Monitoring Data Hierarchical Management Method, Device and Equipment Based on Charging Cloud Platform

Abstract

An embodiment of the present application discloses a method, device and equipment for hierarchical management of monitoring data based on a charging cloud platform, which relates to the field of data processing. The method includes the following steps: classifying and dividing the charging monitoring data of the charging cloud platform to generate dimension data, and setting flow control thresholds for at least part of the dimension data; statistically calculating the TPS value of the dimension data in real time, and determining whether a flow control threshold has been set for the current dimension data. If so, perform a flow control operation on the current dimension data based on the flow control threshold; if not, perform a fusing operation on the current dimension data based on the maximum threshold. The present application adopts a hierarchical management method to adopt different control strategies for monitoring data of different dimensions, avoiding the impact of a sudden increase in one dimension data on the entire reporting process, and effectively ensuring the continuous and normal processing of monitoring data.

Description

Technical Field

[0001] The present invention relates to the field of data processing, and more particularly to a method, device, and equipment for hierarchical management of monitoring data based on a charging cloud platform. Background Art

[0002] In the prior art, the method for collecting and managing monitoring data of a charging cloud platform generally adopts a one-size-fits-all approach, that is, once the monitoring data exceeds a set threshold, a fusing process is performed to prevent the monitoring client from being overwhelmed. The problems with this approach are that, on the one hand, the fusing strategy is too single, and a sudden increase in monitoring data in one dimension will cause the entire monitoring management system to fuse, thus affecting the normal reporting of monitoring data in other dimensions; on the other hand, for the fusing threshold, a fixed value setting method is used, and there is no mechanism for flexibly adjusting the fusing threshold.

[0003] Therefore, based on the problems existing in the monitoring data management of the existing charging cloud platform, it is necessary to provide a method for hierarchical management of monitoring data to avoid affecting the entire monitoring reporting process due to abnormal monitoring data in one dimension. Summary of the Invention

[0004] The purpose of the present invention is to provide a method, device, and equipment for hierarchical management of monitoring data based on a charging cloud platform, which uses a hierarchical management method to perform different processing on monitoring data in different dimensions, effectively ensuring the normal and continuous reporting of monitoring data.

[0005] To achieve the above object, the present invention discloses the following technical solutions:

[0006] On the one hand, the present invention provides a method for hierarchical management of monitoring data based on a charging cloud platform, the method comprising the following steps:

[0007] Classify and divide the charging monitoring data of the charging cloud platform to generate dimension data, and set a flow control threshold for at least part of the dimension data;

[0008] Real-time statistics of the TPS value of the dimension data, and determine whether a flow control threshold has been set for the current dimension data,

[0009] If so, perform a flow control operation on the current dimension data based on the flow control threshold;

[0010] If not, perform a fusing operation on the current dimension data based on the maximum threshold.

[0011] In the above method for hierarchical management of monitoring data, the dimension data includes one or a combination of several of charging start frequency monitoring data, charging order quantity monitoring data, charging source monitoring data, data cleaning rate monitoring data, and data reporting delay monitoring data.

[0012] The above-mentioned monitoring data hierarchical management method, the step of setting a flow control threshold for dimension data further includes:

[0013] Configure the flow control method for the dimension data according to the data importance, data change speed, and / or data stability of the dimension data. Preferably, the flow control methods include degradation, flow limiting, and fusing.

[0014] Based on the flow control method of the dimension data, set the flow control threshold corresponding to the flow control method.

[0015] Furthermore, the flow control thresholds include: degradation threshold, flow limiting threshold, and fusing threshold.

[0016] The above-mentioned monitoring data hierarchical management method, the flow control operations include:

[0017] Degradation processing: used for when the TPS value of the current dimension data exceeds the degradation threshold, give priority to reporting other dimension data, and then report the current dimension data.

[0018] Flow limiting processing: used for when the TPS value of the current dimension data exceeds the flow limiting threshold, report the data within the flow limiting threshold, and the data exceeding the flow limiting threshold is discarded; and

[0019] Fusing processing: used for when the TPS value of the current dimension data exceeds the fusing threshold, directly stop reporting the current dimension data.

[0020] The above-mentioned monitoring data hierarchical management method, the step of performing flow control operations on the current dimension data based on the flow control threshold further includes:

[0021] Judge whether the TPS value of the current dimension data exceeds the fusing threshold.

[0022] If so, directly perform fusing processing on the current dimension data.

[0023] If not, continue to judge whether the TPS value of the current dimension data exceeds the flow limiting threshold.

[0024] If it is, perform flow limiting processing on the current dimension data.

[0025] If not, continue to judge whether the TPS value of the current dimension data exceeds the degradation threshold.

[0026] If so, perform degradation processing on the current dimension data.

[0027] If not, perform normal reporting on the current dimension data.

[0028] The above-mentioned monitoring data hierarchical management method, the step of performing a fusing operation on the current dimension data based on the maximum threshold further includes:

[0029] Determine whether the TPS value of the current dimension data exceeds the maximum threshold.

[0030] If so, directly perform fusing processing on the current dimension data;

[0031] If not, normally report the current dimension data.

[0032] Preferably, the flow control threshold is determined based on the daily average TPS and peak TPS of the dimension data within the set charging date, that is:

[0033] Flow control threshold = (daily average TPS + peak TPS) / 2 × M, where 100% ≤ M ≤ 200%.

[0034] Preferably, the fusing threshold and the maximum threshold are determined based on the memory resources of the charging cloud platform server host, the size of the monitoring data, and the data processing time.

[0035] On the other hand, the present invention provides a monitoring data hierarchical management device based on a charging cloud platform. The device includes:

[0036] A data partitioning module, configured to classify and partition the charging monitoring data of the charging cloud platform to generate dimension data, and set a flow control threshold for at least part of the dimension data;

[0037] A judgment module, configured to statistically calculate the TPS value of the dimension data in real time and judge whether a flow control threshold has been set for the current dimension data.

[0038] A flow control module, configured to perform a flow control operation on the current dimension data based on the flow control threshold when it is judged that a flow control threshold has been set for the current dimension data;

[0039] A fusing module, configured to perform a fusing operation on the current dimension data based on the maximum threshold when it is judged that a flow control threshold has not been set for the current dimension data.

[0040] Preferably, the flow control threshold includes: a degradation threshold, a flow limiting threshold, and a fusing threshold.

[0041] For the above-mentioned monitoring data hierarchical management device, the flow control operation includes:

[0042] Degradation processing: used for when the TPS value of the current dimension data exceeds the degradation threshold, first report other dimension data, and then report the current dimension data;

[0043] Current limit processing: When the TPS value of the current dimension data exceeds the current limit threshold, report the data within the current limit threshold, and discard the data exceeding the current limit threshold; and,

[0044] Fuse processing: When the TPS value of the current dimension data exceeds the fuse threshold, directly stop reporting the current dimension data.

[0045] For the above-mentioned monitoring data hierarchical management device, the steps of the flow control module performing flow control operations on the current dimension data based on the flow control threshold include:

[0046] Judge whether the TPS value of the current dimension data exceeds the fuse threshold,

[0047] If so, directly perform fuse processing on the current dimension data;

[0048] If not, continue to judge whether the TPS value of the current dimension data exceeds the current limit threshold,

[0049] If so, perform current limit processing on the current dimension data;

[0050] If not, continue to judge whether the TPS value of the current dimension data exceeds the downgrade threshold,

[0051] If so, perform downgrade processing on the current dimension data;

[0052] If not, report the current dimension data normally.

[0053] For the above-mentioned monitoring data hierarchical management device, the steps of the fuse module performing fuse operations on the current dimension data based on the maximum threshold include:

[0054] Judge whether the TPS value of the current dimension data exceeds the maximum threshold,

[0055] If so, directly perform fuse processing on the current dimension data;

[0056] If not, report the current dimension data normally.

[0057] On the other hand, the present invention provides a monitoring data hierarchical management system based on a charging cloud platform, and the system includes a charging cloud platform and at least one charging device:

[0058] The charging device is installed with a monitoring client for collecting and sending charging monitoring data to the charging cloud platform;

[0059] The charging cloud platform is provided with a monitoring cluster, and the monitoring cluster includes the monitoring data hierarchical management device based on the charging cloud platform as described above, which is used to hierarchically manage the charging monitoring data sent by the charging device.

[0060] The present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the above-mentioned monitoring data hierarchical management method based on the charging cloud platform is implemented.

[0061] In addition, the present invention also provides an electronic device, which includes a memory, a processor, and a computer program stored on the memory and operable on the processor. When the processor executes the computer program, the above-mentioned monitoring data hierarchical management method based on the charging cloud platform is implemented.

[0062] The effects provided in the summary of the invention are only the effects of the embodiments, rather than all the effects of the invention. One of the above technical solutions has the following advantages or beneficial effects:

[0063] In the embodiment of the present application, by refining the source of the monitoring data of the charging cloud platform, classifying and dividing the monitoring data, and adopting a hierarchical management method to adopt different flow control or fusing strategies for different monitoring data, it avoids the impact of the sudden increase of monitoring data in one dimension on the entire monitoring reporting process, and meets the processing of some monitoring data with excessive traffic. In addition, the flow control threshold and the maximum threshold can be dynamically adjusted based on the load situation, maximizing the processing capacity of the monitoring client and effectively ensuring that the monitoring data is continuously processed. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] The accompanying drawings here are incorporated into the specification and form a part of the specification, showing the embodiments consistent with the present application, and are used together with the specification to explain the principles of the present application.

[0065] Figure 1 It is a schematic flowchart of the monitoring data hierarchical management method based on the charging cloud platform provided by an embodiment of the present application;

[0066] Figure 2 It is a schematic flowchart of the monitoring data hierarchical management method based on the charging cloud platform provided by another embodiment of the present application;

[0067] Figure 3 It is a schematic structural diagram of the monitoring data hierarchical management device based on the charging cloud platform provided by an embodiment of the present application;

[0068] Figure 4 It is a schematic structural diagram of the monitoring data hierarchical management system based on the charging cloud platform provided by an embodiment of the present application;

[0069] Figure 5 Schematic diagram of the structure of an electronic device provided by an embodiment of the present application;

[0070] Reference numerals:

[0071] 300 - Monitoring data hierarchical management device, 310 - Data partitioning module, 320 - Judgment module, 330 - Flow control module, 340 - Fuse module;

[0072] 400 - Monitoring data hierarchical management system, 410 - Charging cloud platform, 411 - Monitoring cluster, 420 - Charging device;

[0073] 500 - Electronic device, 510 - Input unit, 520 - Memory, 530 - Processor, 540 - Output unit. Detailed implementation manners

[0074] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0075] It should be noted that the references to "one embodiment", "embodiment", "example embodiment", etc. in this specification mean that the described embodiment may include specific features, structures or characteristics, but not every embodiment must include these specific features, structures or characteristics. In addition, such expressions do not refer to the same embodiment. Further, when combining an embodiment to describe specific features, structures or characteristics, whether or not there is an explicit description, it has been shown that it is within the knowledge scope of those skilled in the art to combine such features, structures or characteristics into other embodiments.

[0076] In addition, in this specification and subsequent claims, certain terms are used to refer to specific components or parts. Those of ordinary skill in the art should understand that manufacturers may use different nouns or terms to refer to the same component or part. This specification and subsequent claims do not use the difference in names as a way to distinguish components or parts, but use the difference in functions of components or parts as the criterion for distinction. The terms "including" and "comprising" mentioned throughout this specification and subsequent claims are open-ended terms, so they should be interpreted as "including but not limited to". In addition, the term "connection" herein includes any direct and indirect electrical connection means. Indirect electrical connection means include connection through other devices.

[0077] Refer to Figure 1 , Figure 1The figure shows a schematic flow chart of a monitoring data hierarchical management method based on a charging cloud platform provided by an embodiment of the present application. The method includes the following steps:

[0078] S110. Classify and divide the charging monitoring data of the charging cloud platform to generate dimension data, and set flow control thresholds for at least part of the dimension data;

[0079] S120. Real-time count the TPS value of the dimension data, and determine whether a flow control threshold has been set for the current dimension data.

[0080] S130. If so, perform a flow control operation on the current dimension data based on the flow control threshold;

[0081] S140. If not, perform a fusing operation on the current dimension data based on the maximum threshold.

[0082] As described above, the existing monitoring data collection and management method of the charging cloud platform adopts a one-size-fits-all processing method. Once the monitoring data exceeds the set threshold, it will be fused, resulting in the problem that the normal reporting of other dimension monitoring data is affected by the sudden increase of one dimension monitoring data. In this embodiment, by classifying and dividing the monitoring data and adopting different flow control or fusing strategies for different monitoring data, the normal and continuous reporting of the monitoring data is effectively guaranteed.

[0083] Reference Figure 2 , Figure 2 The figure shows a schematic flow chart of a monitoring data hierarchical management method based on a charging cloud platform provided by another embodiment of the present application. The method includes the following steps:

[0084] S210. Classify and divide the charging monitoring data of the charging cloud platform to generate dimension data, and set flow control thresholds for at least part of the dimension data;

[0085] In a specific implementation, the dimension data is the result of classifying and dividing the charging monitoring data. For example, in an implementation manner, program A reports charging monitoring data A, and program B reports charging monitoring data B. A and B correspond to two dimensions of monitoring data, that is, two dimension data.

[0086] In some embodiments, the dimension data may specifically include charging start frequency monitoring data, i.e., frequency monitoring data of the charging start request invocation; charging order quantity monitoring data, i.e., monitoring data of the charging order quantity statistics; charging source monitoring data, i.e., monitoring data of the number of charging requests initiated by the initiator of the charging request per second; data cleaning rate monitoring data, i.e., monitoring data of the amount of data received in the streaming data processing system and the amount of data sent to the downstream business system after being cleaned by the system; data reporting delay monitoring data, i.e., monitoring data of the difference between the current timestamp and the data timestamp in the streaming data processing system. Flow control thresholds may be set for some or all of the dimension data according to specific circumstances.

[0087] In some embodiments, the step of setting flow control thresholds for the dimension data may further include:

[0088] Configure the flow control mode of the dimension data according to the data importance, data change speed, and / or data smoothness of the dimension data. The flow control mode may include degradation, flow limiting, and fusing;

[0089] Based on the flow control mode of the dimension data, set the flow control threshold corresponding to the flow control mode.

[0090] Preferably, in some embodiments, the flow control thresholds of the dimension data may include a degradation threshold, a flow limiting threshold, and a fusing threshold, and the fusing threshold ≥ the flow limiting threshold ≥ the degradation threshold. The flow limiting threshold is usually determined based on the daily average TPS and peak TPS of the dimension data within the set charging time. The initial flow limiting threshold uses an empirical value. After the system runs for a period of time, it is dynamically adjusted according to the TPS value. For example, (daily average TPS + peak TPS) / 2×M may be used as the flow limiting threshold, where 100% ≤ M ≤ 200%, and the value of M may be set according to the data change speed and data smoothness of different dimension data according to specific circumstances. The fusing threshold is usually determined based on the memory resources of the charging cloud platform server host, the size of the monitoring data, and the data processing time. For example, it can be calculated according to the maximum allowable use of 20% of the host memory resources of the cloud platform server, 2K for each average monitoring data, and 10s for each data to be processed.

[0091] S220. Real-time statistics of the TPS value of the dimension data, and determine whether a flow control threshold has been set for the current dimension data.

[0092] S230. If so, perform a flow control operation on the current dimension data based on the flow control threshold. In some embodiments, the flow control operation includes:

[0093] Degradation processing: When the TPS value of the current dimension data exceeds the degradation threshold, give priority to reporting other dimension data, and then report the current dimension data.

[0094] Flow limiting process: used for reporting data within the flow limiting threshold when the TPS value of the current dimension data exceeds the flow limiting threshold, and discarding data exceeding the flow limiting threshold;

[0095] Fusing process: used for directly stopping the reporting of current dimension data when the TPS value of the current dimension data exceeds the fusing threshold.

[0096] Refer to Figure 2 As shown, in specific implementation, the step of performing flow control operation on current dimension data based on the flow control threshold may further include:

[0097] S231. Determine whether the TPS value of the current dimension data exceeds the fusing threshold,

[0098] S232. If so, directly perform fusing process on the current dimension data;

[0099] S233. If not, continue to determine whether the TPS value of the current dimension data exceeds the flow limiting threshold,

[0100] S234. If yes, perform flow limiting process on the current dimension data;

[0101] S235. If not, continue to determine whether the TPS value of the current dimension data exceeds the degradation threshold,

[0102] S236. If so, perform degradation process on the current dimension data;

[0103] S237. If not, perform normal reporting on the current dimension data.

[0104] S240. If not, perform fusing operation on the current dimension data based on the maximum threshold;

[0105] Specifically, if no flow control threshold and corresponding flow control policy are set for the current dimension data, perform fusing operation on it using the maximum threshold. In some embodiments, the maximum threshold can be set the same as the fusing threshold, and is determined based on the memory resources of the charging cloud platform server host, the size of the monitored data, and the data processing time.

[0106] Refer to Figure 2 As shown, in specific implementation, the step of performing fusing operation on current dimension data based on the maximum threshold may further include:

[0107] S241. Determine whether the TPS value of the current dimension data exceeds the maximum threshold,

[0108] S242. If so, directly perform fusing processing on the current dimensional data;

[0109] S243. If not, normally report the current dimensional data.

[0110] When the flow control threshold or the maximum threshold is set too large to meet the system load requirements, or set too small to meet the service requirements, such as when the charging service expands with the increase of charging terminals, the increase of centralized control, and the corresponding increase of the charging cloud server, the threshold configuration of the monitoring data of a certain dimension can be manually adjusted, and the monitoring client can obtain the configuration through the monitoring server and adjust the management strategy.

[0111] Taking the monitoring data of three dimensions as an example below, the implementation process can be as follows:

[0112] There are programs in the system that need to report three-dimensional data, namely charging source monitoring data, data reporting delay monitoring data, and charging start failure monitoring data. These three-dimensional data are respectively abbreviated as A, B, and C. In actual applications, the TPS of A, B, and C decreases in turn, but the importance of the programs increases in turn. The following flow control scheme is formulated according to the empirical values:

[0113] Data dimension Flow control threshold Flow control operation A Fuse threshold 10000 Fuse B Current limit threshold 5000 Current limit C Degradation threshold 2000 Degradation

[0114] Suppose a program on the current host abnormally reports a large amount of type A data, with a TPS of 20,000, exceeding the fusing threshold. At this time, the type A metadata will be directly discarded. Another example is that if there is an abnormal report of type B data with a TPS of 6,000, then only 5,000 pieces of data will be processed per second, and the others will be discarded.

[0115] While the monitoring client is running, it will also record the TPS of the three types of data A, B, and C into the time series database. The inspection program will analyze the trends of the TPS of these three types of data and dynamically adjust the flow limiting thresholds of the three types of data. For example, for type B data, its average daily TPS is 3,000, and the maximum TPS within 7 days is 5,000, then the flow limiting threshold can be set to (3,000 + 5,000) / 2 * 150% = 6,000, and this dynamic process will continue.

[0116] It should be noted that for the method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that the embodiments of the present application are not limited by the described action sequences, because according to the embodiments of the present application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily essential to the embodiments of the present application.

[0117] Refer to Figure 3 ,Figure 3 FIG. Figure 3 shows a schematic structural diagram of a monitoring data hierarchical management device provided by an embodiment of the present application. Using this device, hierarchical management of monitoring data based on a charging cloud platform can be achieved. The device described below can be correspondingly referred to the method described above. The monitoring data hierarchical management device 300 includes:

[0118] A data partitioning module 310, configured to classify and partition the charging monitoring data of the charging cloud platform to generate dimension data, and set flow control thresholds for at least part of the dimension data;

[0119] A judgment module 320, configured to statistically calculate the TPS value of the dimension data in real time, and judge whether a flow control threshold has been set for the current dimension data,

[0120] A flow control module 330, configured to perform a flow control operation on the current dimension data based on the flow control threshold when it is judged that a flow control threshold has been set for the current dimension data;

[0121] A fusing module 340, configured to perform a fusing operation on the current dimension data based on the maximum threshold when it is judged that no flow control threshold has been set for the current dimension data.

[0122] In some embodiments, the data partitioning module 310 sets flow control thresholds for the dimension data. The flow control thresholds may include a degradation threshold, a current limiting threshold, and a fusing threshold.

[0123] Based on the setting of the above flow control thresholds, the flow control module 330 performs a flow control operation on the current dimension data. The flow control operation may include:

[0124] Degradation processing: used for when the TPS value of the current dimension data exceeds the degradation threshold, giving priority to reporting other dimension data, and then reporting the current dimension data;

[0125] Current limiting processing: used for when the TPS value of the current dimension data exceeds the current limiting threshold, reporting the data within the current limiting threshold, and discarding the data exceeding the current limiting threshold;

[0126] Fusing processing: used for when the TPS value of the current dimension data exceeds the fusing threshold, directly stopping the reporting of the current dimension data.

[0127] In some embodiments, the step of the flow control module 330 performing a flow control operation on the current dimension data based on the flow control threshold may specifically include:

[0128] Judging whether the TPS value of the current dimension data exceeds the fusing threshold,

[0129] If so, directly perform fusing processing on the current dimension data;

[0130] If not, continue to determine whether the TPS value of the current dimension data exceeds the current limiting threshold.

[0131] If so, perform current limiting processing on the current dimension data.

[0132] If not, continue to determine whether the TPS value of the current dimension data exceeds the degradation threshold.

[0133] If so, perform degradation processing on the current dimension data.

[0134] If not, report the current dimension data normally.

[0135] In some embodiments, the fusing module 340 performs a fusing operation on the current dimension data based on a maximum threshold, which may specifically include:

[0136] Determine whether the TPS value of the current dimension data exceeds the maximum threshold.

[0137] If so, directly perform fusing processing on the current dimension data.

[0138] If not, report the current dimension data normally.

[0139] Based on the monitoring data hierarchical management device of the charging cloud platform in the above embodiments, the present application further provides a monitoring data hierarchical management system based on the charging cloud platform. In some embodiments, as Figure 4 shown, the monitoring data hierarchical management system 400 includes a charging cloud platform 410 and a plurality of charging devices 420:

[0140] The charging device 420 is installed with a monitoring client for collecting and sending charging monitoring data to the charging cloud platform 410.

[0141] The charging cloud platform 410 is provided with a monitoring cluster 411, and the monitoring cluster 411 includes the monitoring data hierarchical management device 300 in the above embodiments for hierarchically managing the charging monitoring data sent by the charging device 420.

[0142] An embodiment of the present application further provides a computer-readable storage medium for storing and executing as Figures 1 to 2A computer program for any one of the monitoring data hierarchical management methods based on a charging cloud platform. For example, computer program instructions, when executed by a computer, can call or provide the method or technical solution according to the present application through the operation of the computer. The program instructions for calling the method of the present application may be stored in a fixed or removable storage medium, or transmitted through a data stream in a broadcast or other signal-bearing medium or stored in a storage medium operating according to the program instructions.

[0143] In addition, an embodiment of the present application also provides an electronic device. In some embodiments, as Figure 5 shown, the electronic device 500 may include an input unit 510, a memory 520, a processor 530, and an output unit 540. The memory 520 stores program instructions that can run on the processor 530. The processor 530 can execute the method or technical solution based on the foregoing multiple embodiments by calling the program instructions. The electronic device 500 can be a mobile terminal device such as a mobile phone or a computer.

[0144] In summary, the monitoring data hierarchical management method, device, and equipment provided by the embodiments of the present application, on the one hand, manage the monitoring data in a finer dimension, adopt different processing methods for monitoring data at different levels, and avoid affecting the entire monitoring and reporting process due to the sudden increase of monitoring data in one dimension. On the other hand, the flow control threshold and the maximum threshold can be dynamically adjusted based on the load condition, and the processing capacity of the monitoring client can be maximally exerted.

[0145] Obviously, those skilled in the art should understand that the above-mentioned modules or steps of the present application can be implemented by a general-purpose computing device. They can be concentrated on a single computing device or distributed on a network composed of multiple computing devices. Optionally, they can be implemented by program code executable by the computing device, so that they can be stored in a storage device and executed by the computing device, or they can be separately fabricated into individual integrated circuit modules, or multiple modules or steps among them can be fabricated into a single integrated circuit module to implement. In this way, the present application is not limited to any specific combination of hardware and software.

[0146] Although the present application has been described in detail with general descriptions and specific embodiments above, based on the present application, some modifications or improvements can be made, which are obvious to those skilled in the art. Therefore, these modifications or improvements made without departing from the spirit of the present application all fall within the scope claimed by the present application.

Claims

1. A method for hierarchical management of monitoring data based on a charging cloud platform, characterized in that, it includes the following steps: Classify and divide the charging monitoring data of the charging cloud platform to generate dimension data, and set flow control thresholds for at least part of the dimension data. The dimension data includes one or a combination of charging start frequency monitoring data, charging order quantity monitoring data, charging source monitoring data, data cleaning rate monitoring data, and data reporting delay monitoring data; Real-time statistics of the TPS value of the dimension data, and judge whether a flow control threshold has been set for the current dimension data, If so, perform a flow control operation on the current dimension data based on the flow control threshold; If not, perform a fusing operation on the current dimension data based on the maximum threshold; The step of setting flow control thresholds for at least part of the dimension data further includes: According to the data importance, data change speed, and / or data stability of the dimension data, configure the flow control method of the dimension data. The flow control methods include degradation, flow limiting, and fusing; Based on the flow control method of the dimension data, set the flow control threshold corresponding to the flow control method; The flow control thresholds include: degradation threshold, flow limiting threshold, and fusing threshold; The flow control operations include: Degradation processing: used when the TPS value of the current dimension data exceeds the degradation threshold, give priority to reporting other dimension data, and then report the current dimension data; Flow limiting processing: used when the TPS value of the current dimension data exceeds the flow limiting threshold, report the data within the flow limiting threshold, and the data exceeding the flow limiting threshold is discarded; and, Fusing processing: used when the TPS value of the current dimension data exceeds the fusing threshold, directly stop reporting the current dimension data; The step of performing a flow control operation on the current dimension data based on the flow control threshold further includes: Judge whether the TPS value of the current dimension data exceeds the fusing threshold, If so, directly perform fusing processing on the current dimension data; If not, continue to judge whether the TPS value of the current dimension data exceeds the flow limiting threshold, If it is, perform flow limiting processing on the current dimension data; If not, continue to judge whether the TPS value of the current dimension data exceeds the degradation threshold, If so, perform degradation processing on the current dimension data; If not, perform normal reporting on the current dimension data.

2. The method for hierarchical management of monitoring data based on a charging cloud platform according to claim 1, characterized in that, The step of performing a fusing operation on the current dimension data based on the maximum threshold further includes: Judge whether the TPS value of the current dimension data exceeds the maximum threshold, If so, directly perform fusing processing on the current dimension data; If not, perform normal reporting on the current dimension data.

3. The method for hierarchical management of monitoring data based on a charging cloud platform according to claim 1, characterized in that, The flow limiting threshold is determined based on the daily average TPS and peak TPS of the dimension data within the set charging date, that is: Flow control threshold = (Daily average TPS + Peak TPS) / 2 × M, where 100% ≤ M ≤ 200%.

4. The monitoring data hierarchical management method based on a charging cloud platform according to claim 1, characterized in that, the fusing threshold and the maximum threshold are determined based on the memory resources of the charging cloud platform server, the size of the dimensional data, and the data processing time.

5. A monitoring data hierarchical management device based on a charging cloud platform, characterized in that, the device includes: A data partitioning module, configured to classify and partition the charging monitoring data of the charging cloud platform to generate dimensional data, and set a flow control threshold for at least part of the dimensional data, where the dimensional data includes one or a combination of charging start frequency monitoring data, charging order quantity monitoring data, charging source monitoring data, data cleaning rate monitoring data, and data reporting delay monitoring data; A judgment module, configured to statistically calculate the TPS value of the dimensional data in real time and judge whether a flow control threshold has been set for the current dimensional data, A flow control module, configured to, when it is judged that a flow control threshold has been set for the current dimensional data, perform a flow control operation on the current dimensional data based on the flow control threshold; A fusing module, configured to, when it is judged that no flow control threshold has been set for the current dimensional data, perform a fusing operation on the current dimensional data based on the maximum threshold; The step of setting a flow control threshold for at least part of the dimensional data specifically includes: configuring the flow control method of the dimensional data according to the data importance, data change speed, and / or data smoothness of the dimensional data, where the flow control method includes degradation, flow limiting, and fusing; based on the flow control method of the dimensional data, setting a flow control threshold corresponding to the flow control method; The flow control threshold includes a degradation threshold, a flow control threshold, and a fusing threshold; The flow control operation includes: Degradation processing: used for when the TPS value of the current dimensional data exceeds the degradation threshold, giving priority to reporting other dimensional data and then reporting the current dimensional data; Flow limiting processing: used for when the TPS value of the current dimensional data exceeds the flow control threshold, reporting the data within the flow control threshold, and discarding the data exceeding the flow control threshold; and, Fusing processing: used for when the TPS value of the current dimensional data exceeds the fusing threshold, directly stopping the reporting of the current dimensional data; The step of the flow control module performing a flow control operation on the current dimensional data based on the flow control threshold specifically includes: Judging whether the TPS value of the current dimensional data exceeds the fusing threshold, if so, directly performing fusing processing on the current dimensional data; if not, continuing to judge whether the TPS value of the current dimensional data exceeds the flow control threshold, if so, performing flow limiting processing on the current dimensional data; if not, continuing to judge whether the TPS value of the current dimensional data exceeds the degradation threshold, if so, performing degradation processing on the current dimensional data; if not, normally reporting the current dimensional data.

6. A monitoring data hierarchical management system based on a charging cloud platform, characterized in that, the system includes a charging cloud platform and at least one charging device: The charging device is installed with a monitoring client for collecting and sending charging monitoring data to the charging cloud platform; The charging cloud platform is provided with a monitoring cluster, and the monitoring cluster includes the monitoring data hierarchical management device based on the charging cloud platform as claimed in claim 5 for hierarchically managing the charging monitoring data sent by the charging device.

7. A computer-readable storage medium, characterized in that, a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the monitoring data hierarchical management method based on the charging cloud platform as claimed in any one of claims 1 to 4 is implemented.

8. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, when the processor executes the computer program, the monitoring data hierarchical management method based on the charging cloud platform as claimed in any one of claims 1 to 4 is implemented.

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