Embedded device parallel reporting method and system based on data awareness and scheduling

Abstract

The invention relates to the technical field of Internet of Things communication, in particular to an embedded device parallel reporting method and system based on data perception and scheduling, and the method comprises the steps: carrying out the data collection, and obtaining an original collection data package; performing data sensing and marking on the original acquisition data packet to obtain a marked data packet; carrying out persistent storage on the marked data packet; carrying out parallel communication scheduling sending on the persistent storage data; obtaining application layer confirmation information, and releasing the storage space; a single serial data stream is decomposed into multiple strands of concurrent streams through a parallel processing mechanism, and the multi-link capability of hardware is fully utilized; through classification, grading and priority scheduling mechanisms, key data such as alarms can always enjoy the highest sending right, and low delay and high reliability of the key data are guaranteed; and through a configurable rule engine, the data processing behavior of the equipment can be remotely and dynamically adjusted.

Description

Technical Field

[0001] This application relates to the field of Internet of Things (IoT) communication technology, and in particular to a parallel reporting method and system for embedded devices based on data sensing and scheduling. Background Technology

[0002] In the current Internet of Things (IoT) ecosystem, massive numbers of embedded devices continuously collect data from the physical world. This data is the core fuel driving intelligent decision-making and applications. However, the underlying solutions supporting this data transmission generally treat embedded devices as single-function data acquisition and forwarding units, and their core data processing and transmission modes have significant limitations.

[0003] Existing IoT device data transmission solutions typically treat embedded devices as simple data pass-through units, resulting in a fundamental flaw in their data processing model:

[0004] Data is processed serially, which cannot take advantage of the potential of multi-link systems, resulting in low system throughput and significant latency in high-concurrency scenarios.

[0005] Indiscriminate transmission results in all data (regardless of whether it is needed) being sent to all relevant servers, causing a serious waste of network bandwidth and server computing resources;

[0006] Critical data and ordinary data are queued in the same queue, which cannot guarantee low-latency transmission of critical information;

[0007] Data flow logic is usually fixed in the device program, making it difficult to adapt to business changes and lacking flexibility, such as adding servers or adjusting data types. Summary of the Invention

[0008] To overcome the aforementioned problems in the existing technology, this application provides a parallel reporting method and system for embedded devices based on data awareness and scheduling, which adopts the following technical solution:

[0009] Firstly, this application provides a parallel reporting method for embedded devices based on data awareness and scheduling, including:

[0010] Data collection is performed to obtain the raw data packets.

[0011] The raw data packets are processed for data sensing and labeling to obtain labeled data packets;

[0012] The tagged data packets are persistently stored;

[0013] Parallel communication scheduling is used to send persistently stored data;

[0014] Obtain application-layer confirmation information and release storage space.

[0015] Furthermore, the process of data acquisition to obtain the original data packet specifically involves:

[0016] The readings of sensors such as water meters and electricity meters are collected through the RS485 interface to obtain the raw data frames.

[0017] The raw acquired data frames are encapsulated into an internally unified data packet format.

[0018] Furthermore, the specific steps of data perception and labeling of the original acquired data packets are as follows:

[0019] Input the data packet into FLASH for matching with a preset rule set;

[0020] FLASH uses an engine to parse data packets, matching the packet content against a preset set of rules to obtain the matching results;

[0021] Add a type identification tag to the data packet based on the matching results, and obtain the target address that the data packet needs to be reported;

[0022] The marked data packets are assigned priority, with alarm data being the highest and meter readings being the normal ones.

[0023] Furthermore, the step of parallel communication scheduling and transmission of persistent storage data includes:

[0024] Real-time monitoring of logical queues in extended storage; among all non-empty queues, priority queues are processed first according to their priority identifiers.

[0025] Activate multiple sending threads to concurrently retrieve data packets from multiple logical queues and send them;

[0026] Furthermore, the steps also include: a data packet transmission retry mechanism, specifically:

[0027] The sending thread starts a timer after sending a data packet;

[0028] Wait for the application layer to receive the ACK confirmation frame within the preset timeout period. If the application layer does not receive the ACK confirmation frame within the preset timeout period, the current data packet is reinserted into the head of the original logical queue and retransmitted after timeout while maintaining the original priority.

[0029] If the number of retries for the current data packet exceeds the maximum threshold, the data packet will be moved to the dead letter queue and an alarm will be generated to prevent the entire queue from being blocked due to the failure of a single data packet.

[0030] Furthermore, the use of asynchronous thread operation to continuously monitor the remote configuration channel specifically involves:

[0031] Continuously monitor rule update commands within the remote configuration channel;

[0032] Perform security checks on the instructions;

[0033] The received rule set data is temporarily stored in memory;

[0034] Send an atomic update signal to the dynamic rules engine;

[0035] After completing the processing of the current data packet, the dynamic rule engine atomically switches to a new rule set.

[0036] Secondly, this application also provides an embedded device parallel reporting system based on data awareness and scheduling, including:

[0037] Data acquisition module, identification and tagging module, persistent storage module, communication scheduling and sending module, storage space release module, asynchronous execution module;

[0038] Data acquisition module: Used to acquire data and obtain raw data packets;

[0039] Identification and tagging module: used to identify and tag the original acquired data packets to obtain tagged data packets;

[0040] Persistent storage module: Used to persistently store the tagged data packets;

[0041] Communication scheduling and sending module: used for communication scheduling and sending of persistent storage data;

[0042] Storage space release module: Used to obtain application layer confirmation information and release storage space;

[0043] Asynchronous execution module: Used to run in an asynchronous thread and continuously monitor the remote configuration channel.

[0044] In this embodiment of the application, the data acquisition module includes: a data acquisition unit and a data encapsulation unit;

[0045] Data acquisition unit: used to acquire readings from sensors such as water meters and electricity meters via an RS485 interface;

[0046] Data encapsulation unit: Used to encapsulate the original acquired data frames into an internally unified data packet format.

[0047] Furthermore, the communication scheduling and sending module includes: a logical queue monitoring module, a data packet sending module, and a retry module;

[0048] Logical queue monitoring module: used to monitor logical queues in extended storage in real time, and to process high-priority queues first according to their priority identifiers among all non-empty queues;

[0049] Data packet sending module: Used to activate multiple sending threads to concurrently retrieve data packets from multiple logical queues and send them.

[0050] Thirdly, this application provides an electronic device, comprising:

[0051] One or more processors; a memory; and one or more computer programs, wherein the one or more computer programs are stored in the memory, and the one or more computer programs include instructions that, when executed by the device, cause the device to perform the method as described in the first aspect.

[0052] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when run on a computer, causes the computer to perform the method described in the first aspect.

[0053] This application has the following beneficial effects:

[0054] This application provides a parallel reporting method for embedded devices based on data perception and scheduling, including: acquiring data to obtain raw acquisition data packets; performing data perception and marking on the raw acquisition data packets to obtain marked data packets; persistently storing the marked data packets; scheduling and sending the persistently stored data in parallel communication; obtaining application layer confirmation information and releasing storage space; decomposing a single serial data stream into multiple concurrent streams through a parallel processing mechanism to fully utilize the hardware's multi-link capabilities; ensuring that critical data such as alarms always have the highest transmission rights through a classification, hierarchical, and priority scheduling mechanism, guaranteeing their low latency and high reliability; and enabling remote dynamic adjustment of the device's data processing behavior through a configurable rule engine. Attached Figure Description

[0055] To more clearly illustrate the solutions in this application, the accompanying drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0056] Figure 1 This is an exemplary system architecture diagram to which embodiments of this application can be applied;

[0057] Figure 2 This is a flowchart of an embedded device parallel reporting method based on data awareness and scheduling, according to an embodiment of this application.

[0058] Figure 3 This is a schematic diagram of a parallel reporting method for embedded devices based on data awareness and scheduling, according to an embodiment of this application.

[0059] Figure 4 This is a flowchart illustrating the embedded device parallel reporting system based on data awareness and scheduling, according to an embodiment of this application.

[0060] Figure 5 This is a schematic diagram of the embedded device parallel reporting system architecture based on data awareness and scheduling, according to an embodiment of this application.

[0061] Figure 6 This is a schematic diagram of a computer device according to an embodiment of this application. Detailed Implementation

[0062] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein in the specification of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the terms "comprising" and "having," and any variations thereof, in the specification, claims, and foregoing drawings of this application, are intended to cover non-exclusive inclusion. The terms "first," "second," etc., in the specification, claims, or foregoing drawings of this application are used to distinguish different objects, not to describe a particular order.

[0063] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0064] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0065] like Figure 1 As shown, system architecture 100 may include terminal devices 101, 102, and 103, a network 104, and a server 105. Network 104 serves as the medium for providing communication links between terminal devices 101, 102, and 103 and server 105. Network 104 may include various connection types, such as wired or wireless communication links, or fiber optic cables, etc.

[0066] Users can use terminal devices 101, 102, and 103 to interact with server 105 via network 104 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 101, 102, and 103, such as web browser applications, shopping applications, search applications, instant messaging tools, email clients, social media platform software, etc.

[0067] Terminal devices 101, 102, and 103 can be various electronic devices with displays and support web browsing, including but not limited to smartphones, tablets, e-book readers, MP3 players (Moving Picture Experts Group Audio Layer III), MP4 players (Moving Picture Experts Group Audio Layer IV), laptops, and desktop computers, etc.

[0068] Server 105 can be a server that provides various services, such as a backend server that supports the pages displayed on terminal devices 101, 102, and 103.

[0069] It should be noted that the embedded device parallel reporting method based on data awareness and scheduling provided in this application embodiment is generally executed by a server / terminal device, and correspondingly, the embedded device parallel reporting system based on data awareness and scheduling is generally set in the server / terminal device.

[0070] It should be understood that Figure 1 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0071] Continue to refer to Figure 2 , 3 The figure shows a flowchart of a parallel reporting method for embedded devices based on data awareness and scheduling according to this application. The method includes the following steps:

[0072] 201. Perform data acquisition to obtain the raw data acquisition data packet;

[0073] Specifically, the readings of sensors such as water meters and electricity meters are collected through the RS485 interface to obtain the raw data frames.

[0074] The raw acquired data frames are encapsulated into an internally unified data packet format.

[0075] 202. Perform data sensing and marking on the original collected data packets to obtain the marked data packets;

[0076] In embodiment 202 of this application, the data sensing and marking of the original acquired data packets specifically refers to:

[0077] Input the data packet into FLASH for matching with a preset rule set;

[0078] FLASH uses an engine to parse data packets, matching the packet content against a preset set of rules to obtain the matching results;

[0079] Add a type identification tag to the data packet based on the matching results, and obtain the target address that the data packet needs to be reported;

[0080] It should be noted that alarm data needs to be sent to both the monitoring server and the log server simultaneously, so the alarm data corresponds to two target addresses. Meter readings, on the other hand, need to be sent to the billing server, so the meter readings correspond to one target address.

[0081] The marked data packets are assigned priority, with alarm data being the highest and meter readings being the normal ones.

[0082] In this embodiment of the application, the preset rule set is specifically: the preset rule set is stored in FLASH in the form of a configurable table structure, including data feature fields, data types, priorities, and a list of target server addresses.

[0083] In this embodiment of the application, data perception and labeling of the original collected data packets enable accurate data delivery from the source, sending data only to the servers that need it, thus solving the problem of resource waste caused by indiscriminate transmission.

[0084] 203. Persistently store the tagged data packets;

[0085] Specifically, based on the data packet type and the target server address, the data packets are stored in the corresponding logical queues of the extended storage.

[0086] It should be noted that the extended storage logical queue maintains multiple first-in-first-out queues, including: a high-priority alarm queue, a normal data queue A, and a normal data queue B; thereby decomposing a single data stream into multiple concurrent data sub-streams.

[0087] 204, Parallel communication scheduling and transmission of persistent storage data;

[0088] In this embodiment of the application, the specific steps for parallel communication scheduling and sending of persistent storage data are as follows:

[0089] Real-time monitoring of logical queues in extended storage; among all non-empty queues, priority queues are processed first according to their priority identifiers.

[0090] Activate multiple sending threads to concurrently retrieve data packets from multiple logical queues and send them;

[0091] It should be noted that each sending thread independently retrieves data packets from the allocated queue, encapsulates them into the corresponding communication protocol through the protocol adaptation unit, and sends the data report to the target server through the physical communication interface.

[0092] It should be noted that the physical communication interface includes: Ethernet interface, 4G communication interface and other extended communication interfaces.

[0093] Furthermore, the parallel communication scheduling and transmission of persistent storage data also includes: a data packet transmission retry mechanism, specifically:

[0094] The sending thread starts a timer after sending a data packet;

[0095] Wait for the application layer to receive the ACK confirmation frame within the preset timeout period. If the application layer does not receive the ACK confirmation frame within the preset timeout period, the current data packet is reinserted into the head of the original logical queue and retransmitted after timeout while maintaining the original priority.

[0096] If the number of retries for the current data packet exceeds the maximum threshold, the data packet will be moved to the dead letter queue and an alarm will be generated to prevent the entire queue from being blocked due to the failure of a single data packet.

[0097] 205, Obtain application layer confirmation information and release storage space;

[0098] Specifically, after the sending thread sends a data packet, it waits to receive an acknowledgment frame from the target address. Upon receiving an acknowledgment frame for a specific data packet, the thread marks the data packet as successfully sent from its queue and removes it.

[0099] In this embodiment of the application, the embedded device parallel reporting method based on data awareness and scheduling may further include:

[0100] 206. It runs using an asynchronous thread and continuously listens to the remote configuration channel;

[0101] Specifically, continuously listen for rule update commands within the remote configuration channel;

[0102] Perform security checks on the instructions;

[0103] The received rule set data is temporarily stored in memory;

[0104] Send an atomic update signal to the dynamic rules engine;

[0105] After completing the processing of the current data packet, the dynamic rule engine atomically switches to a new rule set.

[0106] It should be noted that the above asynchronous process can make the new data classification and routing strategies take effect immediately without restarting the device; this mechanism realizes remote dynamic adjustment of data flow logic, enabling the device to be upgraded from a "rigid terminal" to an "intelligent node", thus solving the problem of system rigidity.

[0107] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This computer program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. The aforementioned storage medium can be a non-volatile storage medium such as a magnetic disk, optical disk, or read-only memory (ROM), or random access memory (RAM).

[0108] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0109] Continue to refer to Figure 4 The embedded device parallel reporting system based on data awareness and scheduling described in this embodiment includes:

[0110] Data acquisition module, identification and tagging module, persistent storage module, communication scheduling and sending module, storage space release module, asynchronous execution module;

[0111] Data acquisition module: Used to acquire data and obtain raw data packets;

[0112] Identification and tagging module: used to identify and tag the original acquired data packets to obtain tagged data packets;

[0113] Persistent storage module: Used to persistently store the tagged data packets;

[0114] Communication scheduling and sending module: used for communication scheduling and sending of persistent storage data;

[0115] Storage space release module: Used to obtain application layer confirmation information and release storage space;

[0116] Asynchronous execution module: Used to run in an asynchronous thread and continuously monitor the remote configuration channel.

[0117] In this embodiment of the application, the data acquisition module includes: a data acquisition unit and a data encapsulation unit;

[0118] Data acquisition unit: used to acquire readings from sensors such as water meters and electricity meters via an RS485 interface;

[0119] Data encapsulation unit: Used to encapsulate the original acquired data frames into an internally unified data packet format.

[0120] In this embodiment, the identification marker module includes: a parsing and matching unit, a classification unit, and a priority identifier allocation unit;

[0121] Parsing and matching unit: Used to parse data packets using FLASH engine, match the data packet content with a preset rule set, and obtain the matching result;

[0122] Classification unit: Used to add type identification tags to data packets based on matching results and to obtain the target address that the data packet needs to be reported;

[0123] Priority Identifier Allocation Unit: Used to assign priority identifiers to marked data packets.

[0124] It should be noted that alarm data needs to be sent to both the monitoring server and the log server simultaneously, so the alarm data corresponds to two target addresses. Meter readings, on the other hand, need to be sent to the billing server, so the meter readings correspond to one target address.

[0125] In this embodiment of the application, the communication scheduling and sending module includes: a logical queue monitoring module, a data packet sending module, and a retry module;

[0126] Logical queue monitoring module: used to monitor logical queues in extended storage in real time, and to process high-priority queues first according to their priority identifiers among all non-empty queues;

[0127] Data packet sending module: Used to activate multiple sending threads to concurrently retrieve data packets from multiple logical queues and send them.

[0128] To address the aforementioned technical problems, embodiments of this application also provide a computer device. Please refer to [link / reference needed]. Figure 6 , Figure 6 This is a basic structural block diagram of the computer device in this embodiment.

[0129] The computer device 6 includes a memory 6a, a processor 6b, and a network interface 6c that are interconnected via a system bus. It should be noted that only the computer device 6 with components 6a-6c is shown in the figure; however, it should be understood that it is not required to implement all the shown components, and more or fewer components can be implemented alternatively. Those skilled in the art will understand that the computer device described here is a device capable of automatically performing numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes, but is not limited to, microprocessors, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0130] The computer device can be a desktop computer, laptop, handheld computer, or cloud server, etc. The computer device can interact with the user via a keyboard, mouse, remote control, touchpad, or voice control.

[0131] The memory 6a includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 6a may be an internal storage unit of the computer device 6, such as the hard disk or memory of the computer device 6. In other embodiments, the memory 6a may also be an external storage device of the computer device 6, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the computer device 6. Of course, the memory 6a may include both the internal storage unit and its external storage device of the computer device 6. In this embodiment, the memory 6a is typically used to store the operating system and various application software installed on the computer device 6, such as the program code of an embedded device parallel reporting method based on data perception and scheduling. In addition, the memory 6a can also be used to temporarily store various types of data that have been output or will be output.

[0132] In some embodiments, the processor 6b may be a central processing unit (CPU), controller, microcontroller, microprocessor, or other data processing chip. The processor 6b is typically used to control the overall operation of the computer device 6. In this embodiment, the processor 6b is used to run program code stored in the memory 6a or process data, for example, to run the program code of the data-aware and scheduling-based embedded device parallel reporting method.

[0133] The network interface 6c may include a wireless network interface or a wired network interface, which is typically used to establish communication connections between the computer device 6 and other electronic devices.

[0134] This application also provides another embodiment, namely, a non-volatile computer-readable storage medium storing a program of a data-aware and scheduling-based embedded device parallel reporting method, wherein the data-aware and scheduling-based embedded device parallel reporting method can be executed by at least one processor to perform the steps of the data-aware and scheduling-based embedded device parallel reporting method as described above.

[0135] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0136] Obviously, the embodiments described above are only some embodiments of this application, not all embodiments. The accompanying drawings show preferred embodiments of this application, but do not limit the patent scope of this application. This application can be implemented in many different forms; rather, the purpose of providing these embodiments is to provide a more thorough and comprehensive understanding of the disclosure of this application. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing specific embodiments, or make equivalent substitutions for some of the technical features. Any equivalent structures made using the content of this application's specification and drawings, directly or indirectly applied to other related technical fields, are similarly within the scope of patent protection of this application.

Claims

1. A data-aware and scheduling-based embedded device parallel reporting method, characterized by the steps of The application comprises the following steps: Data acquisition is performed to obtain original acquisition data packets; Data sensing and marking are performed on the original acquisition data packets to obtain marked data packets; The marked data packets are stored persistently; Parallel communication scheduling and sending are performed on the persistently stored data; Application layer confirmation information is obtained to release the storage space.

2. The data-aware and scheduling based parallel reporting method for embedded devices according to claim 1, wherein, The data acquisition is performed by the following steps: Reading information of sensors such as water meters and electric meters is acquired through an RS485 interface to obtain original acquisition data frames; The original acquisition data frames are encapsulated into an internal unified data packet format.

3. The data-aware and scheduling based parallel reporting method for embedded devices according to claim 2, wherein, The data sensing and marking on the original acquisition data packets are performed by the following steps: The data packets are input into a FLASH for preset rule set matching; The data packets are parsed by the FLASH engine, and the contents of the data packets are matched with the preset rule set to obtain a matching result; Type identification marks are added to the data packets according to the matching result, and target addresses to which the data packets need to be reported are obtained; Priority identification is allocated to the marked data packets, wherein alarm data has the highest priority and meter reading data is ordinary.

4. The data-aware and scheduling based parallel reporting method for embedded devices according to claim 1 or 3, characterized in that, The parallel communication scheduling and sending on the persistently stored data comprises the following steps: Logical queues in the extended storage are monitored in real time, and in all non-empty queues, high-priority queues are processed preferentially according to the priority identification; Multiple sending threads are activated to concurrently acquire data packets from multiple logical queues for sending.

5. The data-aware and scheduling based parallel reporting method for embedded devices according to claim 4, wherein, The steps further comprise a data packet sending retry mechanism, which is specifically as follows: A timer is started by the sending thread after the data packet is sent; An ACK confirmation frame of the application layer is waited for within a preset timeout period, and if the ACK confirmation frame of the application layer is not received within the preset timeout period, the current data packet is reinserted into the head of the original logical queue and is kept for timeout retransmission with the original priority; If the retry count of the current data packet exceeds a maximum threshold, the data packet is moved to a dead letter queue and an alarm is generated to prevent the entire queue from being blocked due to the sending failure of a single data packet.

6. The data-aware and scheduling based parallel reporting method for embedded devices according to claim 5, wherein, The asynchronous thread is run to continuously monitor the remote configuration channel, which is specifically as follows: The remote configuration channel is continuously monitored for rule update instructions; The instructions are subjected to security verification; The received rule set data are temporarily stored in the memory; An atomic update signal is sent to the dynamic rule engine; After the dynamic rule engine completes the processing of the current data packet, it atomically switches to the new rule set.

7. A data-aware and scheduling based embedded device parallel reporting system, characterized in that, The system comprises a data acquisition module, an identification and marking module, a persistent storage module, a communication scheduling and sending module, a storage space release module, and an asynchronous execution module. The data acquisition module is configured to perform data acquisition to obtain original acquisition data packets. The identification and marking module is configured to identify and mark the original acquisition data packets to obtain marked data packets. The persistent storage module is configured to store the marked data packets persistently. The communication scheduling and sending module is configured to perform communication scheduling and sending on the persistently stored data. The storage space release module is configured to obtain application layer confirmation information to release the storage space. The asynchronous execution module is configured to run the asynchronous thread to continuously monitor the remote configuration channel. In the embodiments of the application, the data acquisition module comprises a data acquisition unit and a data encapsulation unit. Data acquisition unit: for collecting the reading information of water meter, electric meter and other sensors through RS485 interface; Data encapsulation unit: for encapsulating the original collected data frame into internal unified data packet format.

8. The data-aware and scheduling based embedded device parallel reporting system of claim 7, wherein, The communication dispatching sending module comprises a logic queue monitoring module, a data packet sending module and a retry module; The logic queue monitoring module is used for monitoring the logic queues in the extended storage in real time, and in all non-empty queues, high-priority queues are processed in priority according to the priority identifier. The data packet sending module is used for activating multiple sending threads and concurrently obtaining data packets from multiple logic queues for sending.

9. An electronic device, comprising: Comprise: one or more processors; a memory; and one or more computer programs, wherein the one or more computer programs are stored in the memory, the one or more computer programs comprise instructions, when the instructions are executed by the device, make the device execute the steps of the parallel reporting method of the embedded device based on data perception and scheduling as claimed in any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, when it runs on the computer, makes the computer execute the steps of the parallel reporting method of the embedded device based on data perception and scheduling as claimed in any one of claims 1 to 6.

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