Device automatic discovery method, device, equipment and storage medium

Abstract

The present application relates to the technical field of automatic device discovery, and discloses a method, apparatus, device and storage medium for automatic device discovery. The method includes: obtaining multiple first device automatic discovery requests and building multiple first device discovery network environments; establishing a device data interaction mechanism and creating an initial distributed collaborative device automatic discovery strategy; receiving a pending second device automatic discovery request and matching the second device discovery network environment; performing device automatic discovery and device identification, obtaining multiple target devices and performing device connection, and obtaining an initial device connection topology network; performing device authentication and topology network optimization, obtaining a target device connection topology network and performing device interaction status monitoring and feature extraction, and obtaining a target device monitoring feature set; defining a multi-constraint optimization objective function and performing strategy optimization, and obtaining a target distributed collaborative device automatic discovery strategy. The present application improves the efficiency and reliability of automatic device discovery.

Description

Technical Field

[0001] The present application relates to the technical field of automatic device discovery, and in particular to a method, apparatus, device and storage medium for automatic device discovery. Background Art

[0002] With the advancement of technology and the diversification of devices, the demand for efficient and stable automatic device discovery and network configuration is growing. Device networks need to be able to quickly respond to complex environmental changes and achieve efficient communication and collaboration between devices. However, existing automatic device discovery methods face many challenges, such as the diversity of device types, the complexity of network environments, and strict requirements for data security and network stability, making it difficult for traditional device discovery and network configuration methods to meet the needs of practical applications.

[0003] Traditional device discovery methods usually rely on manual intervention, lack flexibility and intelligence, and are difficult to adapt to changing network environments and device configuration requirements. In addition, traditional methods are also insufficient in terms of device data interaction, network topology optimization, and security assurance. These problems lead to inefficient network configuration, unstable device connections, and security risks in data transmission, which seriously affect the overall performance and reliability of the device network. Summary of the invention

[0004] The present application provides a device automatic discovery method, apparatus, device and storage medium for improving the efficiency and reliability of device automatic discovery.

[0005] In a first aspect, the present application provides a device automatic discovery method, the device automatic discovery method comprising:

[0006] Acquire multiple first device automatic discovery requests, and perform device discovery network environment construction and PWL and P2P protocol configuration on the multiple first device automatic discovery requests to obtain multiple first device discovery network environments;

[0007] Establishing device data interaction mechanisms for the multiple first device discovery network environments respectively, obtaining a device data interaction mechanism for each first device discovery network environment, and creating an initial distributed collaborative device automatic discovery strategy for each first device discovery network environment according to the device data interaction mechanism;

[0008] receiving a second device automatic discovery request to be processed, and matching the second device automatic discovery request according to the multiple first device discovery network environments to obtain a second device discovery network environment for the second device automatic discovery request;

[0009] Performing device automatic discovery and device identification through the initial distributed collaborative device automatic discovery strategy of the second device discovery network environment to obtain multiple target devices, and performing device connection on the multiple target devices to obtain an initial device connection topology network;

[0010] Based on the initial device connection topology network, device authentication and topology network optimization are performed on the multiple target devices to obtain a target device connection topology network, and device interaction status monitoring and feature extraction are performed on the multiple target devices according to the target device connection topology network to obtain a target device monitoring feature set;

[0011] A multi-constraint optimization objective function is defined according to the target device monitoring feature set through a preset HSSA algorithm, and the initial distributed collaborative device automatic discovery strategy is optimized according to the multi-constraint optimization objective function to obtain the target distributed collaborative device automatic discovery strategy.

[0012] In a second aspect, the present application provides a device automatic discovery apparatus, the device automatic discovery apparatus comprising:

[0013] An acquisition module, used to acquire multiple first device automatic discovery requests, and to build a device discovery network environment and configure PWL and P2P protocols for the multiple first device automatic discovery requests to obtain multiple first device discovery network environments;

[0014] A creation module, used to establish a device data interaction mechanism for each of the multiple first device discovery network environments, obtain a device data interaction mechanism for each first device discovery network environment, and create an initial distributed collaborative device automatic discovery strategy for each first device discovery network environment according to the device data interaction mechanism;

[0015] A matching module, configured to receive a second device automatic discovery request to be processed, and match the second device automatic discovery request according to the plurality of first device discovery network environments to obtain a second device discovery network environment for the second device automatic discovery request;

[0016] an identification module, configured to perform automatic device discovery and device identification through an initial distributed collaborative device automatic discovery strategy of the second device discovery network environment, obtain a plurality of target devices, and perform device connection on the plurality of target devices to obtain an initial device connection topology network;

[0017] A monitoring module, configured to perform device authentication and topology network optimization on the multiple target devices based on the initial device connection topology network to obtain a target device connection topology network, and perform device interaction status monitoring and feature extraction on the multiple target devices according to the target device connection topology network to obtain a target device monitoring feature set;

[0018] The optimization module is used to define a multi-constraint optimization objective function according to the target device monitoring feature set through a preset HSSA algorithm, and optimize the initial distributed collaborative device automatic discovery strategy according to the multi-constraint optimization objective function to obtain the target distributed collaborative device automatic discovery strategy.

[0019] The third aspect of the present application provides a device automatic discovery device, comprising: a memory and at least one processor, wherein the memory stores instructions; the at least one processor calls the instructions in the memory so that the device automatic discovery device executes the above-mentioned device automatic discovery method.

[0020] A fourth aspect of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores instructions, which, when executed on a computer, enable the computer to execute the above-mentioned device automatic discovery method.

[0021] In the technical solution provided by the present application, by obtaining the first device automatic discovery request, and performing detailed parsing and matching calculation on these requests, accurate identification of device type, required bandwidth and protocol preference is achieved. Through the analysis of the request information set and the calculation of the matching degree of the first request, the method can dynamically build a network environment that adapts to the needs of various devices, and perform PWL and P2P protocol configuration. This dynamic construction and configuration mechanism enables the network to flexibly adapt to the access of various devices and different network conditions, thereby improving the adaptability and scalability of the network. Not only is the data transmission, encryption and decryption, and error handling mechanism established in the initial stage, but the interaction mechanism is continuously optimized through the preset data transmission efficiency model and communication delay evaluation model. This ensures efficient and secure exchange of data between devices, significantly reduces communication delays, and ensures real-time and data integrity. By analyzing the device data interaction mechanism, an initial distributed collaborative device automatic discovery strategy is constructed. The introduction of this strategy enables devices to automatically discover and identify based on real-time network environment and device status, improving the self-organizing ability and self-adaptive ability of the network. By introducing the preset HSSA algorithm, this method defines an accurate multi-constraint optimization objective function based on the target device monitoring feature set, and optimizes the automatic discovery strategy on this basis. This algorithm-based optimization not only improves network performance, but also maximizes resource utilization, thereby improving the efficiency and reliability of device automatic discovery. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0023] Figure 1 A schematic diagram of an embodiment of a method for automatic device discovery in an embodiment of the present application;

[0024] Figure 2 This is a schematic diagram of an embodiment of a device automatic discovery apparatus in an embodiment of the present application. DETAILED DESCRIPTION

[0025] The embodiments of the present application provide a method, apparatus, device and storage medium for automatic device discovery. The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments described here can be implemented in an order other than that illustrated or described here. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0026] For ease of understanding, the specific process of the embodiment of the present application is described below. Figure 1 , an embodiment of the device automatic discovery method in the embodiment of the present application includes:

[0027] Step S101: Acquire multiple first device automatic discovery requests, and perform device discovery network environment construction and PWL and P2P protocol configuration on the multiple first device automatic discovery requests to obtain multiple first device discovery network environments;

[0028] It is understandable that the execution subject of the present application may be a device automatic discovery apparatus, or a terminal or a server, which is not limited here. The present application embodiment is described by taking a server as the execution subject as an example.

[0029] Specifically, multiple first device automatic discovery requests are obtained from a historical database. Request parsing is performed on each first device automatic discovery request. The request parsing process includes identifying and extracting key information in the request, such as device type, required bandwidth, and protocol preference information, etc. These information sets constitute the request information set of each device automatic discovery request. The first request matching degree is calculated for each first device automatic discovery request according to the request information set. The compatibility and adaptability between the request information and the existing network resources, protocol support, and bandwidth requirements are analyzed. The first request matching degree is calculated to effectively guide the subsequent network capacity demand analysis and the establishment of the device discovery network environment. For example, for requests with high matching degree, the existing network resources can be given priority, while for requests with low matching degree, more network resource configuration or adjustment is required. Based on the first request matching degree, network capacity demand analysis and the establishment of the device discovery network environment are performed. According to the specific requirements of each request, such as the required bandwidth, device type, and protocol preference, an initial device discovery network environment is designed. This environment not only needs to meet the current device discovery requirements, but also should consider future scalability and flexibility. Based on the established initial device discovery network environment, configure the PWL and P2P protocols for each first device automatic discovery request. The PWL protocol involves network-level optimization, while the P2P protocol focuses more on the efficiency and reliability of point-to-point communication. When configuring these protocols, you need to consider the device type, network environment, and previously calculated request matching to ensure that the resulting device discovery network environment is both efficient and reliable.

[0030] Step S102: Establish device data interaction mechanisms for multiple first device discovery network environments respectively, obtain the device data interaction mechanism for each first device discovery network environment, and create an initial distributed collaborative device automatic discovery strategy for each first device discovery network environment according to the device data interaction mechanism;

[0031] Specifically, a device data interaction mechanism is established for each of the multiple first device discovery network environments to ensure that devices in different network environments can effectively exchange data. The establishment of the initial data interaction mechanism includes three core parts: data transmission mechanism, encryption and decryption mechanism, and error handling mechanism. The data transmission mechanism focuses on how to efficiently and stably transmit data between devices, which involves the format design of data packets, the selection of transmission protocols, etc. The encryption and decryption mechanism is the key to ensuring data security. It needs to minimize the impact on transmission efficiency while ensuring data security. The design of the error handling mechanism is to ensure that when errors occur during data transmission, the system can promptly discover and take measures to ensure the reliability of the entire data interaction process. These mechanisms are optimized through the preset data transmission efficiency model and communication delay evaluation model to improve the efficiency and reliability of data interaction. The data transmission efficiency model predicts the optimal path and method of data transmission based on factors such as network environment and device characteristics, while the communication delay evaluation model helps understand the delays and potential bottlenecks encountered in data transmission under different network conditions. Through the analysis and calculation of the model, the initial data interaction mechanism is finely adjusted and optimized to ensure that the best data interaction effect can be achieved in various network environments. According to the optimized device data interaction mechanism, a corresponding device automatic discovery strategy is constructed for each first device to discover the network environment, so as to realize efficient and collaborative automatic discovery between devices in a distributed environment. When constructing the strategy, it is necessary to comprehensively consider factors such as the characteristics of the network environment, the device type, and the needs of data interaction. For example, in a network environment with high data transmission efficiency, the automatic discovery strategy can focus more on quickly identifying and connecting new devices; in scenarios with high data security requirements, it is necessary to emphasize the importance of encryption and decryption mechanisms.

[0032] Step S103: receiving a second device automatic discovery request to be processed, and matching the second device automatic discovery request according to a plurality of first device discovery network environments to obtain a second device discovery network environment of the second device automatic discovery request;

[0033] Specifically, receive the automatic discovery request of the second device to be processed, and analyze the specific content of the request, such as device type, network requirements, communication protocol preferences, etc. This information is a key factor in the matching process and directly affects the performance and compatibility of the second device in a specific network environment. Compare and match the request with multiple existing automatic discovery requests of the first device. According to the characteristics of the automatic discovery request of the second device, such as the required bandwidth, data transmission rate, security requirements, etc., compare with the characteristics of each automatic discovery request of the first device. The comparison is completed based on a series of predefined evaluation criteria and algorithms, and its purpose is to quantify the fitness of each match, that is, the second request matching degree. This matching degree is a key indicator to determine which network environment the second device will eventually join. According to the calculated second request matching degree, select the first device discovery network environment corresponding to the first device automatic discovery request with the highest matching degree as the target network environment for the second device automatic discovery request. The second device will be integrated into the network that best matches its characteristics and requirements, ensuring that it can obtain the best performance and the highest compatibility in the network environment. This process not only improves the efficiency of automatic discovery, but also ensures the stability of the network environment and the reliability of the device.

[0034] Step S104: perform device automatic discovery and device identification through the initial distributed collaborative device automatic discovery strategy of the second device discovery network environment, obtain multiple target devices, and perform device connection on the multiple target devices to obtain an initial device connection topology network;

[0035] Specifically, the device automatic discovery is performed through the initial distributed collaborative device automatic discovery strategy of the second device discovery network environment. The distributed structure in the network is used to efficiently identify and locate potential candidate devices, including known devices, newly added devices or previously unidentified devices. In this process, the topology of the network, the communication protocol of the device and the performance parameters of the network are comprehensively considered to ensure that all candidate devices can be detected comprehensively and accurately. The candidate devices are identified and the characteristics of each candidate device are analyzed, such as device type, manufacturer information, operating status and compatibility with the network. The technologies used in the identification process include device fingerprint identification, network protocol analysis and hardware feature detection. Based on the device identification results of each candidate device, further device screening is performed to determine which devices are target devices that meet the current network requirements and compatibility requirements. The screening process is based not only on the technical characteristics of the device, but also on the device's usage history, maintenance records and performance indicators. Device connection and device connection status detection are performed on multiple target devices. A communication connection is established with each target device, and it is ensured that these connections are stable and reliable. The device connection status detection is to verify the quality of each connection, including communication delay, data packet loss rate and bandwidth utilization. Ensure that all target devices are not only identified and added to the network, but also ensure that their connections meet network performance requirements. Create the corresponding initial device connection topology network based on device connection status information and all target devices. The topology network is designed to take into account the geographical location, functional role and network resource usage of each device, aiming to optimize the performance and reliability of the entire network.

[0036] Step S105: performing device authentication and topology network optimization on multiple target devices based on the initial device connection topology network to obtain a target device connection topology network, and performing device interaction state monitoring and feature extraction on multiple target devices according to the target device connection topology network to obtain a target device monitoring feature set;

[0037] Specifically, multiple target devices are authenticated based on the initial device connection topology network, and unauthorized access and potential network attacks are prevented by verifying the identity and permissions of each target device. The device authentication success rate of each target device becomes an important indicator for measuring network security. The authentication process involves a variety of technical means, including digital certificates, cryptographic verification, and biometrics. The initial device connection topology network is optimized according to the device authentication success rate to improve the overall performance and reliability of the network, while ensuring smooth connection and interaction of all devices. In this process, it is necessary to reconfigure the network path, adjust the distribution of network nodes, or add redundant connections to improve the robustness of the network. The real-time performance data of the network, such as transmission delay, data packet loss rate, and network load, will also be taken into account during the optimization process to ensure that the optimization measures can solve the problems in the network in a targeted manner. Through the optimization measures, the target device connection topology network formed will be more efficient and secure, and can adapt to various complex and changing network environments. Further, the device interaction status of multiple target devices is monitored to track and evaluate the performance and behavior of each target device in the network in real time, including the communication frequency, data transmission volume, and connection stability of the device. Extract features from the device interaction status data of each target device to form a target device monitoring feature set. Extract the most valuable and representative information from a large amount of monitoring data, such as device response time, failure frequency, and service quality. These features not only reflect the performance and status of each device, but also provide guidance for subsequent network adjustments and device maintenance.

[0038] Step S106: define a multi-constraint optimization objective function according to the target device monitoring feature set through a preset HSSA algorithm, and optimize the initial distributed collaborative device automatic discovery strategy according to the multi-constraint optimization objective function to obtain the target distributed collaborative device automatic discovery strategy.

[0039] Specifically, a multi-constraint optimization objective function is defined according to the target device monitoring feature set through a preset HSSA algorithm. The purpose of the function is to find the most optimized device automatic discovery strategy under the premise of satisfying a series of constraints. These constraints include network bandwidth utilization, device discovery time, system energy consumption, and network stability. The objective function determines the direction and effect of the optimization process. The initial distributed collaborative device automatic discovery strategy is initialized by the HSSA algorithm to generate multiple first distributed collaborative device automatic discovery strategies. A series of device discovery strategies are designed according to the current state of the network and the characteristics of the device. Each strategy is a variation or adjustment of the initial strategy, aiming to explore a more efficient device discovery method. In this process, the role of the HSSA algorithm is to ensure the diversity and comprehensiveness of the strategy initialization, so as to provide a wider selection space for subsequent optimization. Then, the optimization target value of each first distributed collaborative device automatic discovery strategy is calculated separately through the multi-constraint optimization objective function. The performance of each strategy will be evaluated under multiple constraints, such as whether the strategy will cause excessive network load or increased energy consumption while improving the device discovery speed. In this way, the comprehensive effect of each strategy is quantified, thereby providing a clear evaluation standard for the subsequent strategy optimization. The multiple first distributed collaborative device automatic discovery strategies are further optimized according to the optimization target value to generate multiple second distributed collaborative device automatic discovery strategies. The optimization process includes eliminating poorly performing strategies, combining or mutating better performing strategies, and introducing new strategy elements to explore more effective solutions. This stage is a dynamic adjustment process that continuously optimizes and improves existing strategies to find the best device automatic discovery method. The second distributed collaborative device automatic discovery strategy is solved for the optimal strategy to obtain the final target distributed collaborative device automatic discovery strategy. The solution process takes into account all strategy combinations and mutations to ensure that the final target strategy not only meets all constraints, but also achieves the optimal device discovery efficiency and network performance.

[0040] In the embodiment of the present application, by obtaining the first device automatic discovery request, and performing detailed parsing and matching calculation on these requests, accurate identification of device type, required bandwidth and protocol preference is achieved. Through the analysis of the request information set and the calculation of the matching degree of the first request, the method can dynamically build a network environment that adapts to the needs of various devices, and perform PWL and P2P protocol configuration. This dynamic construction and configuration mechanism enables the network to flexibly adapt to the access of various devices and different network conditions, thereby improving the adaptability and scalability of the network. Not only is the data transmission, encryption and decryption and error handling mechanism established in the initial stage, but the interaction mechanism is continuously optimized through the preset data transmission efficiency model and communication delay evaluation model. This ensures efficient and secure exchange of data between devices, significantly reduces communication delays, and ensures real-time and data integrity. By analyzing the device data interaction mechanism, an initial distributed collaborative device automatic discovery strategy is constructed. The introduction of this strategy enables devices to automatically discover and identify based on real-time network environment and device status, improving the self-organizing ability and adaptive ability of the network. By introducing the preset HSSA algorithm, this method defines an accurate multi-constraint optimization objective function based on the target device monitoring feature set, and optimizes the automatic discovery strategy on this basis. This algorithm-based optimization not only improves network performance, but also maximizes resource utilization, thereby improving the efficiency and reliability of device automatic discovery.

[0041] In a specific embodiment, the process of executing step S101 may specifically include the following steps:

[0042] (1) obtaining a plurality of first device automatic discovery requests from a historical database, and respectively parsing the plurality of first device automatic discovery requests to obtain a request information set of each first device automatic discovery request, wherein the request information set includes: device type, required bandwidth, and protocol preference information;

[0043] (2) calculating a first request matching degree for a plurality of first device automatic discovery requests according to the request information set, and obtaining a first request matching degree for each first device automatic discovery request;

[0044] (3) performing network capacity demand analysis and device discovery network environment construction for multiple first device automatic discovery requests according to the first request matching degree, and obtaining an initial device discovery network environment for each first device automatic discovery request;

[0045] (4) Based on the initial device discovery network environment, PWL and P2P protocol configurations are performed on the multiple first device automatic discovery requests respectively to obtain multiple first device discovery network environments.

[0046] Specifically, multiple first device automatic discovery requests are obtained from the historical database, and each first device automatic discovery request is parsed. For example, the device type, required bandwidth, and protocol preference, etc., these information sets constitute the request information set. According to the request information set, the first request matching degree is calculated to evaluate the matching degree between each request and the existing network resources and capabilities. In this process, various factors are considered, such as the current load of the network, the available bandwidth, the supported protocol type, etc. The calculation result of the matching degree affects the subsequent network capacity demand analysis and the establishment of the device discovery network environment. The network capacity demand analysis aims to determine the network resources that need to be added or reconfigured to meet these requests, while the establishment of the device discovery network environment is to actually build a network environment that can support the discovery of these devices. For example, if the request matching degree of the video conferencing system is high, then the establishment of the network environment will include increasing the network bandwidth for video transmission and configuring a router that supports the real-time transport protocol. Based on the initial device discovery network environment, the PWL and P2P protocol configurations are performed on multiple first device automatic discovery requests respectively. A suitable network protocol configuration is customized for each device automatic discovery request to optimize the connection and communication efficiency of the device. For example, configuring the P2P protocol to enable direct video data transmission between devices, and optimizing the PWL protocol to support more efficient data processing.

[0047] In a specific embodiment, the process of executing step S102 may specifically include the following steps:

[0048] (1) establishing a device data interaction mechanism for each of the plurality of first device discovery network environments to obtain an initial data interaction mechanism for each first device discovery network environment, wherein the initial data interaction mechanism includes: a data transmission mechanism, an encryption and decryption mechanism, and an error handling mechanism;

[0049] (2) Optimizing the initial data interaction mechanism through a preset data transmission efficiency model and a communication delay evaluation model to obtain a device data interaction mechanism for each first device to discover the network environment;

[0050] (3) According to the device data interaction mechanism, a device automatic discovery strategy is constructed for each first device discovery network environment respectively, and an initial distributed collaborative device automatic discovery strategy is obtained for each first device discovery network environment.

[0051] Specifically, an initial data interaction mechanism is established for each first device to discover the network environment. This includes three main parts: data transmission mechanism, encryption and decryption mechanism, and error handling mechanism. The data transmission mechanism is responsible for defining the data exchange method between devices, such as selecting TCP or UDP protocol, setting the appropriate data packet size, and determining the frequency and priority of data transmission. The encryption and decryption mechanism ensures the security of data transmission, which involves using SSL / TLS protocol for encrypted communication, or using more advanced encryption algorithms such as AES to protect data. The role of the error handling mechanism is to timely discover and correct errors during data transmission, which includes retransmission mechanism, checksum calculation or fault recovery strategy. The initial data interaction mechanism is optimized through the preset data transmission efficiency model and communication delay evaluation model. The data transmission efficiency model can help the system evaluate the efficiency of different data transmission methods in a specific network environment, such as which data packet size is most suitable during high traffic periods. The communication delay evaluation model is used to predict the delay under different data transmission strategies to help the system select the optimal data transmission path and method. For example, optimization involves adjusting the frequency of data transmission to reduce network congestion and delay, or changing the parameters of the encryption algorithm to increase the data processing speed while ensuring security. According to the optimized device data interaction mechanism, a corresponding device automatic discovery strategy is constructed for each first device to discover the network environment. This strategy needs to comprehensively consider the characteristics of the network, the type of device, and the needs of data interaction to achieve efficient and stable automatic device discovery. For example, for devices that require frequent data updates, such as sensors or surveillance cameras, a more flexible and fast automatic discovery mechanism is designed, while for devices that do not require so frequent data interaction, a more stable discovery strategy with a longer response time can be adopted.

[0052] In a specific embodiment, the process of executing step S103 may specifically include the following steps:

[0053] (1) receiving a second device automatic discovery request to be processed, and calculating a request matching degree for the second device automatic discovery request and a plurality of first device automatic discovery requests to obtain a second request matching degree between the second device automatic discovery request and each first device automatic discovery request;

[0054] (2) The first device discovery network environment corresponding to the first device automatic discovery request with the highest matching degree with the second request is used as the second device discovery network environment for the second device automatic discovery request.

[0055] Specifically, a pending second device automatic discovery request is received, and the information contained in the second device automatic discovery request is accurately understood and analyzed. This information includes the type of device, the required network characteristics, the data transmission requirements, etc. For example, a second device automatic discovery request comes from a newly added smart temperature control device, and the request includes information such as the type of device (smart temperature control), the required data transmission frequency and the bandwidth requirement. The request matching degree is calculated for the second device automatic discovery request and the existing multiple first device automatic discovery requests to evaluate the compatibility of the new device with the existing network environment. According to the characteristics of the second device request, such as data transmission requirements, protocol preferences, bandwidth requirements, etc., it is compared with the characteristics of the network environment corresponding to the existing first device discovery request. For example, consider whether the existing network environment can support the data transmission frequency of the smart device, whether there is enough bandwidth to meet its data requirements, and whether it supports the required communication protocol. Through comparison and evaluation, the matching degree between the second device automatic discovery request and each first device automatic discovery request is calculated. The matching degree is a quantitative indicator that reflects the degree of compatibility between the new device and the existing network environment. The first device discovery network environment corresponding to the first device automatic discovery request with the highest matching degree is selected as the target network environment for the second device automatic discovery request.

[0056] In a specific embodiment, the process of executing step S104 may specifically include the following steps:

[0057] (1) Performing device automatic discovery by using an initial distributed collaborative device automatic discovery strategy of a second device discovery network environment to obtain multiple candidate devices;

[0058] (2) performing device identification on multiple candidate devices to obtain a device identification result for each candidate device, and performing device screening on the multiple candidate devices according to the device identification result to obtain multiple target devices;

[0059] (3) Perform device connection and device connection status detection on multiple target devices to obtain device connection status information of each target device;

[0060] (4) Create a corresponding initial device connection topology network based on the device connection status information and multiple target devices.

[0061] Specifically, the automatic discovery of devices is performed through the initial distributed collaborative device automatic discovery strategy. The distributed characteristics of the network are used to explore and identify new devices in the network environment. This includes analyzing network traffic, responding to device discovery requests, or using other automatic discovery technologies. Multiple candidate devices are identified, including analyzing the characteristics of the devices, such as device type, supported functions, network compatibility, etc. The results of the identification will be used in the subsequent device screening process to determine which devices are target devices that meet the needs of the current network environment. Multiple candidate devices are screened and the target devices are determined based on the compatibility, functional requirements, and network environment requirements of the devices. The target devices are connected and the connection status is detected. This includes establishing network connections between devices and evaluating the quality of these connections, such as stability, data transmission rate, etc. The purpose of connection status detection is to ensure that the connection between devices is reliable and efficient. Based on the connection status information of the devices, the corresponding initial device connection topology network is created. The topology network takes into account the location, connection type, and data flow pattern of each device in the network, with the goal of optimizing the performance and efficiency of the entire network. The network design process is dynamic and is adjusted according to the real-time changes in the connection status of the devices and the network environment.

[0062] In a specific embodiment, the process of executing step S105 may specifically include the following steps:

[0063] (1) Perform device authentication on multiple target devices based on the initial device connection topology network, and obtain the device authentication success rate of each target device;

[0064] (2) Optimize the initial device connection topology network according to the device authentication success rate to obtain the target device connection topology network;

[0065] (3) Monitor the device interaction status of multiple target devices according to the target device connection topology network to obtain the device interaction status data of each target device;

[0066] (4) Perform feature extraction on the device interaction status data of each target device to obtain a target device monitoring feature set.

[0067] Specifically, multiple target devices are authenticated based on the initial device connection topology network. Ensure the correctness of the identity and permissions of each device in the network to avoid unauthorized access or potential network threats. During the device authentication process, various security mechanisms, such as digital certificates, password verification or biometrics, are used to verify the legitimacy of each device. Through the authentication process, the device authentication success rate of each device is calculated. For example, if the authentication of a device fails multiple times, it means that there is a security risk and further inspection and processing are required. According to the device authentication success rate, the initial device connection topology network is optimized to obtain the target device connection topology network. The security and efficiency of the entire network are improved by adjusting the network structure and configuration. Network optimization includes reconfiguring the network path, adjusting the network node distribution or adding redundant connections to improve the robustness of the network. For example, if it is found that the device authentication success rate in certain areas is low, it is necessary to enhance the security measures in those areas or adjust the network layout to avoid potential security risks. The device interaction status of multiple target devices is monitored based on the target device connection topology network. This includes monitoring and recording information such as communication behavior, data transmission efficiency and connection stability between devices. For example, through monitoring, it can be found that the communication delay of certain devices is abnormal, or the data transmission is frequently interrupted. Perform feature extraction on the device interaction status data of each target device. Extract the most valuable and representative information from a large amount of monitoring data, which reflects the operating status of the device and the performance of the network. Feature extraction includes analyzing key indicators such as the frequency, stability, and response time of device communication. For example, through feature extraction, identify which devices participate in data exchange more frequently, which devices play a key role in the network, or which devices have performance problems. These extracted features constitute the target device monitoring feature set, which provides an important decision-making basis for network management.

[0068] In a specific embodiment, the process of executing step S106 may specifically include the following steps:

[0069] (1) Define a multi-constraint optimization objective function based on the monitoring feature set of the target device through the preset HSSA algorithm;

[0070] (2) Initializing the initial distributed collaborative device automatic discovery strategy through the HSSA algorithm to generate multiple first distributed collaborative device automatic discovery strategies;

[0071] (3) calculating the optimization target value of each first distributed collaborative device automatic discovery strategy respectively through a multi-constraint optimization objective function;

[0072] (4) Optimizing the plurality of first distributed collaborative device automatic discovery strategies according to the optimization target value to generate a plurality of second distributed collaborative device automatic discovery strategies;

[0073] (5) Optimizing the strategy for the multiple second distributed collaborative device automatic discovery strategies to obtain the target distributed collaborative device automatic discovery strategy.

[0074] Specifically, a multi-constraint optimization objective function is defined according to a set of monitoring features of a target device through a preset HSSA algorithm, and the optimization objective of the automatic discovery process of devices in the network is quantified, while taking into account a series of constraints. These constraints include the efficiency of network bandwidth utilization, the response time of device discovery, the energy consumption of the system, and the stability of the network. The initial distributed collaborative device automatic discovery strategy is initialized by the HSSA algorithm to generate a series of first distributed collaborative device automatic discovery strategies. The role of the HSSA algorithm is to explore and generate a series of device discovery strategies based on the current state of the network and the characteristics of the device. For example, some strategies focus on quickly discovering new devices, while others focus on reducing the consumption of network resources. The strategy initialization process ensures that different solutions are explored from a wide range of perspectives, providing a rich selection for subsequent optimization. The optimization target value of each first distributed collaborative device automatic discovery strategy is calculated separately through a multi-constraint optimization objective function. The performance of each strategy under multiple constraints is evaluated. Through calculation, the comprehensive effect of each strategy is quantified, thereby providing a clear evaluation criterion for the subsequent strategy optimization. According to the calculated optimization target value, the first distributed collaborative device automatic discovery strategy is further optimized to generate a series of second distributed collaborative device automatic discovery strategies. The optimization process eliminates poorly performing strategies, combines and mutates strategies with better performance, and introduces new strategy elements to explore more effective solutions. For example, if a strategy performs well in quickly discovering new devices but consumes a lot of network resources, the system will adjust it to reduce resource consumption while ensuring discovery speed. The second distributed collaborative device automatic discovery strategy is optimized to obtain the final target distributed collaborative device automatic discovery strategy. The advanced search capability of the HSSA algorithm is used to select the optimal solution from many strategies. All strategy combinations and mutations are comprehensively considered to ensure that the final target strategy achieves the best performance and highest efficiency of device automatic discovery on the basis of satisfying all constraints.

[0075] The above describes the device automatic discovery method in the embodiment of the present application. The following describes the device automatic discovery device in the embodiment of the present application. Figure 2 In the embodiment of the present application, an embodiment of the device automatic discovery device includes:

[0076] The acquisition module 201 is used to acquire multiple first device automatic discovery requests, and to build a device discovery network environment and configure PWL and P2P protocols for the multiple first device automatic discovery requests to obtain multiple first device discovery network environments;

[0077] A creation module 202 is used to establish a device data interaction mechanism for each of the multiple first device discovery network environments, obtain a device data interaction mechanism for each first device discovery network environment, and create an initial distributed collaborative device automatic discovery strategy for each first device discovery network environment according to the device data interaction mechanism;

[0078] A matching module 203 is used to receive a second device automatic discovery request to be processed, and match the second device automatic discovery request according to the multiple first device discovery network environments to obtain a second device discovery network environment for the second device automatic discovery request;

[0079] The identification module 204 is used to perform device automatic discovery and device identification through the initial distributed collaborative device automatic discovery strategy of the second device discovery network environment, obtain multiple target devices, and perform device connection on the multiple target devices to obtain an initial device connection topology network;

[0080] The monitoring module 205 is used to perform device authentication and topology network optimization on the multiple target devices based on the initial device connection topology network to obtain a target device connection topology network, and perform device interaction status monitoring and feature extraction on the multiple target devices according to the target device connection topology network to obtain a target device monitoring feature set;

[0081] The optimization module 206 is used to define a multi-constraint optimization objective function according to the target device monitoring feature set through a preset HSSA algorithm, and optimize the initial distributed collaborative device automatic discovery strategy according to the multi-constraint optimization objective function to obtain the target distributed collaborative device automatic discovery strategy.

[0082] Through the collaboration of the above components, by obtaining the first device automatic discovery request, and performing detailed analysis and matching calculation on these requests, the accurate identification of device type, required bandwidth and protocol preference is achieved. By analyzing the request information set and calculating the matching degree of the first request, the method can dynamically build a network environment that adapts to the needs of various devices and configure PWL and P2P protocols. This dynamic construction and configuration mechanism enables the network to flexibly adapt to the access of various devices and different network conditions, thereby improving the adaptability and scalability of the network. Not only is the data transmission, encryption and decryption, and error handling mechanism established in the initial stage, but the interaction mechanism is continuously optimized through the preset data transmission efficiency model and communication delay evaluation model. This ensures efficient and secure exchange of data between devices, significantly reduces communication delays, and ensures real-time and data integrity. By analyzing the device data interaction mechanism, an initial distributed collaborative device automatic discovery strategy is constructed. The introduction of this strategy enables devices to automatically discover and identify based on real-time network environment and device status, improving the self-organizing and adaptive capabilities of the network. By introducing the preset HSSA algorithm, this method defines an accurate multi-constraint optimization objective function based on the target device monitoring feature set, and optimizes the automatic discovery strategy on this basis. This algorithm-based optimization not only improves network performance, but also maximizes resource utilization, thereby improving the efficiency and reliability of device automatic discovery.

[0083] The present application also provides a device automatic discovery device, which includes a memory and a processor. The memory stores computer-readable instructions. When the computer-readable instructions are executed by the processor, the processor executes the steps of the device automatic discovery method in the above-mentioned embodiments.

[0084] The present application also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium, wherein instructions are stored in the computer, and when the instructions are executed on a computer, the computer executes the steps of the device automatic discovery method.

[0085] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems, systems and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0086] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art 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, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program codes.

[0087] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A device automatic discovery method, characterized in that: The device automatic discovery method comprises: Acquire multiple first device automatic discovery requests, and perform device discovery network environment construction and PWL and P2P protocol configuration on the multiple first device automatic discovery requests to obtain multiple first device discovery network environments; Establishing device data interaction mechanisms for the multiple first device discovery network environments respectively, obtaining a device data interaction mechanism for each first device discovery network environment, and creating an initial distributed collaborative device automatic discovery strategy for each first device discovery network environment according to the device data interaction mechanism; receiving a second device automatic discovery request to be processed, and matching the second device automatic discovery request according to the multiple first device discovery network environments to obtain a second device discovery network environment for the second device automatic discovery request; Performing device automatic discovery and device identification through the initial distributed collaborative device automatic discovery strategy of the second device discovery network environment to obtain multiple target devices, and performing device connection on the multiple target devices to obtain an initial device connection topology network; Based on the initial device connection topology network, device authentication and topology network optimization are performed on the multiple target devices to obtain a target device connection topology network, and device interaction status monitoring and feature extraction are performed on the multiple target devices according to the target device connection topology network to obtain a target device monitoring feature set; A multi-constraint optimization objective function is defined according to the target device monitoring feature set through a preset HSSA algorithm, and the initial distributed collaborative device automatic discovery strategy is optimized according to the multi-constraint optimization objective function to obtain the target distributed collaborative device automatic discovery strategy; specifically, the purpose of the function is to find the most optimized device automatic discovery strategy under the premise of satisfying a series of constraints. These constraints include network bandwidth utilization, device discovery time, system energy consumption and network stability. The objective function determines the direction and effect of the optimization process; the initial distributed collaborative device automatic discovery strategy is initialized through the HSSA algorithm to generate multiple first distributed collaborative device automatic discovery strategies, and a series of device discovery strategies are designed according to the current state of the network and the characteristics of the device. Each device discovery strategy is a variation or adjustment of the initial strategy.

2. The device automatic discovery method according to claim 1, characterized in that: The step of obtaining a plurality of first device automatic discovery requests, and performing device discovery network environment construction and PWL and P2P protocol configuration on the plurality of first device automatic discovery requests to obtain a plurality of first device discovery network environments includes: Acquire multiple first device automatic discovery requests from a historical database, and parse the multiple first device automatic discovery requests respectively to obtain a request information set of each first device automatic discovery request, wherein the request information set includes: device type, required bandwidth, and protocol preference information; Calculating the first request matching degree of the multiple first device automatic discovery requests according to the request information set to obtain the first request matching degree of each first device automatic discovery request; Performing network capacity demand analysis and device discovery network environment construction on the multiple first device automatic discovery requests according to the first request matching degree, to obtain an initial device discovery network environment for each first device automatic discovery request; Based on the initial device discovery network environment, PWL and P2P protocol configurations are performed on the multiple first device automatic discovery requests respectively to obtain multiple first device discovery network environments.

3. The device automatic discovery method according to claim 1, characterized in that: The establishing of device data interaction mechanisms for the multiple first device discovery network environments respectively to obtain the device data interaction mechanism for each first device discovery network environment, and creating an initial distributed collaborative device automatic discovery strategy for each first device discovery network environment according to the device data interaction mechanism, includes: Establishing a device data interaction mechanism for each of the multiple first device discovery network environments to obtain an initial data interaction mechanism for each first device discovery network environment, wherein the initial data interaction mechanism includes: a data transmission mechanism, an encryption and decryption mechanism, and an error handling mechanism; The initial data interaction mechanism is optimized by using a preset data transmission efficiency model and a communication delay evaluation model to obtain a device data interaction mechanism for each first device to discover the network environment; According to the device data interaction mechanism, a device automatic discovery strategy is constructed for each first device discovery network environment respectively, so as to obtain an initial distributed collaborative device automatic discovery strategy for each first device discovery network environment.

4. The device automatic discovery method according to claim 1, characterized in that: The receiving a second device automatic discovery request to be processed, and matching the second device automatic discovery request according to the multiple first device discovery network environments to obtain a second device discovery network environment for the second device automatic discovery request, includes: Receive a second device automatic discovery request to be processed, and calculate a request matching degree for the second device automatic discovery request and the plurality of first device automatic discovery requests to obtain a second request matching degree between the second device automatic discovery request and each first device automatic discovery request; The first device discovery network environment corresponding to the first device automatic discovery request having the highest matching degree with the second request is used as the second device discovery network environment for the second device automatic discovery request.

5. The device automatic discovery method according to claim 1, characterized in that: The method of performing device automatic discovery and device identification through the initial distributed collaborative device automatic discovery strategy of the second device discovery network environment to obtain multiple target devices, and performing device connection on the multiple target devices to obtain an initial device connection topology network includes: Performing device automatic discovery through an initial distributed collaborative device automatic discovery strategy of the second device discovery network environment to obtain a plurality of candidate devices; Performing device identification on the multiple candidate devices to obtain a device identification result of each candidate device, and performing device screening on the multiple candidate devices according to the device identification result to obtain multiple target devices; Performing device connection and device connection status detection on the multiple target devices to obtain device connection status information of each target device; A corresponding initial device connection topology network is created according to the device connection state information and the multiple target devices.

6. The device automatic discovery method according to claim 1, characterized in that: The device authentication and topology network optimization are performed on the multiple target devices based on the initial device connection topology network to obtain a target device connection topology network, and the device interaction status monitoring and feature extraction are performed on the multiple target devices according to the target device connection topology network to obtain a target device monitoring feature set, including: Performing device authentication on the multiple target devices based on the initial device connection topology network to obtain a device authentication success rate for each target device; Performing topology network optimization on the initial device connection topology network according to the device authentication success rate to obtain a target device connection topology network; Monitor the device interaction status of the multiple target devices according to the target device connection topology network to obtain device interaction status data of each target device; Feature extraction is performed on the device interaction status data of each target device to obtain a target device monitoring feature set.

7. The device automatic discovery method according to claim 1, characterized in that: The method of defining a multi-constraint optimization objective function according to the target device monitoring feature set by using a preset HSSA algorithm, and optimizing the initial distributed collaborative device automatic discovery strategy according to the multi-constraint optimization objective function to obtain a target distributed collaborative device automatic discovery strategy includes: Defining a multi-constraint optimization objective function according to the target device monitoring feature set by a preset HSSA algorithm; Initializing the initial distributed collaborative device automatic discovery strategy through the HSSA algorithm to generate a plurality of first distributed collaborative device automatic discovery strategies; Calculate the optimization target value of each first distributed collaborative device automatic discovery strategy respectively through the multi-constraint optimization objective function; Optimizing the plurality of first distributed collaborative device automatic discovery strategies according to the optimization target value to generate a plurality of second distributed collaborative device automatic discovery strategies; An optimization strategy is solved for the multiple second distributed collaborative device automatic discovery strategies to obtain a target distributed collaborative device automatic discovery strategy.

8. A device automatic discovery device, characterized in that: The device automatic discovery device comprises: An acquisition module, used to acquire multiple first device automatic discovery requests, and to build a device discovery network environment and configure PWL and P2P protocols for the multiple first device automatic discovery requests to obtain multiple first device discovery network environments; A creation module, used to establish a device data interaction mechanism for each of the multiple first device discovery network environments, obtain a device data interaction mechanism for each first device discovery network environment, and create an initial distributed collaborative device automatic discovery strategy for each first device discovery network environment according to the device data interaction mechanism; A matching module, configured to receive a second device automatic discovery request to be processed, and match the second device automatic discovery request according to the plurality of first device discovery network environments to obtain a second device discovery network environment for the second device automatic discovery request; an identification module, configured to perform automatic device discovery and device identification through an initial distributed collaborative device automatic discovery strategy of the second device discovery network environment, obtain a plurality of target devices, and perform device connection on the plurality of target devices to obtain an initial device connection topology network; A monitoring module, configured to perform device authentication and topology network optimization on the multiple target devices based on the initial device connection topology network to obtain a target device connection topology network, and perform device interaction status monitoring and feature extraction on the multiple target devices according to the target device connection topology network to obtain a target device monitoring feature set; The optimization module is used to define a multi-constraint optimization objective function according to the target device monitoring feature set through a preset HSSA algorithm, and optimize the initial distributed collaborative device automatic discovery strategy according to the multi-constraint optimization objective function to obtain a target distributed collaborative device automatic discovery strategy; specifically, the purpose of the function is to find the most optimized device automatic discovery strategy under the premise of satisfying a series of constraints. These constraints include network bandwidth utilization, device discovery time, system energy consumption and network stability. The objective function determines the direction and effect of the optimization process; the initial distributed collaborative device automatic discovery strategy is initialized through the HSSA algorithm to generate multiple first distributed collaborative device automatic discovery strategies. According to the current state of the network and the characteristics of the device, a series of device discovery strategies are designed, and each device discovery strategy is a variation or adjustment of the initial strategy.

9. A device automatically discovers a device, characterized in that: The device automatic discovery device comprises: a memory and at least one processor, wherein instructions are stored in the memory; The at least one processor calls the instructions in the memory to enable the device automatic discovery device to perform the device automatic discovery method according to any one of claims 1 to 7.

10. A computer-readable storage medium having instructions stored thereon, characterized in that: When the instructions are executed by the processor, the device automatic discovery method according to any one of claims 1 to 7 is implemented.

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