Edge calculation method, system and equipment based on blocked memory queue and medium

Abstract

The invention provides an edge calculation method, system and device based on a blocked memory queue and a medium, and the method comprises the steps: writing a protocol conversion program and a device control program according to an analysis result of an access device, converting device data into physical model standard structure data through the protocol conversion program, converting the object model standard structure data into equipment control data through an equipment control program; building an acquisition data blocking type memory queue to store object model standard structure data based on the equipment type, building a data consumption thread, extracting the object model standard structure data, and carrying out edge calculation; constructing a device control blocking type memory queue based on the device type to store device control data, extracting the device control data, transmitting a related instruction to a response device, and receiving a device control result; and reporting the edge calculation result and the equipment control result to the Internet of Things platform. According to the method, the blocking type memory queue is adopted, so that subsequent data processing has high performance and low latency.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to an edge computing method, system, device and medium based on a blocking memory queue. Background Art

[0002] Terminal smart devices are connected to the IoT platform through edge servers. In order to reduce the computing pressure of the IoT platform, edge computing is generally performed on the device data collected in the edge server, and the computing results are reported to the IoT platform. On the edge side, the collected data of the device is pre-processed and then cached. At present, centralized caching is generally used in edge servers, and special cache servers are introduced. Data is stored in special server nodes. However, centralized caching has stability problems. That is, when a problem occurs in the cache server, edge computing will not be able to proceed. In addition, additional servers are required, which will undoubtedly increase costs. Therefore, improvements need to be made to this problem. Summary of the invention

[0003] In view of the deficiencies in the prior art, the present invention proposes an edge computing method, system, device and medium based on a blocking memory queue.

[0004] A first aspect of the present invention discloses an edge computing method based on a blocking memory queue, the method comprising:

[0005] S1: compile a protocol conversion program and a device control program according to the analysis results of the access device, convert the device data into the object model standard structure data through the protocol conversion program, and convert the object model standard structure data into the device control data through the device control program;

[0006] S2: Based on the device type, a blocking memory queue for data collection is built to store the standard structure data of the object model, a data consumption thread is built, the standard structure data of the object model is extracted and edge computing is performed;

[0007] S3: construct a device control blocking memory queue based on the device type to store the device control data, extract the device control data and transmit the relevant instructions to the responding device, and receive the device control result;

[0008] S4: Report the edge computing results and device control results to the Internet of Things platform.

[0009] In an optional embodiment, the protocol conversion program and the device control program are written according to the analysis result of the access device, the device data is converted into the object model standard structure data through the protocol conversion program, and the object model standard structure data is converted into the device control data through the device control program, including:

[0010] S11: Analyze the access device and convert the access device into a physical model for feature extraction;

[0011] S12: defining the object model according to the characteristics of the object model, wherein the object model includes attributes, events, and services;

[0012] S13: Writing a protocol conversion program according to the device protocol and device data collection frequency of the access device, for converting the device data into object model standard structure data;

[0013] S14: Writing a device control program according to the physical model and device protocol of the access device, so as to convert the physical model structure data into device control data.

[0014] In an optional embodiment, the device type-based data collection blocking memory queue is constructed to store the object model standard structure data, a data consumption thread is constructed, the object model standard structure data is extracted and edge computing is performed, including:

[0015] S21: constructing a data acquisition blocking memory queue according to the device type of the access device, and storing the object model standard data structure into the corresponding data acquisition blocking memory queue;

[0016] S22: construct a data consumption thread, and obtain the object model standard structure data from the corresponding acquisition blocking memory queue according to the two dimensions of time and quantity;

[0017] S23: Use the standard structure data of the physical model obtained in S22 as source data for edge computing to perform edge computing.

[0018] In an optional embodiment, in S23, the edge computing includes rule computing, automatic alarm computing, scene linkage computing and persistent computing.

[0019] In an optional embodiment, the device control blocking memory queue is constructed based on the device type to store the device control data, the device control data is extracted and the related instructions are transmitted to the responding device, and the device control result is received, including:

[0020] S31: constructing a device control blocking memory queue according to the device type of the access device, and storing the device control data in the corresponding device control blocking memory queue;

[0021] S32: acquiring device control data from the corresponding device control blocking memory queue according to two dimensions of time and quantity;

[0022] S33: sending the device control data to the responding device, and the responding device receives the device control data and performs corresponding service actions;

[0023] S34: After the responding device performs a corresponding service behavior, it sends a device control result to the receiving device.

[0024] In an optional embodiment, the device control data includes control instructions and control parameters.

[0025] A second aspect of the present invention discloses an edge computing system based on a blocking memory queue, the system comprising:

[0026] A data conversion module, used to write a protocol conversion program and a device control program according to the analysis results of the access device, convert the device data into object model standard structure data through the protocol conversion program, and convert the object model standard structure data into device control data through the device control program;

[0027] The edge computing module is used to build a blocking memory queue for collecting data based on the device type to store the standard structure data of the object model, build a data consumption thread, extract the standard structure data of the object model and perform edge computing;

[0028] The device control module is used to build a device control blocking memory queue based on the device type to store the device control data, extract the device control data and transmit the relevant instructions to the responding device, and receive the device control result;

[0029] The Internet of Things module is used to receive the edge computing results of the edge computing module and the device control results of the device control module.

[0030] A third aspect of the present invention discloses an edge computing device based on a blocking memory queue, comprising:

[0031] at least one processor, and

[0032] a memory communicatively connected to the at least one processor; wherein,

[0033] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the edge computing method based on blocking memory queue as described in any one of the first aspects of the present invention.

[0034] The fourth aspect of the present invention discloses a computer-readable storage medium, which stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute an edge computing method based on a blocking memory queue as described in any one of the first aspect of the present invention.

[0035] Compared with the prior art, the present invention has the following advantages:

[0036] In the present invention, relevant data caches are all cached locally, that is, the device acquisition data and device control data are all stored in the server where the edge computing is located, which ensures the stability of data reading. A blocking memory queue for acquisition data and a blocking memory queue for device control are used to store and read relevant data in batches, respectively, so that subsequent data processing has high performance and low latency. In addition, memory queues are constructed based on device types, so that data of different device types are isolated from each other and do not affect each other; and the blocking memory queue for acquisition data and the blocking memory queue for device control are isolated from each other, and the acquisition and control of data related to the number of devices do not affect each other. Therefore, the edge computing server is reused in the solution of the present invention, and no new servers are required, which can greatly reduce costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0038] Figure 1 A flowchart of the edge computing method based on a blocking memory queue disclosed in the first aspect of the present invention;

[0039] Figure 2 A schematic diagram of an application process of the edge computing method based on a blocking memory queue disclosed in the first aspect of the present invention;

[0040] Figure 3 It is a structural diagram of an edge computing system based on a blocking memory queue disclosed in the second aspect of the present invention;

[0041] Figure 4 It is a structural schematic diagram of an edge computing device based on a blocking memory queue disclosed in the third aspect of the present invention;

[0042] Figure 5 It is a structural schematic diagram of a computer storage medium disclosed in the fourth aspect of the present invention. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is described and illustrated below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. Based on the embodiments provided in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application.

[0044] Obviously, the drawings described below are only some examples or embodiments of the present application. For ordinary technicians in this field, the present application can also be applied to other similar scenarios based on these drawings without creative work. In addition, it can also be understood that although the efforts made in this development process may be complicated and lengthy, for ordinary technicians in this field related to the content disclosed in this application, some changes in design, manufacturing or production based on the technical content disclosed in this application are just conventional technical means, and should not be understood as insufficient content disclosed in this application.

[0045] Reference to "embodiments" in this application means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those of ordinary skill in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0046] Unless otherwise defined, the technical terms or scientific terms involved in this application should be understood by people with ordinary skills in the technical field to which this application belongs. The words "one", "a", "a", "the" and the like involved in this application do not indicate a quantitative limitation, and may represent the singular or plural. The terms "include", "comprise", "have" and any of their variations involved in this application are intended to cover non-exclusive inclusions; for example, a process, method, system, product or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units that are not listed, or may also include other steps or units inherent to these processes, methods, products or devices. The words "connect", "connected", "coupled" and the like involved in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The "multiple" involved in this application refers to two or more. "And / or" describes the association relationship of associated objects, indicating that there may be three relationships, for example, "A and / or B" can represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the objects before and after are in an "or" relationship. The terms "first", "second", "third", etc. involved in this application are only used to distinguish similar objects and do not represent a specific ordering of the objects.

[0047] In the embodiments of the present invention, it is necessary to explain that:

[0048] Access devices: IoT devices that need to be accessed based on business needs. There are many types of IoT devices. If you want to achieve unified operation of devices, you must find out their commonalities and define standards based on the commonalities to make the platform compatible with more devices.

[0049] Physical model: Considering that a wide variety of IoT devices need to be connected to the IoT platform, it is necessary to describe the physical devices at the computer language level. In order for the system to recognize the device and be able to effectively manage the device, a virtualized entity existing in the computer is required, which is the physical model.

[0050] Example 1

[0051] See also Figure 1 and Figure 2 An embodiment of the present invention discloses an edge computing method based on a blocking memory queue, including: S1: writing a protocol conversion program and a device control program according to the analysis results of the access device, converting the device data into a physical model standard structure data through the protocol conversion program, and converting the physical model standard structure data into device control data through the device control program.

[0052] In an optional embodiment, the protocol conversion program and the device control program are written according to the analysis result of the access device, the device data is converted into the object model standard structure data through the protocol conversion program, and the object model standard structure data is converted into the device control data through the device control program, including:

[0053] S11: Analyze the access device and convert the access device into a physical model for feature extraction;

[0054] S12: defining the object model according to the characteristics of the object model, wherein the object model includes attributes, events, and services;

[0055] S13: Writing a protocol conversion program according to the device protocol and device data collection frequency of the access device, for converting the device data into object model standard structure data;

[0056] S14: Writing a device control program according to the physical model and device protocol of the access device, so as to convert the physical model structure data into device control data.

[0057] There are many types of terminal intelligent devices, such as access control, parking, cameras, water meters, electric meters, fire protection and other types of equipment. The communication protocols and data collection methods used by these different types of equipment are different. In order to unify the control of these devices and reduce the computing pressure of the Internet of Things platform, it is usually necessary to collect data from these devices in the edge server and perform edge computing, and then report the results to the Internet of Things platform. In this step, first analyze and abstract the physical models of various types of equipment, define the attributes, events and services in the physical model, and analyze the protocols of the devices to be connected, including communication methods and communication packet structures; so that the protocol conversion program can be written based on the device protocol and device data collection frequency of the access device, and the device data can be converted into the standard structure data of the physical model, and the device control service program can be written based on the physical model and device protocol of the access device, and the standard structure data of the physical model can be converted into device control data, which is convenient for the unified management and calculation of various data.

[0058] S2: Based on the device type, a blocking memory queue for data collection is constructed to store the standard structure data of the object model, and a data consumption thread is constructed to extract the standard structure data of the object model and perform edge computing.

[0059] In an optional embodiment, the device type-based data collection blocking memory queue is constructed to store the object model standard structure data, a data consumption thread is constructed, the object model standard structure data is extracted and edge computing is performed, including:

[0060] S21: constructing a data acquisition blocking memory queue according to the device type of the access device, and storing the object model standard data structure into the corresponding data acquisition blocking memory queue;

[0061] S22: construct a data consumption thread, and obtain the object model standard structure data from the corresponding acquisition blocking memory queue according to the two dimensions of time and quantity;

[0062] S23: Use the standard structure data of the physical model obtained in S22 as source data for edge computing to perform edge computing.

[0063] Among them, a blocking memory queue for collected data is constructed based on the device type, so that different types of devices have independent memory queues to store the standard structure data of the physical model after the collected data is converted, and the queues are isolated from each other to ensure that the collected data will not be cross-linked and prevent mutual interference between data. Then, the above data is extracted and used as source data for edge computing to facilitate the subsequent use of the edge computing results.

[0064] Specifically, in an optional embodiment, in S23, the edge computing includes rule computing, automatic alarm computing, scene linkage computing and persistence computing. The above computing results all correspond to the corresponding service input of the terminal device.

[0065] S3: Build a device control blocking memory queue based on the device type to store the device control data, extract the device control data and transmit the relevant instructions to the responding device, and receive the device control results.

[0066] In an optional embodiment, the device control blocking memory queue is constructed based on the device type to store the device control data, the device control data is extracted and the related instructions are transmitted to the responding device, and the device control result is received, including:

[0067] S31: constructing a device control blocking memory queue according to the device type of the access device, and storing the device control data in the corresponding device control blocking memory queue;

[0068] S32: acquiring device control data from the corresponding device control blocking memory queue according to two dimensions of time and quantity;

[0069] S33: sending the device control data to the responding device, and the responding device receives the device control data and performs corresponding service actions;

[0070] S34: After the responding device performs a corresponding service behavior, it sends a device control result to the receiving device.

[0071] Among them, a device control blocking memory queue is constructed based on the device type, so that different types of devices have independent memory queues to store device control data, and the queues are isolated from each other to ensure that different device control data will not be transmitted in parallel and prevent data from interfering with each other. Then, according to the two dimensions of time and quantity, the device control data is obtained from the corresponding device control blocking memory queue, so that the device control data can be issued to the corresponding device service and the device control result can be received.

[0072] Specifically, in an optional embodiment, the device control data includes control instructions and control parameters so that the corresponding service device can better respond to the service request.

[0073] S4: Report the edge computing results and device control results to the Internet of Things platform.

[0074] In the present invention, relevant data caches are all cached locally, that is, the device acquisition data and device control data are all stored in the server where the edge computing is located, which ensures the stability of data reading. A blocking memory queue for acquisition data and a blocking memory queue for device control are used to store and read related data in batches, respectively, so that subsequent data processing has high performance and low latency. In addition, memory queues are constructed based on device types, so that data of different device types are isolated from each other and do not affect each other; and the blocking memory queue for acquisition data and the blocking memory queue for device control are isolated from each other, and the acquisition and control of data related to the number of devices do not affect each other. Therefore, the edge computing server is reused in the solution of the present invention, and no new servers are required, which can greatly reduce costs.

[0075] Specifically, by constructing isolated blocking queues between different devices through device types, and by constructing isolated blocking queues between different data through data types, the stability and performance of edge computing are greatly improved. For example, when accessing devices such as access control, parking, cameras, water meters, electricity meters, and fire protection, the number of connected devices can reach more than 10,000, and each device queue will not accumulate, and the collection and device control delays are within 1s; and by reusing edge computing servers, project costs can be reduced. Compared with centralized caching, at least two servers can be saved, directly reducing costs by 10,000 to 20,000 yuan.

[0076] like Figure 3 As shown, the second aspect of the present invention discloses an edge computing system based on a blocking memory queue, the system comprising:

[0077] A data conversion module, used to write a protocol conversion program and a device control program according to the analysis results of the access device, convert the device data into object model standard structure data through the protocol conversion program, and convert the object model standard structure data into device control data through the device control program;

[0078] The edge computing module is used to build a blocking memory queue for collecting data based on the device type to store the standard structure data of the object model, build a data consumption thread, extract the standard structure data of the object model and perform edge computing;

[0079] The device control module is used to build a device control blocking memory queue based on the device type to store the device control data, extract the device control data and transmit the relevant instructions to the responding device, and receive the device control result;

[0080] The Internet of Things module is used to receive the edge computing results of the edge computing module and the device control results of the device control module.

[0081] This system is applied to an edge computing method based on a blocking memory queue disclosed in the first aspect.

[0082] See also Figure 4 The third aspect of the present invention discloses an edge computing device based on a blocking memory queue, comprising:

[0083] at least one processor, and

[0084] a memory communicatively connected to the at least one processor; wherein,

[0085] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the edge computing method based on blocking memory queue as described in any one of the first aspects of the present invention.

[0086] The computer device may be a terminal, and the computer device includes a processor, a memory, a network interface, a display screen, and an input device connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, an edge computing method based on a blocking memory queue is implemented. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covered on the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0087] See also Figure 5 The fourth aspect of the present invention discloses a computer-readable storage medium, which stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the edge computing method based on a blocking memory queue as described in any one of the first aspects of the present invention.

[0088] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing related hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it may include the processes of the embodiments of the edge computing method based on the blocking memory queue as described above. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct RAMbus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0089] Alternatively, if the above modules of the present invention are implemented in the form of software function modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the relevant technology. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, terminal, or network device, etc.) to execute all or part of the methods of each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, RAM, ROM, magnetic disks or optical disks.

[0090] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. An edge computing method based on a blocking memory queue, characterized in that: The method comprises: S1: compile a protocol conversion program and a device control program according to the analysis results of the access device, convert the device data into the object model standard structure data through the protocol conversion program, and convert the object model standard structure data into the device control data through the device control program; S2: Based on the device type, a blocking memory queue for data collection is built to store the standard structure data of the object model, and a data consumption thread is built to extract the standard structure data of the object model and perform edge computing; S3: construct a device control blocking memory queue based on the device type to store the device control data, extract the device control data and transmit the relevant instructions to the responding device, and receive the device control result; S4: Report the edge computing results and device control results to the Internet of Things platform.

2. The edge computing method based on blocking memory queue according to claim 1 is characterized in that: The method of writing a protocol conversion program and a device control program according to the analysis result of the access device, converting the device data into the object model standard structure data through the protocol conversion program, and converting the object model standard structure data into the device control data through the device control program includes: S11: Analyze the access device and convert the access device into a physical model for feature extraction; S12: defining the object model according to the characteristics of the object model, wherein the object model includes attributes, events, and services; S13: Writing a protocol conversion program according to the device protocol and device data collection frequency of the access device, for converting the device data into object model standard structure data; S14: Writing a device control program according to the physical model and device protocol of the access device, so as to convert the physical model structure data into device control data.

3. The edge computing method based on blocking memory queue according to claim 2 is characterized in that: The device type-based data collection blocking memory queue is constructed to store the object model standard structure data, a data consumption thread is constructed, the object model standard structure data is extracted and edge computing is performed, including: S21: constructing a data acquisition blocking memory queue according to the device type of the access device, and storing the object model standard data structure into the corresponding data acquisition blocking memory queue; S22: construct a data consumption thread, and obtain the object model standard structure data from the corresponding acquisition blocking memory queue according to the two dimensions of time and quantity; S23: Use the standard structure data of the physical model obtained in S22 as source data for edge computing to perform edge computing.

4. The edge computing method based on blocking memory queue according to claim 3 is characterized in that: In S23, the edge computing includes rule computing, automatic alarm computing, scene linkage computing and persistent computing.

5. The edge computing method based on blocking memory queue according to claim 4 is characterized in that: The device control blocking memory queue is constructed based on the device type to store the device control data, the device control data is extracted and the relevant instructions are transmitted to the responding device, and the device control result is received, including: S31: constructing a device control blocking memory queue according to the device type of the access device, and storing the device control data in the corresponding device control blocking memory queue; S32: acquiring device control data from the corresponding device control blocking memory queue according to two dimensions of time and quantity; S33: sending the device control data to the responding device, and the responding device receives the device control data and performs corresponding service actions; S34: After the responding device performs a corresponding service behavior, it sends a device control result to the receiving device.

6. The edge computing method based on blocking memory queue according to claim 5 is characterized in that: The device control data includes control instructions and control parameters.

7. An edge computing system based on a blocking memory queue, characterized in that: The system comprises: A data conversion module, used to write a protocol conversion program and a device control program according to the analysis results of the access device, convert the device data into object model standard structure data through the protocol conversion program, and convert the object model standard structure data into device control data through the device control program; The edge computing module is used to build a blocking memory queue for collecting data based on the device type to store the standard structure data of the object model, build a data consumption thread, extract the standard structure data of the object model and perform edge computing; The device control module is used to build a device control blocking memory queue based on the device type to store the device control data, extract the device control data and transmit the relevant instructions to the responding device, and receive the device control result; The Internet of Things module is used to receive the edge computing results of the edge computing module and the device control results of the device control module.

8. An edge computing device based on a blocking memory queue, characterized in that: include: at least one processor, and a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the edge computing method based on the blocking memory queue as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the edge computing method based on a blocking memory queue as described in any one of claims 1-6.

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