A source network load storage data aggregation processing method, system, device and medium

Abstract

The application discloses a source network load data aggregation processing method, system, device and medium, mainly relates to the technical field of aggregation processing, and is used to solve the problems that the existing scheme sharing bandwidth causes data transmission conflict and the bandwidth allocation lacks dynamic adjustment mechanism. Including: adjusting real-time bandwidth according to the priority of the special channel and the hop number of the corresponding edge computing node of the special channel in the data aggregation layer; the communication layer transmits device data to the data aggregation layer through an internet communication protocol; the data aggregation layer pushes device data to the real-time edge computing node in a streaming manner and stores the device data to an offline analysis platform according to preset processing logic, and uploads the processing result returned by the edge computing node to the application layer; the application layer issues operation instructions to the data aggregation layer, the data aggregation layer stores the operation instructions, and issues the operation instructions to the communication layer, and adjusts the bandwidth of the special channel again according to the pre-stored operation instructions and the bandwidth allocation strategy of the special channel of the communication layer.

Description

Technical Field

[0001] This application relates to the field of aggregation processing technology, and in particular to a method, system, device and medium for aggregation processing of source, network, load and storage data. Background Technology

[0002] Currently, data processing in source-grid-load-storage systems largely employs a traditional network architecture. Data generated by physical layer devices (such as distributed power sources, energy storage devices, and load terminals) is typically transmitted to the communication layer via shared network bandwidth, and then forwarded to the data aggregation layer. The data aggregation layer generally uses a centralized processing model, first storing all device data on a central server, then processing it in batches according to a preset order. After processing, the results are uploaded to the application layer, which generates operation instructions based on the results and feeds them back to the physical layer devices for execution. In this process, network bandwidth is not differentiated, and data from various devices (such as real-time monitoring data and historical statistics) share the same transmission channel. Furthermore, data processing largely relies on the computing power of the central node, while the role of edge computing nodes is limited to simple data collection and forwarding. The existing technology has the following drawbacks: First, shared bandwidth leads to data transmission conflicts, and data from devices with high real-time requirements (such as load control command feedback data) is easily interfered with by non-critical data, causing transmission delays; Second, bandwidth allocation lacks a dynamic adjustment mechanism and cannot be flexibly optimized according to actual working conditions such as device data priority and edge computing node hop count, resulting in low network resource utilization and affecting the stability and efficiency of the entire system. Summary of the Invention

[0003] This application provides a source-network-load-storage data aggregation processing method, system, device, and medium to solve the problems of data transmission conflicts caused by shared bandwidth and the lack of dynamic adjustment mechanism for bandwidth allocation in existing solutions.

[0004] Firstly, this application provides a method for source-network-load-storage data aggregation and processing, the method comprising: Divide the network bandwidth of the physical layer and communication layer into several dedicated channels; configure the type and priority of each dedicated channel; Based on the type of physical device in the physical layer, determine the dedicated channel corresponding to the physical device; Physical devices transmit device data to the communication layer through corresponding dedicated channels and device communication protocols; during the transmission process, the real-time bandwidth of the dedicated channel is dynamically adjusted according to the priority of the dedicated channel and the number of hops of the edge computing node corresponding to the dedicated channel in the data aggregation layer. The communication layer transmits device data to the data aggregation layer via Internet communication protocols; the data aggregation layer pushes the device data to the real-time edge computing node in a streaming manner and stores it in the offline analysis platform according to the preset processing logic, and uploads the processing results returned by the edge computing node to the application layer; The application layer sends operation instructions to the data aggregation layer, which stores the operation instructions and then sends them to the communication layer. Based on the operation instructions stored in the communication layer and the dedicated channel bandwidth allocation strategy, the dedicated channel bandwidth is adjusted again. At the same time, the operation instructions are sent to the physical layer. Each physical device in the physical layer executes operation commands.

[0005] In one implementation of this application, the network bandwidth of the physical layer and the communication layer is divided into several dedicated channels, specifically including: By employing IP small-granularity hard slicing technology, the network bandwidth of the physical layer and communication layer is divided into several dedicated channels.

[0006] In one implementation of this application, during transmission, the real-time bandwidth of the dedicated channel is dynamically adjusted based on the priority of the dedicated channel and the hop count of the edge computing node corresponding to the dedicated channel in the data aggregation layer. Specifically, this includes: Through the formula: Calculate the real-time bandwidth of the i-th dedicated channel. ; in, Indicates the total bandwidth. This represents the priority weight corresponding to the priority of the i-th dedicated channel; Indicates the attenuation coefficient. This represents the hop count of the corresponding edge computing node in the data aggregation layer, where N represents the total number of dedicated channels. This represents the priority weight corresponding to the priority of the j-th dedicated channel.

[0007] In one implementation of this application, the device data includes a device ID code, a collection time, and collected data; Before the data aggregation layer pushes device data to real-time edge computing nodes and stores it on the offline analysis platform in a streaming manner according to preset processing logic, the method also includes: The data aggregation layer aligns device data from several physical devices using a sliding time window interpolation algorithm based on the acquisition time of the device data.

[0008] In one implementation of this application, the communication layer transmits device data to the data aggregation layer via an Internet communication protocol, specifically including: By employing IP small-granularity hard slicing technology, the network bandwidth of the communication layer and data aggregation layer is divided into several dedicated channels, and a one-to-one correspondence is configured between the dedicated channels between the communication layer and the data aggregation layer and the dedicated channels between the physical layer and the communication layer.

[0009] Secondly, this application provides a source-network-load-storage data aggregation and processing system, the system comprising: The channel configuration module is used to divide the network bandwidth of the physical layer and the communication layer into several dedicated channels; configure the type and priority of each dedicated channel; and determine the dedicated channel corresponding to the physical device based on the type of physical device in the physical layer. The physical layer is used to transmit device data of physical devices to the communication layer through corresponding dedicated channels and device communication protocols. During the transmission process, the real-time bandwidth of the dedicated channel is dynamically adjusted according to the priority of the dedicated channel and the number of hops of the edge computing node corresponding to the dedicated channel in the data aggregation layer. The communication layer is used to transmit device data to the data aggregation layer via Internet communication protocols. The data aggregation layer is used to push device data to real-time edge computing nodes in a streaming manner and store it in an offline analysis platform according to preset processing logic, and upload the processing results returned by the edge computing nodes to the application layer. The application layer is used to send operation instructions to the data aggregation layer. The data aggregation layer stores the operation instructions and then sends them to the communication layer. The communication layer is also used to pre-store operation instructions and dedicated channel bandwidth allocation strategies, and to readjust the dedicated channel bandwidth; at the same time, it sends the operation instructions to the physical layer; and each physical device in the physical layer executes the operation instructions.

[0010] In one implementation of this application, the channel configuration module includes a channel configuration unit. This is used to divide the network bandwidth of the physical layer and communication layer into several dedicated channels using IP small-granularity hard slicing technology.

[0011] In one implementation of this application, the physical layer includes an adjustment unit. Used in the formula: Calculate the real-time bandwidth of the i-th dedicated channel. ; in, Indicates the total bandwidth. This represents the priority weight corresponding to the priority of the i-th dedicated channel; Indicates the attenuation coefficient. This represents the hop count of the corresponding edge computing node in the data aggregation layer, where N represents the total number of dedicated channels. This represents the priority weight corresponding to the priority of the j-th dedicated channel.

[0012] Thirdly, this application provides a source-network-load-storage data aggregation and processing device, the device comprising: processor; And a memory that stores executable code, which, when executed, causes the processor to perform a source-network-load-storage data aggregation processing method as described above.

[0013] Fourthly, this application provides a non-volatile computer storage medium storing computer instructions thereon, which, when executed, implement a source-network-load-storage data aggregation processing method as described above.

[0014] As can be seen from the above technical solutions, this application has the following advantages: By dividing network bandwidth into several dedicated channels and configuring each channel with independent types and priorities, physical isolation of critical device data transmission is achieved. Data with high real-time requirements, such as load control commands, can exclusively occupy high-priority channels, eliminating transmission conflicts with non-critical data and physically ensuring low-latency command feedback data. Simultaneously, the fixed allocation mechanism of dedicated channels avoids resource contention under traditional shared bandwidth, enabling physical devices to stably transmit data through pre-matched channels, thus improving the determinism and reliability of data transmission.

[0015] A dynamic bandwidth adjustment mechanism based on dedicated channel priority and edge computing node hop count enables real-time optimization of network resources according to actual operating conditions. When the volume of high-priority data surges or the hop count of edge nodes increases, the system automatically increases the bandwidth allocation of the corresponding channel to ensure the transmission efficiency of critical data. The linkage between the issuance of operation commands and the bandwidth strategy forms a closed-loop control, ensuring that bandwidth allocation always aligns with the equipment's operating status. This dynamic adaptability not only improves bandwidth utilization but also enhances the system's adaptability to complex operating conditions through the coordinated response of the communication layer, data aggregation layer, and application layer, thereby improving the overall operational stability of the source-network-load-storage system. Attached Figure Description

[0016] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the description will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a flowchart of a source-grid-load-storage data aggregation and processing method provided in an embodiment of this application.

[0018] Figure 2This is a schematic diagram of the internal structure of a source-grid-load-storage data aggregation and processing system provided in an embodiment of this application.

[0019] Figure 3 This is a schematic diagram of the internal structure of a source-grid-load-storage data aggregation and processing device provided in an embodiment of this application. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] Those skilled in the art should understand that the embodiments described below are merely preferred embodiments of this disclosure and do not imply that this disclosure can only be implemented through these preferred embodiments. These preferred embodiments are merely used to explain the technical principles of this disclosure and are not intended to limit the scope of protection of this disclosure. All other embodiments obtained by those skilled in the art based on the preferred embodiments provided in this disclosure without inventive effort should still fall within the scope of protection of this disclosure.

[0022] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0023] The technical solutions proposed in the embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0024] The embodiment provides a method for aggregating and processing source, network, load, and storage data, such as... Figure 1 As shown in the embodiments of this application, the method mainly includes the following steps: Step 110: Divide the network bandwidth of the physical layer and communication layer into several dedicated channels; configure the type and priority of each dedicated channel; determine the dedicated channel corresponding to the physical device based on the type of physical device in the physical layer.

[0025] In some embodiments, the network bandwidth of the physical layer and the communication layer is divided into several dedicated channels, specifically including: By employing IP small-granularity hard slicing technology, the network bandwidth of the physical layer and communication layer is divided into several dedicated channels.

[0026] Based on the above description, the dedicated channel configuration involved in this step can clearly distinguish different types and priorities of network traffic, ensuring that high-priority services (such as real-time communication or critical data transmission) receive stable bandwidth resources and avoiding latency or packet loss issues caused by network congestion. Secondly, the direct binding of physical layer device types to dedicated channels simplifies network management processes and reduces the configuration complexity caused by dynamic resource allocation, making it particularly suitable for heterogeneous network environments with multiple devices. Furthermore, hard slicing technology reduces the risk of interference between different service flows by physically isolating channels, improving the overall network reliability and predictability. This partitioning method does not introduce additional performance overhead but optimizes existing hardware resources; therefore, it does not require specific device upgrades in actual deployments and has strong compatibility.

[0027] Step 120: The physical device transmits device data to the communication layer through the corresponding dedicated channel and device communication protocol; during the transmission process, the real-time bandwidth of the dedicated channel is dynamically adjusted according to the priority of the dedicated channel and the number of hops of the edge computing node corresponding to the dedicated channel in the data aggregation layer.

[0028] During transmission, the real-time bandwidth of the dedicated channel is dynamically adjusted based on its priority and the hop count of the corresponding edge computing node in the data aggregation layer. Specifically, this includes: Through the formula: Calculate the real-time bandwidth of the i-th dedicated channel. ; in, Indicates the total bandwidth. This represents the priority weight corresponding to the priority of the i-th dedicated channel; Indicates the attenuation coefficient. This represents the hop count of the corresponding edge computing node in the data aggregation layer, where N represents the total number of dedicated channels. This represents the priority weight corresponding to the priority of the j-th dedicated channel.

[0029] Based on the above description, this step employs a dynamic bandwidth allocation mechanism based on priority and hop count. This ensures that high-priority services (such as real-time control or critical monitoring data) receive more sufficient bandwidth resources according to their weights, thereby reducing transmission latency and improving the timeliness of critical data. Secondly, by introducing attenuation coefficients and hop count calculations, the system can automatically adapt to changes in network topology, such as the hierarchical expansion of edge computing nodes or fluctuations in link status, avoiding resource waste or congestion caused by fixed bandwidth allocation. Furthermore, the formulaic bandwidth adjustment method provides quantifiable configuration guidelines for network management, simplifying the need for manual intervention, and is particularly suitable for complex scenarios involving multiple edge nodes collaborating. This dynamic adjustment mechanism does not rely on adding new hardware or modifying protocols; instead, it achieves performance improvements by optimizing existing bandwidth allocation logic. Therefore, it has strong compatibility with existing network architectures and does not introduce additional communication overhead.

[0030] Step 130: The communication layer transmits device data to the data aggregation layer via the Internet communication protocol; the data aggregation layer pushes the device data to the real-time edge computing node in a streaming manner and stores it in the offline analysis platform according to the preset processing logic, and uploads the processing results returned by the edge computing node to the application layer.

[0031] The communication layer transmits device data to the data aggregation layer via Internet communication protocols, specifically including: By employing IP small-granularity hard slicing technology, the network bandwidth of the communication layer and data aggregation layer is divided into several dedicated channels, and a one-to-one correspondence is configured between the dedicated channels between the communication layer and the data aggregation layer and the dedicated channels between the physical layer and the communication layer.

[0032] It should be noted that the device data includes the device ID code, collection time, and collected data; Before the data aggregation layer pushes device data to real-time edge computing nodes and stores it on the offline analysis platform in a streaming manner according to preset processing logic, the method also includes: The data aggregation layer aligns device data from several physical devices using a sliding time window interpolation algorithm based on the acquisition time of the device data.

[0033] Based on the above description, the correspondence of the dedicated channel in this step ensures that the transmission path of physical layer device data is completely consistent with the path from the communication layer to the data aggregation layer, avoiding rerouting or protocol conversion of data streams during cross-layer transmission, thereby reducing transmission latency and packet loss risks. Secondly, the streaming push to real-time edge computing nodes enables rapid processing and feedback of device data, making it particularly suitable for applications with high real-time requirements (such as industrial control or intelligent monitoring). Simultaneously, the offline storage mechanism provides a complete historical record for subsequent data analysis. Furthermore, the hard isolation of the dedicated channel avoids bandwidth contention between different service streams, ensuring the stability of critical data transmission. The pre-defined layered processing logic (real-time computing and offline storage) further simplifies the system architecture and reduces the complexity of dynamic decision-making. This design does not introduce new communication protocols or hardware modifications, but rather improves overall efficiency by optimizing existing bandwidth resources and data processing flows. Therefore, it has strong compatibility with existing networks and does not introduce additional management overhead.

[0034] Step 140: The application layer sends the operation instructions to the data aggregation layer. The data aggregation layer stores the operation instructions and sends them to the communication layer. Based on the operation instructions pre-stored in the communication layer and the dedicated channel bandwidth allocation strategy, the dedicated channel bandwidth is adjusted again. At the same time, the operation instructions are sent to the physical layer. Each physical device in the physical layer executes the operation instructions.

[0035] Based on the above description, this step involves the hierarchical storage and forwarding of operation instructions at the application layer, data aggregation layer, and communication layer, ensuring the integrity and traceability of instruction transmission. Simultaneously, the linkage between pre-stored instructions and the dedicated channel bandwidth allocation strategy allows network resources to be adjusted secondary according to actual needs, such as automatically increasing the bandwidth priority of the instruction transmission channel during periods of intensive device operation. Secondly, physical layer devices directly execute operation instructions from the data aggregation layer, avoiding the latency or protocol conversion overhead that may be introduced by traditional multi-layer forwarding, making it particularly suitable for scenarios requiring rapid response (such as remote control or parameter adjustment). Furthermore, the dedicated channel bandwidth readjustment mechanism works in conjunction with physical device operations; for example, when critical devices execute high-priority instructions, the system can automatically allocate more bandwidth resources to them, thereby reducing the risk of instruction transmission interruption or timeout. This design does not rely on complex algorithms or new hardware, but rather improves system flexibility by optimizing the correlation between existing instruction flows and bandwidth management. Therefore, it requires minimal modification to the existing architecture and does not introduce additional communication load.

[0036] As described above, this embodiment achieves physically isolated transmission of critical device data by dividing network bandwidth into several dedicated channels and configuring each channel with independent types and priorities. Data with high real-time requirements, such as load control commands, can exclusively occupy high-priority channels, eliminating transmission conflicts with non-critical data and physically ensuring low-latency characteristics of command feedback data. Simultaneously, the fixed allocation mechanism of dedicated channels avoids resource contention under traditional shared bandwidth, enabling physical devices to stably transmit data through pre-matched channels, thus improving the determinism and reliability of data transmission.

[0037] A dynamic bandwidth adjustment mechanism based on dedicated channel priority and edge computing node hop count enables real-time optimization of network resources according to actual operating conditions. When the volume of high-priority data surges or the hop count of edge nodes increases, the system automatically increases the bandwidth allocation of the corresponding channel to ensure the transmission efficiency of critical data. The linkage between the issuance of operation commands and the bandwidth strategy forms a closed-loop control, ensuring that bandwidth allocation always aligns with the equipment's operating status. This dynamic adaptability not only improves bandwidth utilization but also enhances the system's adaptability to complex operating conditions through the coordinated response of the communication layer, data aggregation layer, and application layer, thereby improving the overall operational stability of the source-network-load-storage system.

[0038] In addition, this application Figure 2 This application provides a source-grid-load-storage data aggregation and processing system as an embodiment. For example... Figure 2 As shown in the embodiments of this application, the system mainly includes: The channel configuration module 210 is used to divide the network bandwidth of the physical layer 220 and the communication layer 230 into several dedicated channels; configure the type and priority of each dedicated channel; and determine the dedicated channel corresponding to the physical device based on the type of the physical device in the physical layer 220.

[0039] The channel configuration module 210 includes a channel configuration unit. This is used to divide the network bandwidth of the physical layer 220 and the communication layer 230 into several dedicated channels using IP small-granularity hard slicing technology.

[0040] The physical layer 220 is used to transmit physical device data to the communication layer 230 through the corresponding dedicated channel and device communication protocol. During the transmission process, the real-time bandwidth of the dedicated channel is dynamically adjusted according to the priority of the dedicated channel and the number of hops of the edge computing node corresponding to the dedicated channel in the data aggregation layer 240.

[0041] Physical layer 220 includes adjustment units. Used in the formula: Calculate the real-time bandwidth of the i-th dedicated channel. ; in, Indicates the total bandwidth. This represents the priority weight corresponding to the priority of the i-th dedicated channel; Indicates the attenuation coefficient. This represents the hop count of the corresponding edge computing node in data aggregation layer 240, where N represents the total number of dedicated channels. This represents the priority weight corresponding to the priority of the j-th dedicated channel.

[0042] Communication layer 230 is used to transmit device data to data aggregation layer 240 via Internet communication protocol.

[0043] The data aggregation layer 240 is used to push device data to real-time edge computing nodes in a streaming manner and store it in an offline analysis platform according to preset processing logic, and to upload the processing results returned by the edge computing nodes to the application layer 250.

[0044] Application layer 250 is used to send operation instructions to data aggregation layer 240. Data aggregation layer 240 stores operation instructions and sends them to communication layer 230.

[0045] The communication layer 230 is also used to pre-store operation instructions and dedicated channel bandwidth allocation strategies, and to readjust the dedicated channel bandwidth; at the same time, it sends the operation instructions to the physical layer 220; each physical device in the physical layer 220 executes the operation instructions.

[0046] The above are method embodiments of this application. Based on the same inventive concept, this application also provides a source-network-load-storage data aggregation and processing device. Figure 3 As shown, the device includes: a processor; and a memory storing executable code thereon, which, when executed, causes the processor to perform a source-network-load-storage data aggregation processing method as described in the above embodiments.

[0047] Specifically, the server divides the network bandwidth of the physical layer and communication layer into several dedicated channels; configures the type and priority of each dedicated channel; determines the dedicated channel corresponding to each physical device based on its type; the physical devices transmit device data to the communication layer through their corresponding dedicated channels and device communication protocols; during transmission, the real-time bandwidth of the dedicated channels is dynamically adjusted according to their priority and the hop count of the edge computing nodes corresponding to each dedicated channel in the data aggregation layer; the communication layer transmits device data to the data aggregation layer via the Internet communication protocol; the data aggregation layer pushes the device data to the real-time edge computing nodes in a streaming manner and stores it in the offline analysis platform according to preset processing logic, and uploads the processing results returned by the edge computing nodes to the application layer; the application layer sends operation instructions to the data aggregation layer, which stores the operation instructions and sends them to the communication layer, readjusting the dedicated channel bandwidth based on the pre-stored operation instructions and dedicated channel bandwidth allocation strategy; simultaneously, the operation instructions are sent to the physical layer; and each physical device in the physical layer executes the operation instructions.

[0048] In addition, embodiments of this application also provide a non-volatile computer storage medium storing executable instructions, which, when executed, implement the source-network-load-storage data aggregation processing method described above.

[0049] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A source network load storage data aggregation processing method, characterized in that, The method includes: The network bandwidth of the physical layer and communication layer is divided into several dedicated channels; the type and priority of each dedicated channel are configured; and the dedicated channel corresponding to each physical device is determined based on the type of physical device in the physical layer. Physical devices transmit device data to the communication layer through corresponding dedicated channels and device communication protocols; during the transmission process, the real-time bandwidth of the dedicated channel is dynamically adjusted according to the priority of the dedicated channel and the number of hops of the edge computing node corresponding to the dedicated channel in the data aggregation layer. The communication layer transmits device data to the data aggregation layer via Internet communication protocols; the data aggregation layer pushes the device data to the real-time edge computing node in a streaming manner and stores it in the offline analysis platform according to the preset processing logic, and uploads the processing results returned by the edge computing node to the application layer; The application layer sends operation instructions to the data aggregation layer, which stores the operation instructions and then sends them to the communication layer. Based on the operation instructions stored in the communication layer and the dedicated channel bandwidth allocation strategy, the dedicated channel bandwidth is adjusted again. At the same time, the operation instructions are sent to the physical layer, and each physical device in the physical layer executes the operation instructions. During transmission, the real-time bandwidth of the dedicated channel is dynamically adjusted based on its priority and the hop count of the corresponding edge computing node in the data aggregation layer. Specifically, this includes: Through the formula: , calculating the real-time bandwidth of the ith dedicated channel ; wherein, denotes the total bandwidth, denotes the priority weight corresponding to the priority of the ith dedicated channel; denotes the attenuation coefficient, denotes the hop number of the corresponding edge computing node in the data aggregation layer, and N denotes the total number of dedicated channels, denotes the priority weight corresponding to the priority of the jth dedicated channel.

2. The source network repository function data aggregation processing method of claim 1, wherein, The network bandwidth of the physical layer and communication layer is divided into several dedicated channels, specifically including: By employing IP small-granularity hard slicing technology, the network bandwidth of the physical layer and communication layer is divided into several dedicated channels.

3. The source network repository function data aggregation processing method of claim 1, wherein, Device data includes device ID code, collection time, and collected data; Before the data aggregation layer pushes device data to the real-time edge computing node and stores it in the offline analysis platform in a streaming manner according to the preset processing logic, the method further includes: The data aggregation layer aligns device data from several physical devices using a sliding time window interpolation algorithm based on the acquisition time of the device data.

4. The source-network-shoal data aggregation processing method of claim 1, wherein, The communication layer transmits device data to the data aggregation layer via Internet communication protocols, specifically including: By employing IP small-granularity hard slicing technology, the network bandwidth of the communication layer and data aggregation layer is divided into several dedicated channels, and a one-to-one correspondence is configured between the dedicated channels between the communication layer and the data aggregation layer and the dedicated channels between the physical layer and the communication layer.

5. A source network data aggregation processing system, comprising: The system includes: The channel configuration module is used to divide the network bandwidth of the physical layer and the communication layer into several dedicated channels; configure the type and priority of each dedicated channel; and determine the dedicated channel corresponding to the physical device based on the type of physical device in the physical layer. The physical layer is used to transmit device data of physical devices to the communication layer through corresponding dedicated channels and device communication protocols. During the transmission process, the real-time bandwidth of the dedicated channel is dynamically adjusted according to the priority of the dedicated channel and the number of hops of the edge computing node corresponding to the dedicated channel in the data aggregation layer. The communication layer is used to transmit device data to the data aggregation layer via Internet communication protocols. The data aggregation layer is used to push device data to real-time edge computing nodes in a streaming manner and store it in an offline analysis platform according to preset processing logic, and upload the processing results returned by the edge computing nodes to the application layer. The application layer is used to send operation instructions to the data aggregation layer. The data aggregation layer stores the operation instructions and then sends them to the communication layer. The communication layer is also used to pre-store operation instructions and dedicated channel bandwidth allocation strategies, and to readjust the dedicated channel bandwidth; at the same time, it sends the operation instructions to the physical layer; and each physical device in the physical layer executes the operation instructions. The physical layer includes adjustment units. Used in the formula: , calculating the real-time bandwidth of the ith dedicated channel ; wherein, denotes the total bandwidth, denotes the priority weight corresponding to the priority of the i-th dedicated channel; denotes the attenuation coefficient, denotes the hop number of the corresponding edge computing node in the data aggregation layer, and N denotes the total number of dedicated channels, denotes the priority weight corresponding to the priority of the j-th dedicated channel.

6. The source network repository function data aggregation handling system of claim 5, wherein, The channel configuration module includes a channel configuration unit. This is used to divide the network bandwidth of the physical layer and communication layer into several dedicated channels using IP small-granularity hard slicing technology.

7. A source-grid-load-storage data aggregation and processing device, characterized in that, The device includes: processor; And a memory having executable code stored thereon, which, when executed, causes the processor to perform a source-network-load-storage data aggregation processing method as described in any one of claims 1-4.

8. A non-volatile computer storage medium, characterized in that, It stores computer instructions, which, when executed, implement a source-grid-load-storage data aggregation processing method as described in any one of claims 1-4.

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