A system, method, and medium for smooth scheduling of massive data based on multi-agent agents.

Abstract

This invention discloses a system, method, and medium for smooth scheduling of massive data based on multi-agent proxies. The method includes: authenticating a first IoT terminal through a first device management module; receiving first data uploaded by the first IoT terminal and determining first data to be scheduled and first local data through a first device access module; decoding the first local data through the first device management module; sending the first data to be scheduled to a second device management module through a first agent proxy module and a second agent proxy module; and decoding the first data to be scheduled through the second device management module and returning a first command to the first IoT terminal based on the decoding result. This invention reduces the business computing pressure on a single cluster node of the IoT device management platform and ensures the stability of the IoT device management platform. This invention can be widely applied in the field of IoT data processing technology.

Description

Technical Field

[0001] This invention relates to the field of Internet of Things (IoT) data processing technology, and in particular to a system, method, and medium for smooth scheduling of massive data based on multi-agent agents. Background Technology

[0002] IoT device management platforms provide access services to devices, requiring them to provide IP or domain names, configure device addresses, and send data to the IoT platform. As the number of IoT devices increases, a single-node deployment approach to provide access services to a massive number of devices faces significant computational pressure. Deploying multiple nodes is necessary to distribute the workload and reduce computational burden. Deploying multiple platform nodes means providing multiple IP or domain names, but IoT devices are geographically dispersed, and modifying device configuration addresses requires significant manpower and resources. Therefore, for already deployed devices, without modifying their access addresses, it is necessary to achieve smooth scheduling of services across multiple nodes to avoid overwhelming a single node with excessive computational pressure.

[0003] To avoid excessive computational load on a single node, it's necessary to deploy new nodes to reduce pressure. However, simply migrating devices from existing nodes to new ones by modifying their configuration addresses has significant drawbacks: IoT devices are highly distributed, and for devices already connected and operational, changing their configuration addresses results in lost revenue and substantial human and financial resources. Furthermore, the pressure on nodes in different regions fluctuates with the number of IoT devices, and simply changing device configuration addresses cannot fundamentally solve the problem of uneven pressure distribution across nodes.

[0004] Therefore, as the number of IoT devices increases, how to achieve smooth scheduling of device access across multiple nodes in a multi-node IoT platform, so as to realize business sharing and reduce the business computing pressure on a single node, has become an urgent problem to be solved. Summary of the Invention

[0005] The purpose of this invention is to at least partially solve one of the technical problems existing in the prior art.

[0006] Therefore, one objective of this invention is to provide a smooth scheduling system for massive data based on multi-agent agents that can reduce the computational pressure on a single node.

[0007] Another objective of this invention is to provide a method for smooth scheduling of massive data based on multi-agent agents.

[0008] To achieve the above-mentioned technical objectives, the technical solutions adopted in the embodiments of the present invention include:

[0009] In a first aspect, embodiments of the present invention provide a massive data smooth scheduling system based on multi-Agent agents, including an IoT device management platform and multiple IoT terminals. The IoT device management platform includes a first cluster and a second cluster. The first cluster includes a first device access module, a first device management module, and a first agent module. The second cluster includes a second device management module and a second agent module. The first device access module is used to receive first data uploaded by a first IoT terminal and determine first data to be scheduled and first local data. The first device management module is used to authenticate the first IoT terminal and decode the first local data. The first agent module is used to forward the first data to be scheduled to the second agent module. The second agent module is used to send the first data to be scheduled to the second device management module. The second device management module is used to decode the first data to be scheduled and return a first command to the first IoT terminal based on the decoding result.

[0010] Furthermore, in one embodiment of the present invention, the first device access module includes:

[0011] The data transmission unit is used to access the first IoT terminal and receive the first data uploaded by the first IoT terminal via the CoAPS / MQTTS protocol;

[0012] The data distribution unit is used to determine the first data to be scheduled and the first local data based on the computing pressure of the first cluster and the first data, and to send the first data to be scheduled to the first agent module and the first local data to the first device management module.

[0013] Furthermore, in one embodiment of the present invention, the first device management module includes:

[0014] The authentication unit is used to authenticate the login of the first IoT terminal connected to the device access unit.

[0015] A decoding unit is used to decode the first local data sent by the data distribution unit and generate a second command based on the decoding result;

[0016] The command issuing unit is used to issue the first command returned by the second device management module and the second command generated by the decoding unit to the first IoT terminal.

[0017] Furthermore, in one embodiment of the present invention, the first Agent module includes:

[0018] A data publishing unit is used to report and publish the first data to be scheduled sent by the data distribution unit;

[0019] The data forwarding unit is used to forward the first data to be scheduled to the second Agent proxy module via the IOAmqp protocol.

[0020] Furthermore, in one embodiment of the present invention, the second Agent proxy module includes:

[0021] The data receiving unit is used to receive the first data to be scheduled forwarded by the data forwarding unit;

[0022] The device synchronization unit is used to synchronize device information of the first IoT terminal according to the first data to be scheduled.

[0023] The command forwarding unit is used to send the first command returned by the second device management module to the command issuing unit.

[0024] Furthermore, in one embodiment of the present invention, the second cluster further includes a second device access module, which is used to receive second data uploaded by the second IoT terminal and determine the second data to be scheduled and the second local data. The second device management module is also used to authenticate the second IoT terminal and decode the second local data.

[0025] Furthermore, in one embodiment of the present invention, both the first cluster and the second cluster further include an API gateway module, which is used to share and synchronize the device information of the IoT terminal.

[0026] Secondly, embodiments of the present invention provide a method for smooth scheduling of massive data based on multi-Agent proxies. This method is executed through an IoT device management platform, which includes a first cluster and a second cluster. The first cluster includes a first device access module, a first device management module, and a first Agent proxy module. The second cluster includes a second device management module and a second Agent proxy module. The method for smooth scheduling of massive data includes the following steps:

[0027] The first IoT terminal is authenticated and logged in through the first device management module.

[0028] The first device access module receives the first data uploaded by the first IoT terminal and determines the first data to be scheduled and the first local data.

[0029] The first local data is decoded by the first device management module;

[0030] The first data to be scheduled is sent to the second device management module through the first agent proxy module and the second agent proxy module;

[0031] The second device management module decodes the first data to be scheduled and returns a first command to the first IoT terminal based on the decoding result.

[0032] Thirdly, embodiments of the present invention provide a device for smooth scheduling of massive data based on multi-agent agents, comprising:

[0033] At least one processor;

[0034] At least one memory for storing at least one program;

[0035] When the at least one program is executed by the at least one processor, the at least one processor implements the above-described method for smooth scheduling of massive data based on a multi-agent agent.

[0036] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing a processor-executable program, which, when executed by a processor, is used to perform the above-described method for smooth scheduling of massive data based on multi-agent agents.

[0037] The advantages and beneficial effects of the present invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention:

[0038] This invention, in its embodiment, determines the data to be scheduled and local data through the original cluster node's device access module. The agent proxy module forwards the marked data to be scheduled to the agent proxy module of another cluster node. The device management module on the other cluster node decodes the data and sends a command back to the original cluster node's device management module, which then sends it to the corresponding IoT terminal. This reduces the computational burden on the original cluster node without requiring changes to device configuration. It enables free and smooth scheduling of massive amounts of data between different cluster nodes and facilitates business processing of access devices across different cluster nodes. This reduces the computational burden on a single cluster node of the IoT device management platform, effectively ensuring its stability and improving its computational efficiency. Attached Figure Description

[0039] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the embodiments of the present invention are described below. It should be understood that the drawings described below are only for the convenience of clearly describing some embodiments of the technical solutions of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0040] Figure 1 A flowchart illustrating the steps of a method for smooth scheduling of massive data based on multi-agent proxies provided in this embodiment of the invention;

[0041] Figure 2 This invention provides a structural block diagram of a massive data smooth scheduling system based on multi-agent agents, as shown in an embodiment of the invention.

[0042] Figure 3 This is a structural block diagram of a massive data smoothing scheduling device based on multi-Agent agents, provided in an embodiment of the present invention. Detailed Implementation

[0043] The embodiments of the present invention are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention. The step numbers in the following embodiments are set only for ease of explanation, and there is no limitation on the order between the steps. The execution order of each step in the embodiments can be adaptively adjusted according to the understanding of those skilled in the art.

[0044] In the description of this invention, "multiple" means two or more. The use of "first" and "second" is for distinguishing technical features only and should not be construed as indicating or implying relative importance, or implicitly indicating the number of indicated technical features, or the order of the indicated technical features. Furthermore, 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.

[0045] Reference Figure 2This invention provides a massive data smooth scheduling system based on multi-Agent agents, including an IoT device management platform and multiple IoT terminals. The IoT device management platform includes a first cluster and a second cluster. The first cluster includes a first device access module, a first device management module, and a first agent module. The second cluster includes a second device management module and a second agent module. The first device access module is used to receive first data uploaded by a first IoT terminal and determine first data to be scheduled and first local data. The first device management module is used to authenticate the first IoT terminal and decode the first local data. The first agent module is used to forward the first data to be scheduled to the second agent module. The second agent module is used to send the first data to be scheduled to the second device management module. The second device management module is used to decode the first data to be scheduled and return a first command to the first IoT terminal based on the decoding result.

[0046] Specifically, this embodiment of the invention includes an IoT terminal, an IoT device management platform, and an IoT private network core network. The IoT terminal attaches to the network, the core network establishes a session bearer, and assigns an IP address to the terminal. After obtaining the IP address, the terminal reports data information. The IoT private network core network is configured according to the destination IP address accessed by the terminal. For terminals accessing the IoT device management platform, the CoAPS / MQTTS protocol is used to access the IoT device management platform. The IoT device management platform accesses the device management service for login authentication and data decoding, reports the device data to be scheduled, and publishes it through Kafka, where it is consumed by the Agent proxy module. Through data transmission between the new and old cluster Agent proxy modules, the device platform of the new cluster node synchronizes device information for authentication, data decoding, and command issuance, while the device management platform of the old cluster node issues commands back to the IoT terminal through a specified CIG.

[0047] The embodiments of the present invention reduce the business computing pressure of the original cluster nodes without changing the device configuration, enabling free and smooth scheduling of massive data between different cluster nodes and business processing of access devices between different cluster nodes. This reduces the business computing pressure of a single cluster node of the IoT device management platform, effectively ensuring the stability of the IoT device management platform and improving the business computing efficiency of the IoT device management platform.

[0048] As a further optional implementation, the first device access module includes:

[0049] The data transmission unit is used to access the first IoT terminal and receive the first data uploaded by the first IoT terminal via the CoAPS / MQTTS protocol;

[0050] The data distribution unit is used to determine the first data to be scheduled and the first local data based on the computing pressure of the first cluster and the first data, and to send the first data to be scheduled to the first agent module and the first local data to the first device management module.

[0051] As a further optional implementation, the first device management module includes:

[0052] The authentication unit is used to authenticate the login of the first IoT terminal connected to the device access unit.

[0053] The decoding unit is used to decode the first local data sent by the data distribution unit and generate a second command based on the decoding result.

[0054] The command issuing unit is used to issue the first command returned by the second device management module and the second command generated by the decoding unit to the first IoT terminal.

[0055] As an optional implementation, the first Agent module includes:

[0056] The data publishing unit is used to report and publish the first data to be scheduled sent by the data distribution unit;

[0057] The data forwarding unit is used to forward the first data to be scheduled to the second Agent module via the IOAmqp protocol.

[0058] As an optional implementation, the second Agent module includes:

[0059] The data receiving unit is used to receive the first data to be scheduled forwarded by the data forwarding unit;

[0060] The device synchronization unit is used to synchronize device information of the first IoT terminal based on the first data to be scheduled.

[0061] The command forwarding unit is used to send the first command returned by the second device management module to the command issuing unit.

[0062] Reference Figure 2 As an optional implementation, the second cluster also includes a second device access module, which is used to receive the second data uploaded by the second IoT terminal and determine the second data to be scheduled and the second local data. The second device management module is also used to authenticate the second IoT terminal and decode the second local data.

[0063] Reference Figure 2 As an optional implementation, both the first cluster and the second cluster also include an API gateway module, which is used to share and synchronize device information of IoT terminals.

[0064] The system structure of the embodiments of the present invention has been described above. The specific operation process of the embodiments of the present invention will be further explained below with reference to a specific embodiment.

[0065] 1) such as Figure 2 As shown, the first IoT terminal is connected to the first device access module via IP1 and reports data through the CoAPS / MQTTS protocol;

[0066] 2) The first device management module performs login authentication and data decoding on the first IoT terminal;

[0067] 3) Report the data to be scheduled and publish the information through Kafka to the first Agent module;

[0068] 4) The first Agent module forwards the data to be scheduled to the second Agent module in the second cluster via the IOAmqp protocol;

[0069] 5) The second device management module of the second cluster synchronizes device information through the second agent proxy module, and can also process the second IoT terminal accessed by IP2, and perform authentication and data decoding.

[0070] 6) The second device management module issues commands and forwards them back to the first device management module through the second agent proxy module. The commands are then issued to the first IoT terminal by specifying the CIG, thereby reducing the computing pressure on the first cluster.

[0071] 7) Each IoT terminal can synchronize with the API gateway of each cluster to obtain product lists and device information.

[0072] It is recognized that the increase of IoT devices on a single node puts significant computational pressure on the device management platform. Traditional solutions involve changing the configuration addresses of each device connected to the original node, which is difficult to implement and consumes substantial human and material resources. To address this issue, this invention proposes a method for scheduling and transferring massive amounts of data between clusters based on multi-agent proxies. By having the device access module forward data transmitted from the terminal through agent proxy modules, the data is processed by the device management module on another node, achieving smooth scheduling of massive amounts of data without requiring changes to device configurations.

[0073] Reference Figure 1This invention provides a method for smooth scheduling of massive data based on multi-agent proxies. The method is executed through an IoT device management platform, which includes a first cluster and a second cluster. The first cluster includes a first device access module, a first device management module, and a first agent proxy module. The second cluster includes a second device management module and a second agent proxy module. The method for smooth scheduling of massive data includes the following steps:

[0074] S101. Login authentication of the first IoT terminal is performed through the first device management module;

[0075] S102, Receive the first data uploaded by the first IoT terminal through the first device access module and determine the first data to be scheduled and the first local data;

[0076] S103. Decode the first local data through the first device management module;

[0077] S104. The first data to be scheduled is sent to the second device management module through the first agent agent module and the second agent agent module;

[0078] S105. The first data to be scheduled is decoded by the second device management module and the first command is returned to the first IoT terminal according to the decoding result.

[0079] The content of the above system embodiments is applicable to this method embodiment. The specific functions implemented in this method embodiment are the same as those in the above system embodiments, and the beneficial effects achieved are also the same as those achieved in the above system embodiments.

[0080] Reference Figure 3 This invention provides a device for smooth scheduling of massive data based on multi-agent proxies, comprising:

[0081] At least one processor;

[0082] At least one memory for storing at least one program;

[0083] When the above-mentioned at least one program is executed by the above-mentioned at least one processor, the above-mentioned at least one processor implements the above-mentioned method for smooth scheduling of massive data based on multi-Agent agents.

[0084] The content of the above method embodiments is applicable to the device embodiments. The specific functions implemented by the device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0085] This invention also provides a computer-readable storage medium storing a processor-executable program that, when executed by a processor, performs the aforementioned method for smooth scheduling of massive data based on a multi-agent agent.

[0086] This invention provides a computer-readable storage medium that can execute a method for smooth scheduling of massive data based on multi-agent agents provided in the method embodiments of this invention. It can execute any combination of the implementation steps of the method embodiments and has the corresponding functions and beneficial effects of the method.

[0087] This invention also discloses a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device can read the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, causing the computer device to perform... Figure 1 The method shown.

[0088] In some alternative embodiments, the functions / operations mentioned in the block diagrams may not occur in the order shown in the operation diagrams. For example, depending on the functions / operations involved, two consecutively shown blocks may actually be executed substantially simultaneously, or the aforementioned blocks may sometimes be executed in reverse order. Furthermore, the embodiments presented and described in the flowcharts of this invention are provided by way of example to provide a more comprehensive understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented herein. Alternative embodiments are contemplated in which the order of various operations is changed and sub-operations described as part of a larger operation are executed independently.

[0089] Furthermore, although the invention has been described in the context of functional modules, it should be understood that, unless otherwise stated, one or more of the aforementioned functions and / or features may be integrated into a single physical device and / or software module, or one or more functions and / or features may be implemented in a separate physical device or software module. It is also understood that a detailed discussion of the actual implementation of each module is unnecessary for understanding the invention. Rather, given the properties, functions, and internal relationships of the various functional modules in the apparatus disclosed herein, the actual implementation of the module will be understood within the scope of conventional skill of an engineer. Therefore, those skilled in the art can implement the invention as set forth in the claims using ordinary techniques without excessive experimentation. It is also understood that the specific concepts disclosed are merely illustrative and not intended to limit the scope of the invention, which is determined by the full scope of the appended claims and their equivalents.

[0090] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0091] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0092] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the aforementioned program can be printed, because the aforementioned program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or, if necessary, processing in other suitable ways, and then stored in computer memory.

[0093] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0094] In the foregoing description of this specification, references to terms such as "one embodiment," "another embodiment," or "some embodiments" indicate that a specific feature, structure, material, or characteristic described in connection with an embodiment or example is included in at least one embodiment or example of the present invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0095] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

[0096] The above is a detailed description of the preferred embodiments of the present invention. However, the present invention is not limited to the above embodiments. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention. All such equivalent modifications or substitutions are included within the scope defined by the claims of this application.

Claims

1. A massive data smoothing scheduling system based on multi-agent agents, characterized in that: The system includes an IoT device management platform and multiple IoT terminals. The IoT device management platform includes a first cluster and a second cluster. The first cluster includes a first device access module, a first device management module, and a first agent proxy module. The second cluster includes a second device management module and a second agent proxy module. The first device access module is used to receive first data uploaded by a first IoT terminal and determine first data to be scheduled and first local data. The first device management module is used to authenticate the first IoT terminal and decode the first local data. The first agent proxy module is used to forward the first data to be scheduled to the second agent proxy module. The second agent proxy module is used to send the first data to be scheduled to the second device management module. The second device management module is used to decode the first data to be scheduled and return a first command to the first IoT terminal based on the decoding result. The first device access module includes: The data transmission unit is used to access the first IoT terminal and receive the first data uploaded by the first IoT terminal via the CoAPS / MQTTS protocol; The data distribution unit is used to determine the first data to be scheduled and the first local data based on the computing pressure of the first cluster and the first data, and to send the first data to be scheduled to the first Agent module and the first local data to the first device management module. The first device management module includes: An authentication unit is used to authenticate the login of the first IoT terminal accessed by the data transmission unit. A decoding unit is used to decode the first local data sent by the data distribution unit and generate a second command based on the decoding result; The command issuing unit is used to issue the first command returned by the second device management module and the second command generated by the decoding unit to the first IoT terminal; The first Agent module includes: A data publishing unit is used to report and publish the first data to be scheduled sent by the data distribution unit; The data forwarding unit is used to forward the first data to be scheduled to the second Agent proxy module via the IOAmqp protocol; The second Agent module includes: The data receiving unit is used to receive the first data to be scheduled forwarded by the data forwarding unit; The device synchronization unit is used to synchronize device information of the first IoT terminal according to the first data to be scheduled. The command forwarding unit is used to send the first command returned by the second device management module to the command issuing unit.

2. The massive data smooth scheduling system based on multi-agent agents according to claim 1, characterized in that: The second cluster also includes a second device access module, which is used to receive second data uploaded by the second IoT terminal and determine the second data to be scheduled and the second local data. The second device management module is also used to authenticate the second IoT terminal and decode the second local data.

3. A massive data smoothing scheduling system based on multi-agent agents according to claim 1 or 2, characterized in that: Both the first cluster and the second cluster further include an API gateway module, which is used to share and synchronize device information of the first IoT terminal.

4. A method for smooth scheduling of massive data based on multi-agent proxies, characterized in that, The massive data smooth scheduling method is implemented through a massive data smooth scheduling system based on a multi-agent agent as described in any one of claims 1 to 3, and the massive data smooth scheduling method includes the following steps: The first IoT terminal is authenticated and logged in through the first device management module. The first device access module receives the first data uploaded by the first IoT terminal and determines the first data to be scheduled and the first local data. The first local data is decoded by the first device management module; The first data to be scheduled is sent to the second device management module through the first agent proxy module and the second agent proxy module; The second device management module decodes the first data to be scheduled and returns a first command to the first IoT terminal based on the decoding result.

5. A device for smooth scheduling of massive data based on multi-agent agents, characterized in that, include: At least one processor; At least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the method for smooth scheduling of massive data based on a multi-agent agent as described in claim 4.

6. A computer-readable storage medium storing a processor-executable program, characterized in that, The processor-executable program, when executed by the processor, is used to perform a method for smooth scheduling of massive data based on a multi-agent agent as described in claim 4.

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