WO2021036465A1

WO2021036465A1 - Edge device processing method and apparatus, storage medium, and processor

Info

Publication number: WO2021036465A1
Application number: PCT/CN2020/098595
Authority: WO
Inventors: 施文彪
Original assignee: 北京国双科技有限公司
Priority date: 2019-08-30
Filing date: 2020-06-28
Publication date: 2021-03-04
Also published as: CN112445673A

Abstract

Disclosed in the present application are an edge device processing method and apparatus, a storage medium, and a processor. The method comprises: inputting collected sensor data of an edge device into a stream computing engine; performing window separation processing on the sensor data by means of the stream computing engine to obtain a plurality of sliding windows comprising data; calculating a slope value according to the data in each sliding window; and determining, on the basis of the calculated slope value, whether a running state of the edge device is in an abnormal state. By means of the present application, the problem in the related art that it is difficult to determine an abnormal running state of the edge device in a timely fashion is solved.

Description

Edge equipment processing method and device, storage medium and processor

This application claims the priority of a Chinese patent application filed with the Chinese Patent Office, the application number is 201910817943.6, and the title of the invention "Processing method and device of edge device, storage medium and processor" on August 30, 2019, the entire content of which is incorporated by reference Incorporated in this application.

Technical field

This application relates to the field of information processing technology, and in particular, to a processing method and device, storage medium, and processor of an edge device.

Background technique

Edge computing originated in the media field, which refers to the use of an open platform that integrates network, computing, storage, and application core capabilities on the side close to the source of things or data, and provides the nearest service nearby. Its applications are initiated at the edge, resulting in faster network service response and meeting the industry's basic needs in real-time business, application intelligence, security, and privacy protection. Edge computing is between physical entities and industrial connections, or at the top of physical entities. And cloud computing, you can still access the historical data of edge computing. Real-time analysis is an important application scenario for edge computing. For abnormal conditions of edge device operating status, there are often abnormal conditions that are difficult to determine the operating status of edge devices in time or failure to deal with abnormal conditions in time leads to subsequent unplanned shutdowns.

Regarding the problem that it is difficult to determine the abnormal situation of the edge device operating state in a related technology in a timely manner, no effective solution has yet been proposed.

Summary of the invention

The main purpose of this application is to provide an edge device processing method and device, storage medium, and processor, so as to solve the problem in the related art that it is difficult to determine the abnormal situation of the edge device operating state in time.

In order to achieve the foregoing objective, according to one aspect of the present application, an edge device processing method is provided. The method includes: inputting the collected sensor data of the edge device into a stream computing engine; performing window processing on the sensor data through the stream computing engine to obtain multiple sliding windows including data; according to the data in each sliding window The data calculates the slope value; based on the calculated slope value, it is determined whether the operating state of the edge device is in an abnormal state.

Further, calculating the slope value according to the data in each sliding window includes: obtaining each sliding window including the maximum and minimum values in the data; obtaining the window length of each sliding window; based on the window length of each sliding window, each The maximum and minimum values in the data of the two sliding windows calculate the slope value of each sliding window.

Further, determining whether the operating state of the edge device is in an abnormal state based on the calculated slope value includes: judging whether the calculated slope value of each sliding window is greater than a preset slope value; if there is a slope value of the sliding window greater than the The preset slope value determines that the operating state of the edge device is in an abnormal state.

Further, after determining whether the operating state of the edge device is in an abnormal state based on the calculated slope value, the method further includes: if it is determined that the operating state of the edge device is in an abnormal state, triggering a reminder message to remind target.

Further, performing windowing processing on the sensor data by the stream computing engine to obtain multiple sliding windows including data includes: determining a time interval for performing windowing processing on the sensor data; using the stream computing engine according to Window processing is performed on the sensor data at the time interval to obtain a plurality of sliding windows including the data.

Further, the sensor data includes at least one of the following: vibration characteristic value data and process quantity data.

In order to achieve the above objective, according to one aspect of the present application, there is provided an edge device processing apparatus, including: an input unit configured to input collected sensor data of the edge device into a stream computing engine; and an acquisition unit configured to pass through the The flow calculation engine performs window processing on the sensor data to obtain multiple sliding windows including data; the calculation unit is configured to calculate the slope value according to the data in each sliding window; the determination unit is configured to be based on the calculated slope The value determines whether the operating state of the edge device is in an abnormal state.

Further, the calculation unit further includes: a first acquisition module, configured to acquire the maximum and minimum values included in the data included in each sliding window; a second acquisition module, configured to acquire the window length of each sliding window; and a calculation module , Is set to calculate the slope value of each sliding window based on the window length of each sliding window, the maximum and minimum values in the data of each sliding window.

In order to achieve the foregoing objective, according to one aspect of the present application, a computer-readable storage medium is provided, wherein the storage medium includes a stored program, wherein the program executes any of the above-mentioned edge device Approach.

In order to achieve the foregoing objective, according to one aspect of the present application, an electronic device is provided, wherein the device includes at least one processor, and at least one memory and a bus connected to the processor; wherein the processor , The memory completes mutual communication through the bus; the processor is used to call program instructions in the memory to execute any one of the above-mentioned edge device processing methods.

Through this application, the following steps are adopted: input the collected sensor data of the edge device into the stream computing engine; perform window processing on the sensor data through the stream computing engine to obtain multiple sliding windows including data; according to the data in each sliding window The data calculates the slope value; based on the calculated slope value, it is determined whether the running state of the edge device is in an abnormal state, which solves the problem that it is difficult to determine the abnormal situation of the running state of the edge device in time in the related technology. Based on the slope value calculated from the data in the sliding window, it is determined whether the operating state of the edge device is in an abnormal state, thereby achieving the effect of improving the timeliness of determining the abnormality of the operating state of the edge device.

Description of the drawings

The drawings constituting a part of the application are used to provide a further understanding of the application, and the exemplary embodiments and descriptions of the application are used to explain the application, and do not constitute an improper limitation of the application. In the attached picture:

Fig. 1 is a flowchart of a processing method for an edge device according to an embodiment of the present application;

Fig. 2 is a schematic diagram of a sensor data input stream calculation engine provided according to an embodiment of the present application;

FIG. 3 is a schematic diagram of windowing processing of sensor data provided by an embodiment of the present application;

Fig. 4 is a schematic diagram of an edge device processing apparatus according to an embodiment of the present application; and

Fig. 5 is a block diagram of a device provided according to an embodiment of the present application.

detailed description

It should be noted that the embodiments in this application and the features in the embodiments can be combined with each other if there is no conflict. Hereinafter, the present application will be described in detail with reference to the drawings and in conjunction with the embodiments.

In order to enable those skilled in the art to better understand the solutions of the application, the technical solutions in the embodiments of the application will be clearly and completely described below in conjunction with the drawings in the embodiments of the application. Obviously, the described embodiments are only It is a part of the embodiments of this application, not all the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative work should fall within the protection scope of this application.

It should be noted that the terms "first" and "second" in the specification and claims of the application and the above-mentioned drawings are used to distinguish similar objects, and not necessarily used to describe a specific sequence or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances for the purposes of the embodiments of the present application described herein. In addition, the terms "including" and "having" and any variations of them are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those clearly listed. Those steps or units may include other steps or units that are not clearly listed or are inherent to these processes, methods, products, or equipment.

For ease of description, some terms or terms involved in the embodiments of this application are described below:

Stream computing, in the traditional data processing process, always collect data first, and then put the data in the DB. When people need to query data through DB, get answers or perform related processing. Although this seems very reasonable, the result is very compact, especially for some specific problems in some real-time search application environments. Offline processing similar to the MapReduce method cannot solve the problem well. This leads to a new data computing structure-stream computing. It can well analyze the large-scale flow of data in real-time during the changing movement process, capture potentially useful information, and send the result to the next computing node.

According to an embodiment of the present application, an edge device processing method is provided.

Fig. 1 is a flowchart of a processing method of an edge device according to an embodiment of the present application. As shown in Figure 1, the method includes the following steps:

Step S101: Input the collected sensor data of the edge device into the stream computing engine.

Optionally, in the edge device processing method provided in the embodiment of the present application, the aforementioned sensor data includes at least one of the following: vibration characteristic value data and process quantity data.

The process quantity data includes temperature data, pressure data, and humidity data. For example, when the sensor data is temperature data, the collected temperature data are: 2,5,9,8,8,3,4,2,2,5, 1,1,1,2,5,9. Input the collected temperature into the schematic diagram of the flow calculation engine, as shown in Figure 2.

Step S102: Perform window processing on the sensor data by the stream computing engine to obtain multiple sliding windows including data.

Optionally, in the edge device processing method provided in the embodiment of the present application, performing window processing on the sensor data by the stream computing engine to obtain multiple sliding windows including data includes: determining that the sensor data is The time interval for performing windowing processing; the stream computing engine performs windowing processing on the sensor data according to the time interval to obtain multiple sliding windows including data.

The above-mentioned time interval is the time length corresponding to the step length of each sliding of the window. For example, the time interval for windowing the sensor data is 1s, if the data collected in 1s is 2 and the sliding window contains 4 data, then the temperature data collected above is windowed as Shown in Figure 3. That is, the stream computing engine slides the sensor data into different sliding windows according to time intervals to obtain multiple sliding windows including data. For example, sliding window 1 includes data 2, 5, 9, 8; sliding window 2 includes data 9, 8, 8, 3; sliding window 3 includes data 8, 3, 4, 2; and so on.

Step S103: Calculate the slope value according to the data in each sliding window.

Optionally, in the edge device processing method provided in the embodiment of the present application, calculating the slope value according to the data in each sliding window includes: acquiring each sliding window including the maximum value and the minimum value in the data; acquiring each sliding window The window length of the window; the slope value of each sliding window is calculated based on the window length of each sliding window, the maximum value and the minimum value in the data of each sliding window.

For example, the maximum value of the data included in the sliding window 1 is 9, the minimum value is 2, and the window length is 4, and the calculated slope value=(9-2)/4=7/4.

Step S104: Determine whether the operating state of the edge device is in an abnormal state based on the calculated slope value.

For example, by judging whether the slope value calculated for each sliding window is greater than the preset slope value; if there is a slope value of the sliding window greater than the preset slope value, it is determined that the operating state of the edge device is in an abnormal state.

For example, the preset slope value is 2, and if the calculated slope value of the sliding window is greater than 2, it is determined that the operating state of the edge device is in an abnormal state.

When it is determined that the operating state of the edge device is in an abnormal state, a reminder message can be triggered to remind the target object. So that the target object can obtain the running status of the edge device in time, and deal with the edge device in time.

Through the above technical means, the slope analysis method using time sliding window combined with flow calculation can determine the abnormal situation of the edge device operating state in time, so as to avoid the failure to know the abnormal situation of the edge device operating state and lead to subsequent unplanned shutdowns.

In summary, the edge device processing method provided by the embodiments of the present application inputs the collected sensor data of the edge device into a stream computing engine; the stream computing engine performs window processing on the sensor data to obtain multiple data including data. Sliding window; calculate the slope value according to the data in each sliding window; determine whether the operating state of the edge device is in an abnormal state based on the calculated slope value, which solves the problem of the related technology that it is difficult to determine the abnormal situation of the edge device's operating state in time. Based on the slope value calculated from the data in the sliding window, it is determined whether the operating state of the edge device is in an abnormal state, thereby achieving the effect of improving the timeliness of determining the abnormality of the operating state of the edge device.

It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although the logical sequence is shown in the flowchart, in some cases, The steps shown or described can be performed in a different order than here.

The embodiment of the present application also provides a processing apparatus for an edge device. It should be noted that the processing apparatus for an edge device in an embodiment of the present application can be used to execute the processing method for an edge device provided in the embodiment of the present application. The following describes the processing apparatus of the edge device provided in the embodiment of the present application.

Fig. 4 is a schematic diagram of a processing apparatus of an edge device according to an embodiment of the present application. As shown in FIG. 4, the device includes: an input unit 201, an acquisition unit 202, a calculation unit 203, and a determination unit 204.

Specifically, the input unit 201 is configured to input the collected sensor data of the edge device into the stream computing engine;

The acquiring unit 202 is configured to perform window processing on the sensor data through the stream computing engine to obtain multiple sliding windows including data;

The calculation unit 203 is configured to calculate the slope value according to the data in each sliding window;

The determining unit 204 is configured to determine whether the operating state of the edge device is in an abnormal state based on the calculated slope value.

Optionally, in the processing apparatus of the edge device provided in the embodiment of the present application, the calculation unit 203 further includes: a first obtaining module configured to obtain the maximum value and the minimum value in the data included in each sliding window; and second The obtaining module is set to obtain the window length of each sliding window; the calculating module is set to calculate the slope value of each sliding window based on the window length of each sliding window and the maximum and minimum values in the data of each sliding window.

Optionally, in the processing apparatus of the edge device provided in the embodiment of the present application, the determining unit 204 includes: a determining module configured to determine whether the slope value calculated for each sliding window is greater than a preset slope value; The module is configured to determine that the operating state of the edge device is in an abnormal state when the slope value of the sliding window is greater than the preset slope value.

Optionally, in the apparatus for processing edge devices provided in the embodiment of the present application, the apparatus further includes: a reminding unit configured to determine whether the operating state of the edge device is in an abnormal state based on the calculated slope value, When it is determined that the operating state of the edge device is in an abnormal state, a reminder message is triggered to remind the target object.

Optionally, in the processing apparatus of the edge device provided in the embodiment of the present application, the acquiring unit 202 further includes: a second determining module configured to determine a time interval for performing windowing processing on the sensor data; and third acquiring The module is configured to perform window processing on the sensor data according to the time interval through the stream computing engine to obtain multiple sliding windows including data.

Optionally, in the processing apparatus for the edge device provided in the embodiment of the present application, the sensor data includes at least one of the following: vibration characteristic value data and process quantity data.

In the processing apparatus of the edge device provided by the embodiment of the present application, the collected sensor data of the edge device is input into the stream computing engine through the input unit 201; the acquisition unit 202 performs window processing on the sensor data through the stream computing engine to obtain A plurality of sliding windows including data; the calculation unit 203 calculates the slope value according to the data in each sliding window; the determination unit 204 determines whether the operating state of the edge device is in an abnormal state based on the calculated slope value, which solves the problem in the related art It is difficult to determine the abnormal situation of the edge device operating state in time. Based on the slope value calculated from the data in the sliding window, determine whether the operating state of the edge device is in an abnormal state, thereby improving the abnormal situation of determining the operating state of the edge device The effect of timeliness.

The processing device of the edge device includes a processor and a memory. The input unit 201, the acquisition unit 202, the calculation unit 203, and the determination unit 204 are all stored as program units in the memory, and the processor executes the above programs stored in the memory. Unit to realize the corresponding function.

The processor contains the kernel, and the kernel calls the corresponding program unit from the memory. The kernel can be set to one or more, by adjusting the kernel parameters to deal with edge devices.

The embodiment of the present invention provides a computer-readable storage medium on which a program is stored, and the program is executed by a processor to implement the processing method of the edge device.

The embodiment of the present invention provides a processor configured to run a program, wherein the processing method of the edge device is executed when the program is running.

An embodiment of the present invention provides an electronic device. As shown in FIG. 5, the device 70 includes at least one processor 701, and at least one memory 702 and a bus 703 connected to the processor; wherein the processor and the memory complete each other through the bus. Inter-communication; the processor is used to call the program instructions in the memory to execute the above-mentioned edge device processing method. The devices in this article can be servers, PCs, PADs, mobile phones, etc.

This application also provides a computer program product, which when executed on a data processing device, is suitable for executing a program that initializes the following method steps: inputting the collected sensor data of the edge device into the stream computing engine; using the stream computing The engine performs window processing on the sensor data to obtain multiple sliding windows including data; calculates a slope value based on the data in each sliding window; determines whether the operating state of the edge device is in an abnormal state based on the calculated slope value .

When executed on a data processing device, it is also suitable for executing a program that initializes the following method steps: calculating the slope value according to the data in each sliding window includes: obtaining each sliding window including the maximum and minimum values in the data; obtaining The window length of each sliding window; the slope value of each sliding window is calculated based on the window length of each sliding window, the maximum value and the minimum value in the data of each sliding window.

When executed on a data processing device, it is also suitable for executing a program that initializes the following method steps: determining whether the operating state of the edge device is in an abnormal state based on the calculated slope value includes: judging the slope calculated by each sliding window Whether the value is greater than the preset slope value; if the slope value of the sliding window is greater than the preset slope value, it is determined that the operating state of the edge device is in an abnormal state.

When executed on a data processing device, it is also suitable for executing a program that initializes the following method steps: after determining whether the operating state of the edge device is in an abnormal state based on the calculated slope value, the method further includes: if it is determined If the operating state of the edge device is in an abnormal state, a reminder message is triggered to remind the target object.

When executed on a data processing device, it is also suitable for executing a program that initializes the following method steps: windowing the sensor data through the stream computing engine to obtain multiple sliding windows including data includes: determining to The time interval during which the sensor data is subjected to windowing processing; the stream computing engine performs windowing processing on the sensor data according to the time interval to obtain a plurality of sliding windows including data.

When executed on a data processing device, it is also suitable for executing a program that initializes the following method steps: the sensor data includes at least one of the following: vibration characteristic value data and process quantity data.

This application is described with reference to flowcharts and/or block diagrams of methods, devices (systems), and computer program products according to embodiments of this application. It should be understood that each process and/or block in the flowchart and/or block diagram, and the combination of processes and/or blocks in the flowchart and/or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing equipment to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing equipment are generated It is a device that realizes the functions specified in one process or multiple processes in the flowchart and/or one block or multiple blocks in the block diagram.

In a typical configuration, the device includes one or more processors (CPUs), memory, and buses. The device may also include input/output interfaces, network interfaces, and so on.

The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and/or non-volatile memory, such as read-only memory (ROM) or flash memory (flash RAM), and the memory includes at least one Memory chip. The memory is an example of a computer-readable medium.

Computer-readable media include permanent and non-permanent, removable and non-removable media, and information storage can be realized by any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, CD-ROM, digital versatile disc (DVD) or other optical storage, Magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media can be used to store information that can be accessed by computing devices. According to the definition in this article, computer-readable media does not include transitory media, such as modulated data signals and carrier waves.

It should also be noted that the terms "include", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, product or device that includes a series of elements includes not only those elements, but also Other elements that are not explicitly listed, or they also include elements inherent to such processes, methods, commodities, or equipment. If there are no more restrictions, the element defined by the sentence "including a..." does not exclude the existence of other identical elements in the process, method, commodity or equipment that includes the element.

Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, this application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, this application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

The above are only examples of the application, and are not used to limit the application. For those skilled in the art, this application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of this application shall be included in the scope of the claims of this application.

Claims

A processing method for edge devices, including:

Input the collected sensor data of the edge device into the stream computing engine;

Performing window processing on the sensor data by the stream computing engine to obtain multiple sliding windows including data;

Calculate the slope value according to the data in each sliding window;

Based on the calculated slope value, it is determined whether the operating state of the edge device is in an abnormal state.
The method according to claim 1, wherein calculating the slope value according to the data in each sliding window comprises:

Get each sliding window including the maximum and minimum values in the data;

Get the window length of each sliding window;

The slope value of each sliding window is calculated based on the window length of each sliding window, the maximum value and the minimum value in the data of each sliding window.
The method according to claim 1, wherein determining whether the operating state of the edge device is in an abnormal state based on the calculated slope value comprises:

Determine whether the calculated slope value of each sliding window is greater than the preset slope value;

If the slope value of the sliding window is greater than the preset slope value, it is determined that the operating state of the edge device is in an abnormal state.
The method according to claim 1, wherein after determining whether the operating state of the edge device is in an abnormal state based on the calculated slope value, the method further comprises:

If it is determined that the operating state of the edge device is in an abnormal state, a reminder message is triggered to remind the target object.
The method according to claim 1, wherein performing window processing on the sensor data by the stream computing engine to obtain multiple sliding windows including data comprises:

Determine the time interval for windowing the sensor data;

The stream computing engine performs window processing on the sensor data according to the time interval to obtain multiple sliding windows including data.
The method according to claim 1, wherein the sensor data includes at least one of the following: vibration characteristic value data and process quantity data.
A processing device for edge equipment, including:

The input unit is set to input the collected sensor data of the edge device into the stream computing engine;

An obtaining unit, configured to perform window processing on the sensor data through the stream computing engine to obtain a plurality of sliding windows including data;

The calculation unit is set to calculate the slope value according to the data in each sliding window;

The determining unit is configured to determine whether the operating state of the edge device is in an abnormal state based on the calculated slope value.
The device according to claim 7, wherein the calculation unit further comprises:

The first obtaining module is configured to obtain the maximum value and the minimum value in the data included in each sliding window;

The second obtaining module is set to obtain the window length of each sliding window;

The calculation module is set to calculate the slope value of each sliding window based on the window length of each sliding window, the maximum value and the minimum value in the data of each sliding window.
A computer-readable storage medium, wherein the storage medium includes a stored program, wherein the program executes the edge device processing method according to any one of claims 1 to 6.
An electronic device, characterized in that the device includes at least one processor, and at least one memory and a bus connected to the processor;

Wherein, the processor and the memory complete mutual communication through the bus;

The processor is configured to call program instructions in the memory to execute the edge device processing method according to any one of claims 1 to 6.