Cooperative control method, system and equipment for intelligent agent in industrial Internet of Things, and medium

Abstract

The invention provides a cooperative control method, system and device for agents in the industrial Internet of Things and a medium, and relates to the technical field of the industrial Internet of Things, and the method comprises the steps: obtaining the metadata of the agents, the metadata of the agents having corresponding levels; each agent is put into the corresponding hierarchy, and the agents contained in each hierarchy are updated; aiming at the updated hierarchies, constructing a communication topological structure according to the intelligent agents contained in each hierarchies; a preset mapping rule is adopted, at least one corresponding communication protocol is mapped for the communication topological structure, and the agents in the same level communicate through the communication protocol obtained through mapping. According to the method, the intelligent agents are divided into the corresponding hierarchies, and then the adaptive communication protocol is mapped for the single hierarchies, so that the communication protocol is more adaptive to the intelligent agents in the hierarchies, the internal communication of the hierarchies is more stable, meanwhile, the mutual influence between the hierarchies is also reduced through hierarchy division, and stable communication of the industrial Internet of Things is ensured.

Description

Technical Field

[0001] This application relates to the technical field of industrial Internet of Things, and particularly to a method, system, device and medium for collaborative control of agents in industrial Internet of Things. Background Art

[0002] With the rapid development of industrial Internet of Things, the number of devices in industrial environment has increased sharply, such as different types of devices like sensors, controllers, actuators, gateways, etc. A single device is also called an agent. Frequent data transmission is required between multiple agents to achieve functions such as real-time monitoring, automation control and data analysis. However, the current industrial Internet of Things systems face many challenges in device communication and management.

[0003] Firstly, the communication between agents usually relies on wired or wireless transmission lines. As the number of agents increases, the number of communication paths also increases exponentially, resulting in a large increase in the number of transmission lines. Too many transmission lines not only occupy physical space, but also may cause problems such as signal interference, transmission delay and increased failure rate. Secondly, the agents in industrial Internet of Things may come from different manufacturers and use different communication protocols (such as Modbus, CAN, Ethernet / IP, Profinet, etc.). This heterogeneity makes direct communication between agents difficult, and usually requires a protocol converter or gateway to achieve communication adaptation. This not only increases the cost and complexity of the system, but also may lead to a decrease in communication efficiency and potential compatibility problems. In addition, industrial Internet of Things systems usually need to process a large amount of real-time data, which may come from different agents and subsystems composed of multiple agents. Due to the lack of a unified data management and processing mechanism, the phenomenon of data islands is widespread, resulting in low data utilization rate and difficulty in realizing cross-device and cross-system collaborative work.

[0004] It can be seen that the current industrial Internet of Things systems have defects in device communication, data management and system scalability. Summary of the Invention

[0005] To overcome the above technical problems, this application provides a method, system, device and medium for collaborative control of agents in industrial Internet of Things to achieve the purpose of cross-level control and collaborative work of multiple agents. The technical solutions are as follows: In the first aspect, a method for collaborative control of agents in industrial Internet of Things is provided, including: Obtaining metadata of multi-source heterogeneous devices, where one of the multi-source heterogeneous devices is used as an agent, and the metadata of the agent has a corresponding level; Matching to obtain the level corresponding to the agent according to the metadata of the agent; Place each of the agents into their respective levels and update the agents included in each of the levels; For the updated levels, construct a communication topology based on the agents included in each level. The communication topology consists of nodes and line segments, where the nodes are agents and the line segments are communication paths between agents; Using a preset mapping rule, map at least one corresponding communication protocol to the communication topology in each level. Agents included in the same level use the mapped communication protocol for information interaction.

[0006] In a possible implementation, the constructing a communication topology based on the agents included in each level includes: Determine the central agent in each level. The central agent is the agent in the corresponding level that is used to interact with agents in other levels; Determine the other agents in the level that communicate with the central agent; Establish communication paths between the central agent and the other agents that communicate with the central agent to obtain the communication topology.

[0007] In a possible implementation, the determining the central agent includes: Calculate the communication scores of each agent. The communication scores are obtained by weighted calculation of function importance and communication frequency; Select the agent with the highest communication score as the central agent.

[0008] In a possible implementation, the using a preset mapping rule to map at least one corresponding communication protocol to the communication topology in each level includes: Obtain a plurality of initial protocols based on the communication topology; Select at least one protocol from the plurality of initial protocols as the communication protocol according to the priority of the agents in the communication topology and / or the priority of the data transmitted by the agents and / or the bandwidth of the communication paths between the agents.

[0009] In a possible implementation, when selecting at least one protocol from the plurality of initial protocols as the communication protocol according to the priority of the data transmitted by the agents in the communication topology and the bandwidth of the communication paths between the agents, the method includes: If the data priority is high and the bandwidth of the communication path is greater than the preset bandwidth, select the initial protocol with the maximum throughput and the lowest transmission delay as the communication protocol; If the data priority is high and the bandwidth of the communication path is less than or equal to the preset bandwidth, select an initial protocol that supports data compression or fragmentation as the communication protocol; If the data priority is low and the bandwidth of the communication path is greater than the preset bandwidth, select the initial protocol with the lowest power consumption as the communication protocol; If the data priority is low and the bandwidth of the communication path is less than or equal to the preset bandwidth, select an initial protocol that supports bulk transfer or asynchronous transfer as the communication protocol.

[0010] In a possible implementation, the metadata at least includes a functional role, computing power, geographical location, and a transmission protocol. The matching of the metadata of the agent to obtain the level corresponding to the agent includes: Determine the level corresponding to the agent according to any one or a combination of the functional role, computing power, geographical location, and transmission protocol of the agent.

[0011] In a possible implementation, the method further includes: When there are multiple levels in the industrial Internet of Things, there is a corresponding relationship between the communication protocols of different levels. The corresponding relationship at least includes one of the following: If there is information interaction between the first level and the second level, the communication protocol of the first level is compatible with the communication protocol of the second level; If there is no information interaction between the first level and the second level, the communication protocol of the first level is independent of the communication protocol of the second level; If there is data aggregation between the first level and the second level, the communication protocol of the first level supports conversion to the communication protocol of the second level; Wherein, the first level and the second level are used to represent different levels in the industrial Internet of Things.

[0012] In a second aspect, a collaborative control system for agents in an industrial Internet of Things is provided, which is used to execute the collaborative control method for agents in the industrial Internet of Things described in any one of the above, including: A data acquisition module, configured to acquire metadata of multi-source heterogeneous devices, where one of the multi-source heterogeneous devices is used as an agent, and the metadata of the agent has a corresponding level; A data matching module, configured to match the metadata of the agent to obtain the level corresponding to the agent; A data processing module, configured to place each agent into its corresponding level and update the agents included in each level; A data construction module, configured to construct a communication topology for an updated layer according to agents included in each layer, where the communication topology consists of nodes and line segments, the nodes are agents, and the line segments are communication paths between agents; A data determination module, configured to map at least one corresponding communication protocol for the communication topology in each layer by using a preset mapping rule, and agents included in the same layer perform information interaction by using the mapped communication protocol.

[0013] In a third aspect, an electronic device is provided, which includes a processor and a memory. Among them, a computer program is stored in the memory, and the processor is configured to run the computer program to execute the collaborative control method of agents in the industrial Internet of Things as described in any one of the above.

[0014] In a fourth aspect, a storage medium is provided, which stores a computer program. Among them, the computer program is configured to execute the collaborative control method of agents in the industrial Internet of Things as described in any one of the above when running.

[0015] The technical solutions provided in the embodiments of the present application can achieve the following technical effects: (1) In the present application, agents are first divided into different layers. For each layer, a communication topology is constructed according to the agents included in the layer, and then a corresponding communication protocol is mapped according to the communication topology in the layer (including the priority of agents, the priority of data transmitted by agents, the bandwidth of communication paths, etc.), so that the communication protocol is more adapted to the agents in the layer, and the internal communication of a single layer is more stable and efficient.

[0016] (2) Through the above layer division method, the agents in the industrial Internet of Things are divided into different layers in the present application, reducing the mutual influence between layers and ensuring stable communication of the industrial Internet of Things. Description of the Drawings

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for description in the embodiments of the present application will be briefly introduced below. In the drawings: Figure 1 is a flowchart of the collaborative control method of agents in the industrial Internet of Things provided by the embodiments of the present application; Figure 2 is a flowchart of the work of agents in the method embodiments of the present application; Figure 3 is a block diagram of the collaborative control system of agents in the industrial Internet of Things provided by the embodiments of the present application; Figure 4 is a structural diagram of an electronic device provided by the embodiments of the present application. Detailed implementation manners

[0018] Exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present application can be more thoroughly understood and the scope of the present application can be fully conveyed to those skilled in the art.

[0019] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects and do not necessarily have to be used to describe a specific order or sequence. It should be understood that such use can be interchanged under appropriate circumstances so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the term "comprising" and its variants are to be construed as open-ended terms meaning "including but not limited to".

[0020] In order to promote the intelligence of the industrial Internet of Things, the number of devices included in the industrial Internet of Things has been increasing in recent years. A large number of devices are used for data collection and data processing, providing data guarantee for intelligent applications. Specifically, the industrial Internet of Things usually has the following characteristics: 1) The devices in the industrial Internet of Things can be widely distributed and can be located in different geographical locations; 2) It can require logically high-precision synchronous timing and can provide time bases from ns (nanosecond), us (microsecond), ms (millisecond) to s (second); 3) It can require strict logical time sequences; 4) Prediction and real-time feedback act together; 5) In terms of artificial intelligence, it has intelligent processing of perception, decision-making, and execution.

[0021] This industrial Internet of Things is applicable to the requirements of high logic and time. It can be a large-scale distributed synchronous real-time control system or a widely distributed real-time control system with high synchronization. For example, it can be one or a combination of an accelerator, a reactor, a fission device, a fusion device, chemical industry, electric power, and a large accelerator. This embodiment does not limit this.

[0022] The industrial Internet of Things can also be a system with relatively high time accuracy requirements for the logical sequence of operations, such as a production line with close associations, etc. Based on the system with time accuracy requirements, multi-dimensional data with spatio-temporality is collected through each device in the system, and the multi-dimensional data is used to digitally map the system in the real scenario, providing data support for building a native data base under the spatio-temporal coordinates and supporting the full-link data analysis and modeling covered in the system.

[0023] Most of the devices in the above-mentioned Industrial Internet of Things have cross-access to each other, resulting in an increasing number of communication paths established between devices, occupying physical space. Moreover, there may be signal interference problems between different communication paths, causing transmission delays or transmission failures. At the same time, a large number of devices in the Industrial Internet of Things also have incompatible communication protocols and inconsistent data processing mechanisms, resulting in low data utilization rates, making it difficult to achieve cross-device and cross-system collaborative work, and affecting the intelligent development of the Industrial Internet of Things.

[0024] To solve the above technical problems, the embodiments of the present application provide a collaborative control method for agents in the Industrial Internet of Things, as Figure 1 shown, the collaborative control method for agents in the Industrial Internet of Things may include the following steps S101 to S105: Step S101, obtain the metadata of multi-source heterogeneous devices, where a multi-source heterogeneous device serves as an agent, and the metadata of the agent has a corresponding level; Step S102, match the level corresponding to the agent according to the metadata of the agent.

[0025] An agent refers to a single device with communication functions in the Industrial Internet of Things. The types, functions, and sources of different single devices may be different, so an agent can also be a multi-source heterogeneous device, that is, this embodiment supports dividing multi-source heterogeneous devices into different levels. In this embodiment, it mainly targets agents newly connected to the Industrial Internet of Things or agents in the Industrial Internet of Things after transformation, that is, dividing agents that have not been divided into the corresponding levels for subsequent unified management and maintenance.

[0026] Among the agents, some agents serve as edge control devices and intelligent carriers, and these edge control devices and intelligent carriers undertake functions such as data collection, analysis, processing, and instruction execution in the Industrial Internet of Things. For the sake of illustration, for example Figure 2 shown, in Figure 2 both the edge control device and the intelligent carrier are represented by GIANT, Figure 2 in which GIANT1 and GIANT2 represent different agents. Among them, the protocols supported by GIANT1 include the PS protocol and the Low Level Reader Protocol (LLRF). GIANT2 also supports the same protocols as GIANT1. GIANT1 and GIANT2 communicate with the cloud brain through the EPICS protocol or the standard protocol. Specifically, the functions of GIANT1, GIANT2, and other agents are as follows: 1) Task acceptance and analysis: Accurately receive plans and task instructions from the Cloud Brain. As the core decision-making unit of the Industrial Internet, the Cloud Brain generates macro-level operational plans based on global data and complex algorithms. After receiving the instructions, the agent conducts in-depth analysis to extract key information, such as the specific accelerator operating parameter settings, the order of task execution, and the expected operational results, thereby fully preparing for subsequent execution steps. 2) Task execution is based on unified time constraints: The time sequence is provided by the timing system, and the intelligent agent is equipped with a precise clock synchronization mechanism to strictly control the timing of each operation step, so that the accelerator can be organized and driven to execute tasks in an orderly manner according to the time sequence; 3) Closed-Loop Operation: Leveraging the powerful parallel processing capabilities and fast response speed of the edge FPGA controller, the FPGA controller can collect various data during the accelerator's operation in real time, such as beam intensity, energy status, and device temperature. Based on this real-time data and the task requirements of the cloud brain, the intelligent agent quickly adjusts the accelerator's operating parameters, such as RF power and magnetic field strength, through the FPGA controller, thus forming a complete closed loop from data collection and analysis to control and adjustment. 4) Regional prediction and decision-making: While completing the accelerator operation task, the intelligent agent uses local rich data resources and built-in intelligent algorithms. Through in-depth mining and analysis of the accelerator's historical operation data, surrounding environment data, and real-time monitoring data, the edge intelligent agent can predict the possible changes in the accelerator's operating status in the future, and realize regional-level prediction and decision-making functions. This facilitates the intelligent agent to make reasonable decisions based on the prediction results, reducing the resource consumption of the cloud brain, and adjusting maintenance plans in advance and optimizing operating parameters to avoid potential risks, thereby improving the reliability and overall efficiency of the accelerator's operation and reducing operating costs.

[0027] It should be noted that the devices in the industrial Internet of Things involved below are all represented by intelligent agents.

[0028] The metadata of the agent includes, but is not limited to, functional role, computing power, geographical location, and transmission protocol. Among them, the functional role of the agent refers to its function in the industrial Internet, such as any one of sensors, actuators, and gateways. The computing power of the agent represents the processing power, storage capacity, and resource limitations of the agent, and the computing power is related to the hardware configuration of the agent. The geographical location of the agent represents its physical location in the industrial Internet of Things, such as GPS coordinates or workshop location, etc. The transmission protocol of the agent represents the protocols it supports, such as Modbus communication protocol, Message Queuing Telemetry Transport (MQTT), and Hypertext Transfer Protocol (HTTP).

[0029] Based on the metadata of the agent, the agent is divided into different levels.

[0030] In a specific example, the agent is divided into different levels according to its functional role. Specifically, first divide the levels of the industrial Internet of Things in advance, and set the functions that the agents in each level need to possess. Then calculate the matching degree between the agent and the agents in different levels. Here, the method of calculating the matching degree is obtained by using a deep neural network model, and it is obtained by calculating the similarity of the functions that the agent and the agents in the level both possess. Finally, the agent is divided into the level with the highest matching degree. For the convenience of explanation, the following is an example: Suppose the industrial Internet of Things is divided into three layers: the end layer, the edge layer, and the cloud layer from bottom to top. Among them, the agents in the end layer need to have the ability to collect real-time data. The real-time data collected by multiple agents in the end layer has spatio-temporality, and the agent can perform preliminary processing on the real-time data. The agents in the edge layer need to make local optimization decisions and refine strategies based on the data uploaded from the end layer and the strategies issued by the cloud layer to improve the decision-making efficiency and accuracy. The cloud layer formulates long-term strategic decisions from a global perspective. The agents in the cloud layer, as the decision-making brain of the industrial Internet, can perform semantic parsing, logical reasoning, and strategy planning on the real-time data with spatio-temporality, and issue the decisions to the edge layer. Based on the levels divided in advance, according to the matching degree between the agent and the agents in different levels, the agent is divided into the level with the highest matching degree.

[0031] In a specific example, the agent is divided into different levels according to its computing power. Similar to the above method of using the functional role as the division basis, when using the computing power as the basis for dividing the agent, first divide the levels of the industrial Internet of Things in advance, and set the computing power that the agents in each level need to possess. Then, according to the level that the computing power of the agent falls into as its belonging level, the agent is divided into the belonging level.

[0032] In a specific example, the intelligent agents are divided into different levels based on their geographical locations. Specifically, according to the distribution of intelligent agents, the intelligent agents within a certain range are regarded as one level, or according to the distribution of intelligent agents, the intelligent agents are divided into levels according to different transmission segments. For the sake of convenience, taking the superconducting proton linear accelerator as an example, the various devices of the superconducting proton linear accelerator may include a room temperature front-end accelerator, a superconducting linear accelerator, and a high-energy transmission line and beam collection terminal, wherein the room temperature front-end accelerator may include an ion source and a low-energy transmission segment, a radio frequency quadrupole accelerator, and a medium-energy transmission segment; the superconducting linear accelerator may include a superconducting half-wavelength cavity acceleration segment, a superconducting spoke-type cavity acceleration segment, and a superconducting ellipsoidal cavity acceleration segment; the high-energy transmission line and beam collection terminal may include a high-energy transmission segment and a beam collection terminal. Based on this, the purpose of dividing the intelligent agents in the industrial Internet of Things into different levels can be achieved.

[0033] In a specific example, the agents are divided into different levels according to their transmission protocols. Specifically, multiple agents supporting the same transmission protocol are merged into one level to reduce protocol conversions in the same level and lower communication costs.

[0034] In other examples, the classification of agents into different tiers can also be based on a combination of any two or more of the agent's functional role, computing power, geographic location, and transmission protocol. The following uses the combination of an agent's functional role and geographic location as an example: First, the agent's matching degree with different tiers is calculated based on its functional role, and then its matching degree with different tiers is calculated based on its geographic location. The closer the agent's geographic location is to the agents in the tier, the higher the matching degree. Finally, the two matching degrees are combined, and the tier with the highest matching degree is used as the tier to which the agent belongs.

[0035] Step S103: Place each agent into its corresponding level and update the agents contained in each level.

[0036] After determining the level to which the agent belongs, place the agent in the level to which it belongs, and then update the agents in the level.

[0037] In order to reduce the number of updates of the agents in the hierarchy and reduce the impact of the newly added agents on the original agents in the hierarchy, it is usually necessary to divide all the agents into corresponding hierarchies, and then update the hierarchies where the agents have changed, while not updating the hierarchies where the agents have not changed.

[0038] Step S104. For the updated layer, construct a communication topology based on the agents included in each layer. The communication topology consists of nodes and line segments, where the nodes are agents and the line segments are the communication paths between agents.

[0039] For the updated layer, it is necessary to reconstruct the communication topology according to the agents in the layer. Take the construction of the communication topology of the agents in an updated layer as an example: First, determine the central agent; Second, determine the other agents that communicate with the central agent; Finally, build a communication path between the central agent and the other agents that communicate with the central agent to obtain the communication topology.

[0040] The above-mentioned central agent refers to the agent in the updated layer that is used to interact with the agents in other layers. The number of central agents can be multiple.

[0041] In a specific example, a communication score is calculated by weighted calculation based on the functional importance and communication frequency of the agents, and then the agent with the highest communication score is used as the central agent. Specifically: The functional importance of the agent corresponds to the first score I, 0 ≤ I ≤ 1. The first score I can be determined according to the functional role and business requirements of the agent. For example, the first score I of a key control device (such as a PLC or an industrial robot) is 1, the first score I of an important monitoring device (such as a vibration sensor) is 0.8, the first score I of an ordinary monitoring device (such as a temperature and humidity sensor) is 0.5, and the first score I of a non-critical device (such as an environmental monitoring device) is 0.2; The communication frequency of the agent corresponds to the second score F, 0 ≤ F ≤ 1. The second score F is determined by the number of communication times of the agent within a unit time. The greater the number of communication times of the agent within a unit time, the greater the second score F.

[0042] The communication score S is calculated based on the first score I and the second score F, S = w I ×I + w F ×F, where w I and w F are preset weights. w I represents the weight of the functional importance in the score, and w F represents the weight of the communication frequency in the score.

[0043] In another specific example, if there is only one gateway in the updated layer, the gateway is used as the central agent of this layer because the gateway is usually used for information interaction with agents in other layers. If there are multiple gateways in the updated layer, the central agent is determined by continuing to calculate the communication score in the above-mentioned manner.

[0044] As can be seen from the above, if there is only one central agent in the updated layer, and the remaining agents in this layer all communicate with the central agent, after establishing a communication path between the central agent and the remaining agents, the formed communication topology structure is a star topology. If there are multiple central agents in the updated layer and the multiple central agents communicate in a certain order, the formed communication topology structure is a tree topology. If there is cross-communication between the central agents, the formed communication topology structure is a mesh topology. Therefore, the communication topology structures in the layer are mainly divided into structures such as star, tree, and mesh.

[0045] Step S105, using a preset mapping rule, map at least one corresponding communication protocol to the communication topology structure in each layer, and the agents included in the same layer use the mapped communication protocol for information interaction.

[0046] In a possible implementation manner, the mapping rule adopts a static matching method. For example: The star topology structure usually has only one central agent, and the central agent is directly connected to multiple agents in the same layer where it is located. Then the communication protocols corresponding to the star topology structure can be the master-slave protocol and the centralized routing protocol. The master-slave protocol is such as Modbus RTU, and the centralized routing protocol is such as the coordinator-end device mode of Zigbee, so as to realize that the central agent is responsible for the scheduling of this layer; The tree topology structure has multiple paths and small differences in connection degrees, then the dynamic routing protocol and the flooding protocol can be adopted. The dynamic routing protocol is such as AODV, OLSR, and the flooding protocol is such as Gossip, so that this layer has a self-healing function; In the mesh topology structure, a closed loop is formed between some agents, and the remaining agents only have adjacent agents. Then the token ring protocol, such as IEEE 802.5, can be adopted, and the token passing mechanism is used to avoid conflicts.

[0047] In another possible implementation, the mapping rule adopts a combination of static matching and dynamic matching methods. For example, multiple initial protocols are obtained based on the communication topology. The initial protocols are pre-set protocols, and different initial protocols have different throughput, transmission delay, data compression ability, transmission power consumption, etc. In this embodiment, the corresponding relationship between different communication topologies and initial protocols is defined in advance. For example, in a star-shaped communication topology, the central agent needs to communicate with other agents. As the number of other agents increases, the communication pressure on the central agent also increases. Therefore, for a star-shaped communication topology, a protocol with a throughput higher than a certain throughput needs to be selected. For a tree-shaped communication topology, since the communication distance for data to be transmitted from the branches to the trunk is long and it passes through many nodes, the data needs to be compressed before transmission to reduce the data transmission pressure. Therefore, for a mesh communication topology, a protocol with data compression ability needs to be selected. Further, for a mesh communication topology, a protocol with a transmission delay lower than a certain time needs to be selected to ensure the timeliness and stability of various types of data during inter-level transmission.

[0048] Secondly, based on the priority of the agents in the communication topology and / or the priority of the data transmitted by the agents and / or the bandwidth of the communication paths between the agents, at least one protocol is selected from the multiple initial protocols as the communication protocol for the level.

[0049] In a specific example, at least one protocol is selected from the multiple initial protocols as the communication protocol according to the priority of the agents in the communication topology. First, according to the functional roles of the agents, corresponding priorities are assigned to the agents. For example, the priority of an agent with decision-making authority is higher than that of an agent that only transmits data, and the priority of a key agent is higher than that of a non-key agent. Then, protocols corresponding to different agent priorities are set. For example, the higher the priority of the agent, the greater the throughput and the lower the transmission delay of the corresponding protocol. Therefore, after obtaining the priority of the agent, the corresponding protocol is matched according to the priority of the agent, and the matched protocol is used as the communication protocol.

[0050] In a specific example, at least one protocol is selected from the multiple initial protocols as the communication protocol according to the priority of the data transmitted by the agents in the communication topology. First, according to the importance of the data transmitted by the agents, corresponding priorities are assigned to the data. For example, the priority of decision-making and fault data is higher than that of daily monitoring data. Then, protocols corresponding to different data priorities are set. For example, the higher the priority of the data, the greater the throughput and the lower the transmission delay of the corresponding protocol. Therefore, after obtaining the priority of the data, the corresponding protocol is matched according to the priority of the data, and the matched protocol is used as the communication protocol.

[0051] In a specific example, at least one protocol is selected from multiple initial protocols as the communication protocol according to the bandwidth of the communication path. Different communication paths may have different bandwidths. If the bandwidth occupied by the data passing through the communication path is higher than the bandwidth of the communication path itself, there may be problems with transmission failure. Therefore, a protocol with a bandwidth smaller than that of the communication path needs to be selected.

[0052] In other examples, it is also possible to use any combination of two or more of the priority of the agent, the priority of the data transmitted by the agent, and the bandwidth of the communication path as the basis for selecting at least one protocol from multiple initial protocols as the communication protocol. The following takes the selection of at least one protocol from multiple initial protocols as the communication protocol according to the priority of the data transmitted by the agent and the bandwidth of the communication path as an example: If the data priority is high and the bandwidth of the communication path is greater than the preset bandwidth, select the protocol with the maximum throughput and the lowest transmission delay as the communication protocol; If the data priority is high and the bandwidth of the communication path is less than or equal to the preset bandwidth, select the protocol that supports data compression or fragmentation as the communication protocol; If the data priority is low and the bandwidth of the communication path is greater than the preset bandwidth, select the protocol with the lowest power consumption as the communication protocol; If the data priority is low and the bandwidth of the communication path is less than or equal to the preset bandwidth, select the protocol that supports bulk transmission or asynchronous transmission as the communication protocol.

[0053] Based on the obtained communication protocol, the agents in the updated layer use this communication protocol for information interaction. It should be noted that as the priority of the agents in the communication topology or the priority of the data transmitted by the agents changes, the communication protocol corresponding to the layer also changes to achieve dynamic update of the communication protocol corresponding to the layer and ensure timely and stable information interaction between the agents.

[0054] It should also be noted that for multiple layers in the industrial Internet of Things, there is a corresponding relationship between the communication protocols of different layers. The corresponding relationship includes at least one of the following: If there is information interaction between the first layer and the second layer, the communication protocol of the first layer is compatible with the communication protocol of the second layer; If there is no information interaction between the first layer and the second layer, the communication protocol of the first layer is independent of the communication protocol of the second layer; If there is data aggregation between the first layer and the second layer, the communication protocol of the first layer supports conversion to the communication protocol of the second layer.

[0055] Among them, the first level and the second level represent different levels. In actual application scenarios, there may be more than two levels, which are not limited in this embodiment. It can be seen that when using the mapping rule to match the corresponding communication protocol for each level, it is also necessary to consider the association relationship between the first level and the second level. For example, it is necessary to consider whether there are information interactions, data aggregations, etc. The association relationship between different levels is also used as one of the screening conditions for selecting at least one communication protocol from multiple initial protocols, so that the communication protocols between different levels are more coordinated, providing technical support for the collaborative control of the industrial Internet.

[0056] In summary, the implementation principle of the collaborative control method for agents in the industrial Internet of Things in the embodiment of this application is as follows: First, the agents are divided into different levels according to the metadata of the agents, and the levels of the agents are updated and put in. Then, a communication topology structure is constructed based on the agents in the levels. Next, the corresponding communication protocol is obtained by matching according to the communication topology structure in the levels. Finally, the agents in the levels use the obtained communication protocol for information interaction, making the communication protocol more adaptable to the agents in the level, and the internal communication of a single level is more stable and efficient. Further, through the method of level division in this application, the mutual influence between levels can also be reduced, ensuring that the industrial Internet of Things can conduct stable communication.

[0057] Figure 3 is the block diagram of the collaborative control system for agents in the industrial Internet of Things provided by the embodiment of this application. As Figure 3 shown, the collaborative control system for agents in the industrial Internet of Things can specifically include a data acquisition module 301, a data matching module 302, a data processing module 303, a data construction module 304, and a data determination module 305.

[0058] The data acquisition module 301 is used to acquire the metadata of multi-source heterogeneous devices. Among them, a multi-source heterogeneous device is used as an agent, and the metadata of the agent has a corresponding level; The data matching module 302 is used to match the level corresponding to the agent according to the metadata of the agent; The data processing module 303 is used to put each agent into its corresponding level and update the agents included in each level; The data construction module 304 is used to construct a communication topology structure for the updated level according to the agents included in each level. The communication topology structure is composed of nodes and line segments. The nodes are agents, and the line segments are the communication paths between agents; The data determination module 305 is used to map at least one corresponding communication protocol for the communication topology structure in each level by using a preset mapping rule, and the agents included in the same level use the mapped communication protocol for information interaction.

[0059] In an embodiment of the present application, a possible implementation is provided. The data construction module 304 is further configured to determine a central agent, where the central agent is an agent in the updated hierarchy for information interaction with agents in other hierarchies; determine other agents in the updated hierarchy that communicate with the central agent; and establish a communication path between the central agent and other agents that communicate with the central agent to obtain a communication topology structure.

[0060] In an embodiment of the present application, a possible implementation is provided. The data determination module 305 is further configured to obtain a plurality of initial protocols according to the communication topology structure; and select at least one protocol from the plurality of initial protocols as a communication protocol according to the priority of the agents in the communication topology structure and / or the priority of the data transmitted by the agents and / or the bandwidth of the communication path.

[0061] Based on the same inventive concept, an embodiment of the present application further provides an electronic device, including a processor and a memory. A computer program is stored in the memory, and the processor is configured to run the computer program to execute the collaborative control method of the agents in the industrial Internet of Things in any of the above embodiments.

[0062] In an exemplary embodiment, an electronic device is provided, as Figure 4 shown. Figure 4 The electronic device 400 shown includes a processor 401 and a memory 403. Among them, the processor 401 and the memory 403 are connected, such as connected through a bus 402. Optionally, the electronic device 400 may further include a transceiver 404. It should be noted that in practical applications, the transceiver 404 is not limited to one, and the structure of the electronic device 400 does not constitute a limitation to the embodiments of the present application.

[0063] The processor 401 may be a CPU (Central Processing Unit), a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute various exemplary logic blocks, modules, and circuits described in combination with the disclosure of the present application. The processor 401 may also be a combination for implementing a computing function, such as a combination including one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0064] The bus 402 may include a path for transmitting information between the above components. The bus 402 can be a PCI (Peripheral Component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus 402 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 4 only a thick line is used in Figure 4 , but it does not mean that there is only one bus or one type of bus.

[0065] The memory 403 can be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or it can also be an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory), or other optical disc storage, optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), magnetic disk storage media, or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0066] The memory 403 is used to store the computer program code for executing the solution of this application, and is controlled by the processor 401 for execution. The processor 401 is used to execute the computer program code stored in the memory 403 to implement the content shown in the foregoing method embodiments.

[0067] Among them, the electronic device includes but is not limited to: mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Tablet Computers), PMPs (Portable Multimedia Players), in-vehicle terminals (such as in-vehicle navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 4 The shown electronic device is only an example and should not impose any limitations on the functions and usage scopes of the embodiments of this application.

[0068] Based on the same inventive concept, the embodiments of this application also provide a storage medium in which a computer program is stored, where the computer program is set to execute the collaborative control method of the agents in the industrial Internet of Things in any one of the above embodiments when running.

[0069] Those skilled in the art can clearly understand the specific working processes of the above-described systems and modules. For the corresponding processes, reference can be made to the corresponding processes in the foregoing method embodiments. For the sake of brevity, they will not be described in detail here.

[0070] Those of ordinary skill in the art can understand that the technical solution of the present application, in essence, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, which includes a number of program instructions for causing an electronic device (such as a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in the embodiments of the present application when the program instructions are run. The foregoing storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs.

[0071] Alternatively, all or part of the steps of implementing the foregoing method embodiments can be completed by hardware related to program instructions (such as an electronic device such as a personal computer, a server, or a network device). The program instructions can be stored in a computer-readable storage medium. When the program instructions are executed by the processor of the electronic device, the electronic device executes all or part of the steps of the method described in the embodiments of the present application.

[0072] The above embodiments are only used to illustrate the technical solution of the present application, rather than to limit it; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that within the spirit and principle of the present application, they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not cause the corresponding technical solutions to deviate from the protection scope of the present application.

Claims

1. A collaborative control method for agents in the industrial Internet of Things, characterized in that, Including: Obtain metadata of multi-source heterogeneous devices, where one of the multi-source heterogeneous devices serves as an agent, and the metadata of the agent has a corresponding level; Match the level corresponding to the agent according to the metadata of the agent; Place each agent into its corresponding level and update the agents included in each level; For the updated levels, construct a communication topology according to the agents included in each level. The communication topology is composed of nodes and line segments. The nodes are agents, and the line segments are communication paths between agents; Adopt a preset mapping rule to map at least one corresponding communication protocol to the communication topology in each level, and the agents included in the same level use the mapped communication protocol for information interaction.

2. The collaborative control method of agents in the industrial Internet of Things according to claim 1, wherein The constructing a communication topology according to the agents included in each level includes: Determine the central agent in each level. The central agent is the agent in the corresponding level that is used to interact with agents in other levels; Determine other agents in the level that communicate with the central agent; Build a communication path between the central agent and other agents that communicate with the central agent to obtain the communication topology.

3. The collaborative control method of agents in the industrial Internet of Things according to claim 2, characterized in that, The determining the central agent includes: Calculate the communication score of each agent, and the communication score is obtained by weighted calculation of function importance and communication frequency; Select the agent with the highest communication score as the central agent.

4. The collaborative control method of agents in the industrial Internet of Things according to claim 1, characterized in that, The adopting a preset mapping rule to map at least one corresponding communication protocol to the communication topology in each level includes: Obtain multiple initial protocols according to the communication topology; Select at least one protocol from the multiple initial protocols as the communication protocol according to the priority of the agents in the communication topology and / or the priority of the data transmitted by the agents and / or the bandwidth of the communication paths between the agents.

5. The collaborative control method of agents in the industrial Internet of Things according to claim 4, wherein, When selecting at least one protocol from the multiple initial protocols as the communication protocol according to the priority of the data transmitted by the agents in the communication topology and the bandwidth of the communication paths between the agents, the method includes: If the data priority is high and the bandwidth of the communication path is greater than the preset bandwidth, select the initial protocol with the maximum throughput and the lowest transmission delay as the communication protocol; If the data priority is high and the bandwidth of the communication path is less than or equal to the preset bandwidth, select the initial protocol that supports data compression or fragmentation as the communication protocol; If the data priority is low and the bandwidth of the communication path is greater than the preset bandwidth, select the initial protocol with the lowest power consumption as the communication protocol; If the data priority is low and the bandwidth of the communication path is less than or equal to the preset bandwidth, select the initial protocol that supports batch transmission or asynchronous transmission as the communication protocol.

6. The collaborative control method of agents in the industrial Internet of Things according to claim 1, characterized in that The metadata at least includes function role, computing power, geographical location, and transmission protocol. The matching the level corresponding to the agent according to the metadata of the agent includes: Determine the level corresponding to the agent according to any one or a combination of the functional role, computing power, geographical location, and transmission protocol of the agent.

7. The collaborative control method of agents in the industrial Internet of Things according to claim 6, characterized in that, The method further includes: When there are multiple levels in the industrial Internet of Things, there is a corresponding relationship between the communication protocols of different levels, and the corresponding relationship includes at least one of the following: If there is information interaction between the first level and the second level, the communication protocol of the first level is compatible with the communication protocol of the second level; If there is no information interaction between the first level and the second level, the communication protocol of the first level is independent of the communication protocol of the second level; If there is data aggregation between the first level and the second level, the communication protocol of the first level supports conversion to the communication protocol of the second level; wherein, the first level and the second level are used to represent different levels in the industrial Internet of Things.

8. A collaborative control system for agents in an industrial Internet of Things, which is used to execute the collaborative control method for agents in an industrial Internet of Things as described in any one of claims 1-7, characterized in that, Including: A data acquisition module, configured to acquire metadata of multi-source heterogeneous devices, where one of the multi-source heterogeneous devices is used as an agent, and the metadata of the agent has a corresponding level; A data matching module, configured to match the level corresponding to the agent according to the metadata of the agent; A data processing module, configured to place each agent into its corresponding level and update the agents included in each level; A data construction module, configured to construct a communication topology structure for the updated level according to the agents included in each level, the communication topology structure is composed of nodes and line segments, the nodes are agents, and the line segments are communication paths between agents; A data determination module, configured to map at least one corresponding communication protocol to the communication topology structure of each level by using a preset mapping rule, and the agents included in the same level use the mapped communication protocol for information interaction.

9. An electronic device, characterized in that, Including a processor and a memory, wherein, a computer program is stored in the memory, and the processor is configured to run the computer program to execute the method for cooperative control of agents in the industrial Internet of Things according to any one of claims 1-7.

10. A storage medium, characterized in that, A computer program is stored in the storage medium, wherein the computer program is configured to execute the method for cooperative control of agents in the industrial Internet of Things according to any one of claims 1-7 when running.

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