Only Memory, ROM), a random access memory (Random Access Memory, RAM), a magnetic disk, or an optical disk.

[0105] The embodiments of the present application further provide a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is configured to run a program or instruction to implement each process of the above-mentioned data collection method embodiments, and achieve the same technical effects. To avoid repetition, details are not described herein.

[0106] It should be understood that the chip mentioned in the embodiments of the present application can also be referred to as a system-level chip, a system chip, a chip system, or a system-on-chip, etc.

[0107] The embodiments of the present application further provide a computer program / program product stored in a storage medium, which is executed by at least one processor to implement the processes of the above-mentioned data acquisition method embodiments, and can achieve the same technical effects. To avoid repetition, details are not described here.

[0108] The embodiments of the present application further provide a processing device configured to execute the processes of the above-mentioned data acquisition method embodiments, and can achieve the same technical effects. To avoid repetition, details are not described here.

[0109] It should be noted that in this document, the terms "comprising", "including", or any other variant thereof are intended to cover non-exclusive inclusion, so that processes, methods, articles, or devices including a series of elements not only include those elements, but also include other elements not explicitly listed, or further include elements inherent to such processes, methods, articles, or devices. Without more limitations, the element defined by the statement "including a" does not exclude the presence of additional identical elements in the process, method, article, or device including the element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to the order of performing the functions as shown or discussed, but can also include performing the functions in a substantially simultaneous manner or in reverse order, for example, the described method can be performed in an order different from the described order, and various steps can also be added, omitted, or combined. In addition, the features described with reference to certain examples can be combined in other examples.

[0110] From the above description of the embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be realized by means of software and necessary general hardware platforms, of course, they can also be realized by hardware, but in many cases the former is a better embodiment. Based on such understanding, the technical solutions of the present application can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a plurality of instructions for making a terminal (which can be a mobile phone, computer, server, or network equipment, etc.) execute the methods described in the embodiments of the present application.

[0111] The embodiments of the present application are described above with reference to the accompanying drawings, but the present application is not limited to the specific embodiments described above, and the specific embodiments described above are merely illustrative, but not restrictive, and a person of ordinary skill in the art can make many forms under the inspiration of the present application without departing from the purpose of the present application and the scope protected by the claims.

Claims

1. A data collection method, comprising: collecting a twin value of a collectable twin attribute in a twin body as a twin value when constructing the collectable twin attribute; simulating the twin value based on a twin simulation algorithm to obtain a simulation value of a simulatable twin attribute; in a case where the simulation value meets a preset condition, taking the simulation value as the twin value when constructing the simulatable twin attribute; modifying a collection configuration to reduce or cancel collection of the simulation value of the simulatable twin attribute by an optical network device.

2. The method of claim 1, wherein, in the case where the simulation value meets the preset condition, taking the simulation value as the twin value when constructing the simulatable twin attribute, comprising: calculating a first error between the simulation value and an actual value of the simulatable twin attribute, and a second error between a collection value and the actual value of the simulatable twin attribute; in a case where the first error is less than or equal to the second error, taking the simulation value as the twin value when constructing the simulatable twin attribute.

3. The method of claim 1, wherein, in the case where the simulation value meets the preset condition, taking the simulation value as the twin value when constructing the simulatable twin attribute, comprising: in a case where an error between the simulation value and the collection value of the simulatable twin attribute is less than a first threshold, taking the simulation value as the twin value when constructing the simulatable twin attribute.

4. The method of claim 1, wherein, the modification of the collection configuration comprises at least one of: masking a performance alarm; canceling a subscription operation for telemetry collection reporting; extending a period of data collection reporting; changing a reporting form of a collection item.

5. The method of claim 1, wherein, after the taking of the simulation value as the twin value when constructing the simulatable twin attribute, further comprising: in a case where an abnormal event is detected, taking the collection value as the twin value when constructing the simulatable twin attribute; modifying the collection configuration again to restore the collection of the simulation value of the simulatable twin attribute by the optical network device; the abnormal event comprises at least one of: an abnormality occurring in a process of simulating based on the twin simulation algorithm; receiving an alarm report affecting data collection; an abnormal jump of a performance of the twin value used for simulation.

6. The method of claim 5, wherein, the modification of the collection configuration again comprises at least one of: issuing a query command to update a current state; canceling the masking of the performance alarm; shortening the period of the data collection reporting.

7. The method of claim 1, wherein, the twin body comprises a plurality of twin attributes, forming a twin attribute set, a part of the twin attribute set is the collectable twin attribute, and the remaining twin attribute is the simulatable twin attribute, forming a construction scheme of the twin attribute set; in the case where the simulation value meets the preset condition, taking the simulation value as the twin value when constructing the simulatable twin attribute, comprising: obtaining different construction schemes of the twin attribute set by dividing different twin attributes into the collectable twin attribute, and taking the remaining twin attributes as the simulatable twin attribute; determining simulation values of the simulatable twin attributes corresponding to all the construction schemes; evaluating the plurality of construction schemes to determine an optimal construction scheme; in a case where the simulation value of the optimal construction scheme meets the preset condition, applying the optimal construction scheme, and taking the simulation values of all the simulatable twin attributes in the optimal construction scheme as the twin values when constructing the simulatable twin attribute.

8. The method of claim 7, wherein, The evaluating the multiple construction schemes comprises: The evaluating the multiple construction schemes comprises one or more of the following: the number of collectable twin attributes, the accuracy of collected values, the number of imitable twin attributes, the accuracy of simulated values, and simulation computing resources.

9. The method of claim 7, wherein, The determining the optimal construction scheme comprises: According to the evaluation result, one construction scheme is selected from the multiple construction schemes as the optimal construction scheme; In the case that the optimal construction scheme is abnormal, the multiple construction schemes are re-evaluated to determine a new optimal construction scheme, and the optimal construction scheme is switched to the new optimal construction scheme.

10. The method of claim 7, wherein, The twin attribute set comprises a first twin attribute and a second twin attribute, The construction scheme of the twin attribute set comprises one of the following: The first twin attribute is a collectable twin attribute; The second twin attribute is a collectable twin attribute.

11. The method of claim 7, wherein, The twin body comprises multiple sets of twin attribute sets, and the simulation value is used as a twin value for constructing the imitable twin attribute, which comprises: In the case that the multiple sets of twin attribute sets have the same imitable twin attribute, the simulation value of the imitable twin attribute in each set of twin attribute sets is determined as the optimal twin attribute set; The simulation value of the imitable twin attribute in the optimal twin attribute set is used as a twin value for constructing the imitable twin attribute.

12. The method of claim 7, wherein, The twin attribute set comprises a first twin attribute, a last twin attribute, and multiple intermediate twin attributes, and the twin simulation algorithm is a multi-level simulation based on the collected value of the first twin attribute to obtain the simulation value of the last twin attribute, The construction scheme of the twin attribute set comprises one of the following: The first twin attribute and the last twin attribute are collectable twin attributes; The first twin attribute, the last twin attribute, and at least one intermediate twin attribute are collectable twin attributes.

13. The method of claim 12, wherein, The method further comprises: In the case that the simulation value of the last twin attribute is abnormal, it is determined that the simulation value of the intermediate twin attribute is abnormal; The simulation value of the intermediate twin attribute is located, and the first twin attribute, the last twin attribute, and the located intermediate twin attribute are used as collectable twin attributes.

14. An electronic device comprising a processor, a memory, and a program or instructions stored on the memory and executable on the processor, the program or instructions being executed by the processor to implement the steps of the method of any one of claims 1 to 13.

15. A storage medium having a program or instructions stored thereon, the program or instructions being executed by a processor to implement the steps of the method of any one of claims 1 to 13.

16. A program product stored in a storage medium, the program product being executed by at least one processor to implement the steps of the method of any one of claims 1 to 13.

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