Data acquisition method, cache data query method, device and related equipment

Abstract

The invention relates to a data acquisition method, a cache data query method, a cache data query device and related equipment. The data acquisition method comprises the following steps: displaying a browsing interface browsed by a target object, and determining a prediction interface set related to the browsing interface and prediction interface data displayed in each prediction interface; sending a pre-sensing request message to a target edge cloud node related to the client, and obtaining a data cache query result for the pre-sensing request message; determining a target interface triggered by the target object from the prediction interface set, and determining a target data identifier of target interface data of the target interface; obtaining a target cache result of the target data identifier from the data cache query result through the target data identifier; and obtaining target interface data through the target cache result, and displaying the target interface data on the target interface. By adopting the method, the data acquisition time can be saved, and the data acquisition efficiency is improved.

Description

Technical Field

[0001] This application relates to the field of data transmission technology, and in particular to a method for data acquisition, a method for cached data retrieval, an apparatus, and related equipment. Background Technology

[0002] With the development of computer technology, edge cloud technology has emerged. This means that edge nodes are located closer to objects or data sources, enabling them to provide services at the nearest point in time. This results in faster network service response times and meets users' edge-side needs in areas such as real-time business operations and security and privacy protection.

[0003] Currently, when an object browses a webpage or application (APP) interface, the client typically performs multiple background operations such as data resource requests. When the server receives a data resource request from the client, if the requested data resource is not present locally, it needs to request the data from the server storing the aforementioned data resource. After retrieving the data resource, the server then sends the requested data resource back to the client. The latency of data resource retrieval depends on the time it takes for the server storing the required data resource to send the data back. Therefore, reducing the time spent on data retrieval is a pressing issue that needs to be addressed. Summary of the Invention

[0004] Therefore, it is necessary to provide a data acquisition method, a method for caching data queries, an apparatus, and related equipment that can reduce data acquisition time and improve data acquisition efficiency in response to the above-mentioned technical problems.

[0005] Firstly, this application provides a method for data acquisition. The method includes:

[0006] Display the browsing interface that the target object is browsing, determine the set of prediction interfaces related to the browsing interface, and the prediction interface data displayed on each prediction interface.

[0007] Send a pre-awareness request message to the target edge cloud node related to the client, and obtain the data cache query results for the pre-awareness request message; the data cache query results shall at least include the cache results corresponding to the data identifier of each prediction interface data;

[0008] Determine the target interface triggered by the target object from the set of predicted interfaces, and determine the target data identifier of the target interface data of the target interface.

[0009] Retrieve the target cache result based on the target data identifier from the data cache query results;

[0010] The target interface data is obtained by retrieving the target cache results and then displayed on the target interface.

[0011] Secondly, this application provides a method for caching data queries. The method is applied to an edge cloud auxiliary node and includes:

[0012] Receive redirected data packets sent by the target edge cloud node; the redirected data packets include at least: a pre-awareness request packet sent by the client to the target edge cloud node;

[0013] Extract the data identifier of each prediction interface from the pre-sensing request message;

[0014] Based on the data identifier of each prediction interface data, data queries are performed on the caching status of each prediction interface data at each edge cloud node to determine the caching result corresponding to the data identifier of each prediction interface data, and data cache query results are constructed.

[0015] Send the cached query results to the target edge cloud node so that the target edge cloud node can return the cached query results to the client.

[0016] Thirdly, this application also provides a data acquisition device. The device is deployed on a client side and includes:

[0017] The interface data processing module is used to display the browsing interface that the target object is browsing, determine the set of prediction interfaces related to the browsing interface, and display the prediction interface data in each prediction interface.

[0018] The cache query result acquisition module is used to send a pre-sensing request message to the target edge cloud node related to the client and acquire the data cache query result for the pre-sensing request message; the data cache query result includes at least the cache result corresponding to the data identifier of each prediction interface data;

[0019] The interface data determination module is used to determine the target interface triggered by the target object from the predicted interface set, and to determine the target data identifier of the target interface data of the target interface.

[0020] The cache result retrieval module is used to retrieve the target cache result of the target data identifier from the data cache query results.

[0021] The data acquisition module is used to obtain target interface data through target cache results and display the target interface data on the target interface.

[0022] Fourthly, this application also provides a cached data query apparatus. The apparatus includes:

[0023] The data packet receiving module is used to receive redirected data packets sent by the target edge cloud node; the redirected data packet includes at least: a pre-awareness request packet sent by the client to the target edge cloud node;

[0024] The data identifier extraction module is used to extract the data identifier of each prediction interface data from the pre-sensing request message.

[0025] The cached data query module is used to query the cache status of each prediction interface data on each edge cloud node based on the data identifier of each prediction interface data, determine the cache result corresponding to the data identifier of each prediction interface data, and construct the data cache query result.

[0026] The cached result feedback module is used to send the cached query results to the target edge cloud node, so that the target edge cloud node can feed back the cached query results to the client.

[0027] Fifthly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to perform the following steps:

[0028] Display the browsing interface that the target object is browsing, determine the set of prediction interfaces related to the browsing interface, and the prediction interface data displayed on each prediction interface.

[0029] Send a pre-awareness request message to the target edge cloud node related to the client, and obtain the data cache query results for the pre-awareness request message; the data cache query results shall at least include the cache results corresponding to the data identifier of each prediction interface data;

[0030] Determine the target interface triggered by the target object from the set of predicted interfaces, and determine the target data identifier of the target interface data of the target interface.

[0031] Retrieve the target cache result based on the target data identifier from the data cache query results;

[0032] The target interface data is obtained by retrieving the target cache results and then displayed on the target interface.

[0033] Sixthly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to perform the following steps:

[0034] Receive redirected data packets sent by the target edge cloud node; the redirected data packets include at least: a pre-awareness request packet sent by the client to the target edge cloud node;

[0035] Extract the data identifier of each prediction interface from the pre-sensing request message;

[0036] Based on the data identifier of each prediction interface data, data queries are performed on the caching status of each prediction interface data at each edge cloud node to determine the caching result corresponding to the data identifier of each prediction interface data, and data cache query results are constructed.

[0037] Send the cached query results to the target edge cloud node so that the target edge cloud node can return the cached query results to the client.

[0038] Seventhly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, performs the following steps:

[0039] Display the browsing interface that the target object is browsing, determine the set of prediction interfaces related to the browsing interface, and the prediction interface data displayed on each prediction interface.

[0040] Send a pre-awareness request message to the target edge cloud node related to the client, and obtain the data cache query results for the pre-awareness request message; the data cache query results shall at least include the cache results corresponding to the data identifier of each prediction interface data;

[0041] Determine the target interface triggered by the target object from the set of predicted interfaces, and determine the target data identifier of the target interface data of the target interface.

[0042] Retrieve the target cache result based on the target data identifier from the data cache query results;

[0043] The target interface data is obtained by retrieving the target cache results and then displayed on the target interface.

[0044] Eighthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, performs the following steps:

[0045] Receive redirected data packets sent by the target edge cloud node; the redirected data packets include at least: a pre-awareness request packet sent by the client to the target edge cloud node;

[0046] Extract the data identifier of each prediction interface from the pre-sensing request message;

[0047] Based on the data identifier of each prediction interface data, data queries are performed on the caching status of each prediction interface data at each edge cloud node to determine the caching result corresponding to the data identifier of each prediction interface data, and data cache query results are constructed.

[0048] Send the cached query results to the target edge cloud node so that the target edge cloud node can return the cached query results to the client.

[0049] Ninthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, performs the following steps:

[0050] Display the browsing interface that the target object is browsing, determine the set of prediction interfaces related to the browsing interface, and the prediction interface data displayed on each prediction interface.

[0051] Send a pre-awareness request message to the target edge cloud node related to the client, and obtain the data cache query results for the pre-awareness request message; the data cache query results shall at least include the cache results corresponding to the data identifier of each prediction interface data;

[0052] Determine the target interface triggered by the target object from the set of predicted interfaces, and determine the target data identifier of the target interface data of the target interface.

[0053] Retrieve the target cache result based on the target data identifier from the data cache query results;

[0054] The target interface data is obtained by retrieving the target cache results and then displayed on the target interface.

[0055] Tenthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, performs the following steps:

[0056] Receive redirected data packets sent by the target edge cloud node; the redirected data packets include at least: a pre-awareness request packet sent by the client to the target edge cloud node;

[0057] Extract the data identifier of each prediction interface from the pre-sensing request message;

[0058] Based on the data identifier of each prediction interface data, data queries are performed on the caching status of each prediction interface data at each edge cloud node to determine the caching result corresponding to the data identifier of each prediction interface data, and data cache query results are constructed.

[0059] Send the cached query results to the target edge cloud node so that the target edge cloud node can return the cached query results to the client.

[0060] The aforementioned data acquisition method, cached data query method, apparatus, computer equipment, storage medium, and computer program product, through the client displaying the browsing interface that the target object is browsing, determine the set of predicted interfaces related to the browsing interface, as well as the predicted interface data displayed on each predicted interface, then send a pre-awareness request message to the target edge cloud node related to the client, and obtain the data cache query result for the pre-awareness request message. The data cache query result includes at least the cache result corresponding to the data identifier of each predicted interface data. That is, before browsing and displaying the interface data, the predicted interface data that may need to be displayed is predicted, and the node where each predicted interface data is cached is determined through data cache query. Based on this, the target interface triggered by the target object is determined from the set of predicted interfaces, and the target data identifier of the target interface data is determined. Through the target data identifier, the target cache result of the target data identifier is obtained from the data cache query results. Since the target interface belongs to the set of predicted interfaces, that is, the data cache query results obtained in advance already record the data cache results and acquisition methods for the target interface. Therefore, the target interface data is obtained through the target cache results and displayed on the target interface. By using the data cache query results obtained in advance for a more accurate and targeted data acquisition method, it is possible to avoid repeatedly making data requests to different edge cloud nodes, thereby saving data acquisition time and improving data acquisition efficiency. Attached Figure Description

[0061] Figure 1 This is an application environment diagram of a data acquisition method in one embodiment;

[0062] Figure 2 This is a flowchart illustrating a method for acquiring data from a client, a target edge cloud node, an edge cloud auxiliary node, and a data service node in one embodiment.

[0063] Figure 3 This is a flowchart illustrating a data acquisition method in one embodiment;

[0064] Figure 4 This is a schematic diagram of the prediction interface and prediction interface data in one embodiment.

[0065] Figure 5 This is a schematic diagram of the prediction interface and prediction interface data in another embodiment;

[0066] Figure 6 This is a schematic diagram of the process of obtaining target interface data through target cache results in one embodiment;

[0067] Figure 7 This is a schematic diagram of the process of obtaining target interface data through target cache results in another embodiment;

[0068] Figure 8 This is a flowchart illustrating a data acquisition method in another embodiment;

[0069] Figure 9 This is a complete flowchart of a data acquisition method in one embodiment;

[0070] Figure 10 This is a flowchart illustrating a method for caching data retrieval in one embodiment;

[0071] Figure 11 This is a schematic diagram illustrating the caching situation of each edge cloud node in one embodiment;

[0072] Figure 12 This is a flowchart illustrating the process of determining the cached result in one embodiment;

[0073] Figure 13 This is a flowchart illustrating the process of determining the data loading method in one embodiment;

[0074] Figure 14 This is a complete flowchart illustrating a method for caching data queries in one embodiment;

[0075] Figure 15 This is a structural block diagram of a data acquisition device in one embodiment;

[0076] Figure 16 This is a structural block diagram of a cached data query device in one embodiment;

[0077] Figure 17 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0078] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0079] With the development of computer technology, edge cloud technology has emerged. Edge nodes are located closer to objects or data sources, enabling them to provide services at the nearest point of contact. This results in faster network service response times and meets users' edge-side needs in areas such as real-time business operations and security and privacy protection. Currently, when an object browses a webpage or application (APP) interface, the client's background typically involves multiple data resource requests. When the server receives a data resource request from the client, if the requested data resource is not found locally, it needs to request the data from the server storing the aforementioned data resource. After obtaining the data resource, it then sends the requested data resource back to the client. The latency of obtaining the data resource depends on the time it takes for the server storing the required data resource to send the data back. Therefore, reducing the data acquisition time is a pressing issue that needs to be addressed.

[0080] Based on this, embodiments of this application provide a data acquisition method that can save data acquisition time and thus improve data acquisition efficiency, as well as a method for caching data queries. The data acquisition method and the data caching method provided in these embodiments can be applied to, for example... Figure 1 In the application environment shown, Figure 1 The application environment shown includes a client 102, a target edge cloud node 104, an edge cloud auxiliary node 106, and a data service node 108. The data service node 108 specifically includes a data source node 1081 and an edge cloud node 1082. The client 102 communicates with the target edge cloud node 104 via a network. The edge cloud auxiliary node 106 has communication connections with both the target edge cloud node 104 and the edge cloud node 1082 within the data service node 108. This means that the edge cloud auxiliary node 106 can use its communication connections with the target edge cloud node 104 and the edge cloud node 1082 to detect and query the caching status of the interface data of the target edge cloud node 104 and the edge cloud node 1082. The data source node 1081 stores the source data for each interface. The data source node 1081 can be integrated on a single server or placed in the cloud; this is not limited here.

[0081] Specifically, the data acquisition method provided in this application embodiment is applied to client 102, that is, client 102 displays the browsing interface that the target object is browsing, determines the set of predicted interfaces related to the browsing interface, and the predicted interface data displayed on each predicted interface. Based on this, client 102 sends a pre-awareness request message to the target edge cloud node 104 related to the client, and obtains the data cache query result for the pre-awareness request message. The aforementioned data cache query result includes at least the cache result corresponding to the data identifier of each predicted interface data. Therefore, client 102 determines the target interface triggered by the target object from the set of predicted interfaces, determines the target data identifier of the target interface data of the target interface, and obtains the target cache result of the target data identifier from the data cache query result through the target data identifier. Finally, it obtains the target interface data through the target cache result and displays the target interface data on the target interface. Before browsing and displaying the interface data, it is possible to predict the predicted interface data that may be displayed. By querying the data cache to determine the node where each predicted interface data is cached, a more accurate and targeted data acquisition method can be achieved by using the data cache query results obtained in advance. This avoids repeatedly requesting data from different edge cloud nodes, thereby saving data acquisition time and improving data acquisition efficiency.

[0082] Secondly, the cached data query method provided in this application embodiment is applied to the edge cloud auxiliary node 106. The edge cloud auxiliary node 106 receives a redirection data message sent by the target edge cloud node 104. The redirection data message includes at least a pre-sensing request message sent by the client 102 to the target edge cloud node 104. Then, the edge cloud auxiliary node 106 extracts the data identifier of each prediction interface data from the pre-sensing request message, and performs a data query based on the data identifier of each prediction interface data for the caching status of each prediction interface data in each edge cloud node. It determines the caching result corresponding to the data identifier of each prediction interface data, constructs a data cache query result, and sends the data cache query result to the target edge cloud node 104, so that the target edge cloud node 104 feeds back the data cache query result to the client 102, so that the client 102 executes the aforementioned data acquisition method. Since the cache query is performed on the prediction interface data through the redirection data message before the client browses and displays the interface data to determine the node where each prediction interface data is cached, the resulting advance-obtained and accurate data cache query result ensures the reliability of the cached data query. This allows clients to cache query results in advance for more accurate and targeted data retrieval, avoiding repeated data requests to different edge cloud nodes, thus saving data retrieval time and improving data retrieval efficiency.

[0083] In this embodiment, the aforementioned target edge cloud node 104, edge cloud auxiliary node 106, and data service node 108 can all be servers. These servers can be independent physical servers, server clusters or distributed systems composed of multiple physical servers, or cloud servers providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The aforementioned client is deployed on a terminal; therefore, the terminal with client 102 deployed can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, etc., but is not limited to these. The terminal and server can be directly or indirectly connected via wired or wireless communication, and this embodiment does not impose any limitations. Furthermore, the data acquisition method and cached data query method provided in this embodiment can be applied to various scenarios, including but not limited to cloud technology.

[0084] The following is about Figure 1 The application environment shown below will be used to describe the data acquisition methods for client 102, target edge cloud node 104, edge cloud auxiliary node 106, and data service node 108. Figure 2 As shown:

[0085] Step 201: The pre-sensing module in client 102 determines whether to perform a pre-sensing caching operation based on whether the object information of the target object in the currently viewed browsing interface meets the filtering conditions. If so, proceed to step 202.

[0086] Step 202: Client 102 sends a pre-sensing request message to the relevant target edge cloud node 104 with a communication connection. The pre-sensing request message carries at least the data identifier of each prediction interface data.

[0087] Step 203: The redirection module in the target edge cloud node 104, if it determines that the request message type in the pre-sensing request message is a redirection type, constructs a redirection data message based on the pre-sensing request message and sends the redirection data message including the pre-sensing request message to the edge cloud auxiliary node 106.

[0088] Step 204: The cache query module in the edge cloud auxiliary node 106 extracts the data identifier of each prediction interface data from the pre-sensing request message, performs a data query on the caching status of each prediction interface data in each edge cloud node based on the data identifier of each prediction interface data, determines the cache result corresponding to the data identifier of each prediction interface data, constructs the data cache query result, and then feeds the data cache query result back to the target edge cloud node 104.

[0089] Step 205: The target edge cloud node 104 sends the data cache query results to the client 102.

[0090] In step 206, client 102 receives the data cache query result and stores it in the data loading module. Therefore, after client 102 determines the target data identifier of the target interface data, it retrieves the target cache result of the target data identifier from the data cache query result cached by the data loading module.

[0091] Step 207: If the target interface data is determined to be obtained from the target edge cloud node 104 based on the target cache result, the client 102 sends a data request message to the target edge cloud node 104; if the target interface data is to be obtained from the data service node 108, the client 102 sends a data request message to the data service node 108.

[0092] Step 208: After receiving the data request message, if the target edge cloud node 104 stores the target interface data, the data acquisition module in the target edge cloud node 104 directly obtains the target interface data from the cache and feeds back the target interface data to the client 102.

[0093] Step 209: If the target edge cloud node 104 does not store the target interface data, but the edge cloud node 1082 stores the target interface data, the data acquisition module in the target edge cloud node 104 needs to acquire the target interface data through the communication connection with the edge cloud node 1082 and feed back the target interface data to the client 102.

[0094] The data acquisition method is described below, with specific examples as follows: In one example, such as Figure 3 As shown, a data acquisition method is provided, which is applied to... Figure 1 Taking client 102 as an example, it can be understood that this method can also be applied to a system including client 102, target edge cloud node 104, edge cloud auxiliary node 106, and data service node 108, and is implemented through the interaction of client 102, target edge cloud node 104, edge cloud auxiliary node 106, and data service node 108. In this embodiment, the method includes the following steps:

[0095] Step 302: Display the browsing interface that the target object is browsing, determine the set of prediction interfaces related to the browsing interface, and the prediction interface data displayed on each prediction interface.

[0096] The browsing interface refers to the interface that the target object is currently browsing and that is being displayed on the client used by the target object; in other words, the browsing interface displays the browsing interface data. Secondly, the prediction interface set includes prediction interfaces related to the browsing interface. These prediction interfaces can be any of the following: an interface belonging to the same category as the browsing interface but not browsed by the target object, or another interface displayed after navigating from the browsing interface. Based on this, the prediction interface data can be the interface data displayed on the prediction interface.

[0097] Specifically, the client displays the browsing interface that the target object is currently browsing based on the target object's browsing operations. It then determines whether there exists an interface belonging to the same category as the browsing interface but not currently being viewed by the target object. If such an interface exists, it is identified as a predicted interface, forming a set of predicted interfaces related to the browsing interface. Furthermore, the interface data displayed on these predicted interfaces is determined as predicted interface data.

[0098] To facilitate understanding of different prediction interfaces and prediction interface data, such as Figure 4 The prediction interface and prediction interface data shown are as follows. Figure 4 The displayed interface 401 is the browsing interface that the target object is currently browsing, and the browsing interface 401 displays browsing interface data A1, browsing interface data A2, and browsing interface data A3. Therefore, the interface 402, which belongs to the same interface as the browsing interface 401 but is not browsed by the target object, is the prediction interface, and the interface data that can be displayed in the prediction interface 402 includes: prediction interface data A4, prediction interface data A5, prediction interface data A6, and prediction interface data A7.

[0099] And such Figure 5 The prediction interface and prediction interface data shown are as follows. Figure 5 The interface 501 shown in Figure (A) is the browsing interface that the target object is currently browsing, and the browsing interface 501 displays browsing interface data A1, browsing interface data A2, and browsing interface data A3. If the target object performs a trigger operation on browsing interface data A2, it will be redirected to... Figure 5 The interface 502 shown in Figure (B) is the prediction interface. The interface data that can be displayed in the prediction interface 502 include: prediction interface data A8, prediction interface data A9, prediction interface data A10 and prediction interface data A11.

[0100] Step 304: Send a pre-awareness request message to the target edge cloud node related to the client, and obtain the data cache query results for the pre-awareness request message; the data cache query results shall include at least the cache results corresponding to the data identifier of each prediction interface data.

[0101] Among them, the pre-awareness request message is generated under the premise that the client needs to pre-aware the prediction interface data. Therefore, the pre-awareness request message includes at least: request message type, request message identifier, the number of pre-aware prediction interface data, and the data identifier of each prediction interface data. The aforementioned request message type is a redirection type, which means that the request message is a pre-awareness request message. The data identifier is specifically a Uniform Resource Identifier (URI). Based on this, the pre-awareness request message can be exemplified by the following formula (1):

[0102] (1)

[0103] in, This indicates a pre-sensing request message. Indicates the request message type. Indicates the request message identifier, This indicates the amount of pre-perceived data in the prediction interface. This refers to the data identifier representing the prediction interface data. And in formula (1)... And the number of pre-perceived data in the prediction interface is In this case, the data identifier for each prediction interface data can be... .

[0104] Secondly, the data cache query results should include at least the cached results corresponding to the data identifier of each prediction interface data. Furthermore, if the target edge cloud node does not cache the target interface data, the data cache query results should also include: the data loading method of the prediction interface data. And if the data loading method indicates that the client requests prediction interface data from the cache edge cloud node, the data cache query results should also include: the address and port number of the cache edge cloud node.

[0105] Specifically, such as Figure 1 As shown, the edge cloud node connected to client 102 is target edge cloud node 104. Therefore, client 102 can send a pre-sensing request message to target edge cloud node 104, including at least the data identifier of each prediction interface data. Considering that in practical applications, data pre-sensing is not performed for every object, that is, data caching results are not obtained in advance for every object, the pre-sensing module in client 102 needs to monitor whether the target object meets the object filtering conditions to avoid performing data pre-sensing on objects that do not meet the object filtering conditions. This will be described below:

[0106] In one specific embodiment, sending a pre-awareness request message to a target edge cloud node associated with the client includes: sending a pre-awareness request message to the target edge cloud node associated with the client when the object information of the target object meets the object filtering conditions.

[0107] The object information includes at least an object identifier and an object priority. In this embodiment, the object priorities are: high priority (usr_level=high), medium priority (usr_level=middle), and low priority (usr_level=normal). Therefore, the object filtering condition is based on object priority, not necessarily low priority. Specifically, the object information of a target object meets the object filtering condition, meaning that the object priority in the target object's object information is at least high or medium priority. Only then is it determined that the object information meets the object filtering condition, and a pre-awareness request message is sent to the target edge cloud node related to the client.

[0108] Secondly, the required predicted interface data differs depending on whether the object priority is high or medium; that is, the data identifiers of the predicted interface data carried in the pre-sensing request message are different. Based on this, when the object priority in the target object's object information is high, the predicted interface data specifically includes: interface data belonging to the same interface as the browsing interface but not viewed by the target object, and interface data of another interface displayed when navigating from the browsing interface. Conversely, when the object priority in the target object's object information is medium, the predicted interface data specifically includes: interface data belonging to the same interface as the browsing interface but not viewed by the target object.

[0109] Furthermore, after client 102 sends a pre-awareness request message to target edge cloud node 104 in the manner described in the foregoing embodiments, target edge cloud node 104 constructs a redirection data message including the pre-awareness request message based on the pre-awareness request message, and sends the redirection data message to edge cloud auxiliary node 106. Edge cloud auxiliary node 106 constructs a data cache query result based on the redirection data message using the cache data query method described in subsequent embodiments, and sends the data cache query result to target edge cloud node 104. Then, target edge cloud node 104 can feed back the received data cache query result to client 102, so that client 102 can obtain the data cache query result for the pre-awareness request message fed back by target edge cloud node 104.

[0110] Secondly, after receiving the data cache query result, the pre-sensing module in client 102 sends the received data cache query result to the data loading module, and the data loading module maintains the data resource status information table based on the data cache query result. For ease of understanding, taking as an example that the data cache query result includes at least the cache result corresponding to the data identifier of each prediction interface data, the data loading method of the prediction interface data when the target edge cloud node does not cache the prediction interface data, and the node information (address and port number) of the cache edge cloud node from which the client requests the prediction interface data from the cache edge cloud node, the data resource status information table shown in Table 1 can be maintained.

[0111] Data Identifier Does the target edge cloud node cache? Data loading method Node information URI_1 HIT_1=1 / / URI_2 HIT_2=0 Method_load_2 Server_source_2 … … … …

[0112] Table 1

[0113] HIT_1=1 indicates that the target edge cloud node caches the prediction interface data uniquely identified by the data identifier, while HIT_1=0 indicates that the target edge cloud node does not cache the prediction interface data uniquely identified by the data identifier. The data loading method, Method_load_0, represents data loading through the target edge cloud node. Method_load_1 represents data loading through the target edge cloud node, and Method_load_2 represents data loading through the data source node. Since the data source node caches the source data of the prediction interface, it also carries the node information (address and port number).

[0114] Therefore, as shown in Table 1, the prediction interface data identified by data identifier URI_1 is cached by the target edge cloud node because "HIT_1=1". However, the prediction interface data identified by data identifier URI_2 is not cached by the target edge cloud node because "HIT_1=0". In this case, the data loading method for the prediction interface data identified by data identifier URI_2 needs to be considered. "Method_load_2" indicates that the data is loaded through the data source node, meaning that the node information of the data source node (Server_source_2) is still stored.

[0115] As can be seen from the aforementioned embodiments, the pre-sensing request message includes a request message type. Therefore, when the request message type is a redirection type, the aforementioned pre-sensing request message truly indicates that the request message needs to pre-sensitize the prediction interface data it carries. This is described below: Based on this, obtaining the data cache query result for the pre-sensing request message includes: when the request message type in the pre-sensing request message is a redirection type, causing the target edge cloud node to construct a redirection data message based on the pre-sensing request message and send the redirection data message to the edge cloud auxiliary node; obtaining the data cache query result for the pre-sensing request message received by the target edge cloud node from the edge cloud auxiliary node.

[0116] Specifically, when the request message type in the pre-sensing request message is a redirection type, that is, after the target edge cloud node 104 receives the pre-sensing request message, it first obtains the request message type carried in the pre-sensing request message. If the request message type is determined to be a redirection type (i.e. At this point, it is determined that the pre-awareness request message needs to be redirected to the edge cloud auxiliary node 106. Therefore, the target edge cloud node 104 constructs a redirection data message based on the pre-awareness request message. The aforementioned redirection data message includes at least: the address and port number of the target edge cloud node, the address and port number of the edge cloud auxiliary node, and the pre-awareness request message. Then, the target edge cloud node 104 sends the redirection data message to the edge cloud auxiliary node 106, and then, through the aforementioned method, the client 102 obtains the data cache query result of the pre-awareness request message fed back by the target edge cloud node 104.

[0117] Step 306: Determine the target interface triggered by the target object from the set of predicted interfaces, and determine the target data identifier of the target interface data of the target interface.

[0118] Among them, the target interface belongs to the set of predicted interfaces. That is, only when the target interface triggered by the target object belongs to the set of predicted interfaces can the corresponding data query and acquisition be performed through the aforementioned pre-perceived data cache query results.

[0119] Specifically, client 102 determines the target interface triggered by the target object from the predicted interface set, and determines the target data identifier of the target interface data. That is, client 102 first obtains the candidate interfaces triggered by the target object, determines the candidate interface data to be displayed, and the candidate data identifier of the candidate interface data. Then, it performs a data identifier query using the data cache query results cached by the data loading module. If the data cache query results include the candidate data identifier, the candidate data identifier can be determined as the target data identifier, the candidate interface data can be determined as the target interface data, and the candidate interface triggered by the target object can be determined as the target interface. At this point, it can be determined that the target interface must belong to the predicted interface set.

[0120] It is understandable that in practical applications, there will inevitably be situations where the data cache query results do not include candidate data identifiers, that is, the candidate interface data to be displayed has not been pre-perceived. In this case, a request message for the candidate data identifier is sent directly to the target edge cloud node so that the target edge cloud node can obtain the candidate interface data indicated by the candidate data identifier. This embodiment will not elaborate on this situation.

[0121] Step 308: Obtain the target cache result of the target data identifier from the data cache query results by using the target data identifier.

[0122] The target cache result includes at least the cache result corresponding to the target data identifier, the data loading method for the target interface data when the target edge cloud node does not cache the target interface data indicated by the target data identifier, and the node information (address and port number) of the data service node (which can be a cache edge cloud node or a data source node) that the client requests the target interface data from the cache edge cloud node. Specifically, the client 102 obtains the target cache result of the target data identifier from the data cache query result through the target data identifier. That is, the client 102 can determine that the data cache query result includes the target data identifier through the aforementioned method, and at this time, the target cache result corresponding to the target data identifier can be directly extracted from the data cache query result.

[0123] Step 310: Obtain the target interface data through the target cache result and display the target interface data on the target interface.

[0124] Specifically, client 102 obtains target interface data through the target cache result and displays the target interface data on the target interface. That is, client 102 requests the target interface data from the indicated node based on the cache result represented by the target cache result and the data loading method, and displays the target interface data on the target interface after receiving the feedback target interface data.

[0125] The cache result corresponding to the target data identifier in the target cache result can indicate whether the target edge cloud node has cached the target interface data or not. That is, if the target edge cloud node has cached the target interface data, client 102 can obtain the target interface data by requesting it from the target edge cloud node. If the target edge cloud node has not cached the target interface data, client 102 can obtain the target interface data by requesting it from the target edge cloud node, or by requesting it from other data service nodes (which can be cache edge cloud nodes or data source nodes). The specific node used to obtain the target interface data is not discussed here; the targeted data retrieval will depend on the result indicated by the target cache result in the actual situation.

[0126] It should be understood that the corresponding examples in the embodiments of this application are used to understand this solution, but should not be construed as specific limitations on this solution.

[0127] In the above data acquisition method, before browsing and displaying the interface data, the predicted interface data that may be displayed is predicted. The node where each predicted interface data is cached is determined by data cache query. In the data cache query results obtained in advance, the cache results and acquisition methods for the target interface data are recorded. Therefore, by using the data cache query results obtained in advance to carry out a more accurate and targeted data acquisition method, it is possible to avoid repeatedly making data requests to different edge cloud nodes, thereby saving data acquisition time and improving data acquisition efficiency.

[0128] Since the cache result corresponding to the target data identifier in the target cache result can represent two situations—that the target edge cloud node caches the target interface data and that the target edge cloud node does not cache the target interface data—the following describes these two situations separately: In one embodiment, such as Figure 6 As shown, the target interface data is obtained through the target cache result, including:

[0129] Step 602: If the target cache result indicates that the target edge cloud node has cached target interface data, send a data request message to the target edge cloud node; the data request message includes the target data identifier and the target cache result.

[0130] Specifically, when the target cache result indicates that the target edge cloud node caches the target interface data, that is, the target edge cloud node 104 connected to the client 102 caches the required target interface data, the client 102 directly sends a data request message to the target edge cloud node 104. The data request message includes the target data identifier and the target cache result. The target data identifier is used to identify the target interface data required by the client 102, and the target cache result indicates that the target edge cloud node caches the target interface data. Therefore, after receiving the data request message, the target edge cloud node 104 extracts the target data identifier and the target cache result obtained from the data request message. Through the target cache result, it can be determined that the target interface data identified by the target data identifier is stored in the cache. That is, the target edge cloud node 104 can directly obtain the target interface data from the cache through the target data identifier. Based on this, the data request message can be exemplified by the following formula (2):

[0131] (2)

[0132] in, Indicates a data request message. The data identifier representing interface data i This represents the cached result of interface data i.

[0133] For ease of understanding, let's take the example shown in Table 1. If the target data identifier is specifically... And data identification Corresponding cached results Cache results This indicates that the target edge cloud node cache contains target data identifiers. The target interface data is uniquely identified; therefore, the data request message sent by client 102 to the target edge cloud node is specifically as follows: { , }

[0134] Step 604: Receive the target interface data fed back by the target edge cloud node.

[0135] Specifically, since client 102 directly sends a data request message including target data identifier and target cache result to target edge cloud node 104, and this is under the condition that target edge cloud node 104 has cached target interface data, target edge cloud node 104 can extract the cached target interface data based on target data identifier and target cache result, and feed the target interface data back to client 102. At this time, client 102 can receive the target interface data fed back by target edge cloud node.

[0136] Secondly, as can be seen from the aforementioned embodiments, there will inevitably be situations where the data cache query results do not include candidate data identifiers, meaning that the candidate interface data to be displayed has not been pre-perceived. In this case, the data request message sent by client 102 to target edge cloud node 104 only includes candidate data identifiers, meaning that the cached results for candidate interface data are not included at this time. Then, the target edge cloud node 104 needs to check whether it has cached the candidate interface data indicated by the candidate data identifier. If the target edge cloud node 104 has cached the candidate interface data, it will also send the candidate interface data back to the client 102. If the target edge cloud node 104 has not cached the candidate interface data, it can request the candidate interface data from other edge cloud nodes or data source nodes, and send the received candidate interface data back to the client. The specific implementation method will not be described in detail in this embodiment.

[0137] It should be understood that the corresponding examples in the embodiments of this application are used to understand this solution, but should not be construed as specific limitations on this solution.

[0138] In this embodiment, the data request message includes a target data identifier and a target cache result. This means that after the target edge cloud node receives the data request message, it does not need to perform a data cache query based on the target data identifier. Instead, it directly determines that the target interface data indicated by the target data identifier is stored locally through the target cache result. This allows for direct data acquisition based on the target data identifier, reducing the time spent on data cache queries and thus reducing the time spent on feeding back the target interface data to the client. This improves the efficiency and reliability of data acquisition.

[0139] In one embodiment, such as Figure 7 As shown, the target interface data is obtained through the target cache result, including:

[0140] Step 702: If the target cache result indicates that the target edge cloud node has not cached the target interface data, obtain the target data loading method of the target data identifier from the data cache query result.

[0141] The data loading methods include at least: loading data through the target edge cloud node, or loading data through a cached edge cloud node that caches the target interface data. Secondly, considering that in practical applications there may be situations where no edge cloud node caches the target interface data, in this case, data can only be loaded from the data source node that matches the target interface data. Therefore, the data loading method can also include: loading data from the data source node that matches the target interface data when no edge cloud node caches the target interface data.

[0142] Specifically, if the target cache result indicates that the target edge cloud node has not cached the target interface data, it means that the client 102 cannot directly obtain the target interface data from the cache of the target edge cloud node. In this case, data loading and data acquisition need to be performed using the target data loading method for the target interface data. That is, when the edge cloud auxiliary node determines that the target edge cloud node has not cached the target interface data, the data loading method for the target interface data is determined by the caching status of each edge cloud node for the target interface data. The method for determining the data loading method is described in detail in the subsequent embodiments of the cached data query method, and will not be repeated here.

[0143] Based on this, since the data cache query results also include the predicted data loading method of the interface data when the target edge cloud node does not cache the target interface data, the target data loading method of the target interface data indicated by the target data identifier can be obtained from the data cache query results when the target cache result represents that the target edge cloud node does not cache the target interface data.

[0144] Step 704: Obtain target interface data through target data loading method.

[0145] Specifically, client 102 obtains target interface data through target data loading method, that is, based on the node information corresponding to the node indicated by the target data loading method, sends a data request message to the node indicated by the target data loading method, so that the node indicated by the target data loading method obtains target interface data based on the data request message and feeds back the target interface data to client 102, so that client 102 receives the target interface data fed back by the node.

[0146] Since there are multiple ways to load target data, the following describes the implementation methods for instructing different nodes to load data using the target data loading method: In one optional embodiment, obtaining target interface data through the target data loading method includes: when the target data loading method indicates that data is loaded through a target edge cloud node, sending a data request message to the target edge cloud node so that the target edge cloud node obtains the target interface data from the cache edge cloud node; the data request message includes a target data identifier and a target cache result; the cache edge cloud node caches the target interface data; and receiving the target interface data fed back by the target edge cloud node.

[0147] The cached edge cloud node caches the target interface data, and the data request message also includes the address and port number of the cached edge cloud node.

[0148] Specifically, when the target data loading method is characterized by loading data through the target edge cloud node, that is, the client 102 needs to obtain data from the data service node storing the target interface data through the target edge cloud node 104. Therefore, at this time, the client 102 needs to obtain the address and port number of the cache edge cloud node that caches the target interface data, the target data identifier, and the target cache result from the data cache query result. At this time, the target cache result indicates that the target edge cloud node does not cache the target interface data.

[0149] Based on this, client 102 constructs a data request message using the aforementioned information and then sends the data request message to target edge cloud node 104. Target edge cloud node 104 extracts the address and port number of the cache edge cloud node, the target data identifier, and the target caching result from the data request message. Since the target caching result indicates that target edge cloud node 104 has not cached the target interface data, target edge cloud node 104 needs to send a data request message for the target data identifier to the cache edge cloud node using the extracted address and port number of the cache edge cloud node. Since it carries the address and port number of the cache edge cloud node, it can be determined that the target interface data is cached in the cache edge cloud node. Therefore, the data request message sent by target edge cloud node 104 to the cache edge cloud node carries the target data identifier and the caching result of the cache edge cloud node for the target interface data.

[0150] Therefore, the cached edge cloud node will be similar to the implementation method in the previous embodiment where the target edge cloud node caches the target interface data. It will obtain the target interface data from the cache and feed the obtained target interface data back to the target edge cloud node 104. The target edge cloud node 104 will then feed the target interface data back to the client 102, so that the client 102 receives the target interface data fed back by the target edge cloud node 104.

[0151] In one optional embodiment, obtaining target interface data through a target data loading method includes: when the target data loading method indicates that data is loaded through a cached edge cloud node, obtaining the address and port number of the cached edge cloud node from the data cache query results; the cached edge cloud node caches the target interface data; sending a data request message to the cached edge cloud node based on the address and port number of the cached edge cloud node; the data request message includes a target data identifier and the data caching result of the cached edge cloud node for the target interface data; and receiving the target interface data fed back by the cached edge cloud node.

[0152] Specifically, the edge cloud node caches the target interface data, and the data request message includes the target data identifier and the data caching result of the edge cloud node for the target interface data. In the case where the target data loading method indicates that data is loaded through the edge cloud node (i.e., client 102 directly retrieves data from the edge cloud node), client 102 needs to obtain the address and port number of the edge cloud node that caches the target interface data, the target data identifier, and the data caching result of the edge cloud node for the target interface data from the data cache query results. The data caching result of the edge cloud node for the target interface data indicates that the edge cloud node caches the target interface data.

[0153] Based on this, client 102 constructs a data request message using the aforementioned information and sends the data request message to the cache edge cloud node based on the address and port number of the cache edge cloud node. The cache edge cloud node extracts the data caching result for the target interface data in the data request message and can determine that the cache contains the target interface data required by client 102. Then, the cache edge cloud node can obtain the target interface data from the cache through the target data identifier and feed the target interface data back to client 102, so that client 102 receives the target interface data fed back by the cache edge cloud node.

[0154] Optionally, since the client 102 can determine which prediction interface data loading methods are represented by data loading through the cache edge cloud node after obtaining the data cache query results in advance, it can establish a communication connection with the cache edge cloud node that caches the prediction interface data in advance for the data loading method of data loading through the cache edge cloud node, so as to reduce the time loss caused by the need to create a connection when sending data request messages.

[0155] As described above, the data loading method can also include: loading data from a data source node that matches the target interface data when no edge cloud node caches the target interface data. That is, in the case where the aforementioned data loading method involves loading data from a data source node that matches the target interface data, the client 102 sends a data request message to the data source node that matches the target interface data. This data request message includes a target data identifier. Then, the data source node that matches the target interface data retrieves the stored target interface data using a similar method and sends the target interface data back to the client 102, allowing the client 102 to receive the target interface data fed back by the data source node that matches the target interface data.

[0156] It should be understood that the corresponding examples in the embodiments of this application are used to understand this solution, but should not be construed as specific limitations on this solution.

[0157] In this embodiment, since the target edge cloud node does not store the target interface data, the node for data loading is accurately located through different data loading methods. Thus, the corresponding data is acquired based on the different data loading methods. In other words, the method of loading uncached data from the edge cloud can also be directly loaded from other data service nodes, which effectively reduces the data resource loading time of the client, so as to ensure the reliability and efficiency of data loading, thereby improving the efficiency and reliability of data acquisition.

[0158] In one embodiment, such as Figure 8 As shown, data acquisition methods also include:

[0159] Step 802: After displaying the target interface data on the target interface, delete the target cache result from the data cache query result.

[0160] Specifically, after the client 102 obtains the target interface data in the aforementioned manner and displays the target interface data on the target interface, since the loading and acquisition of the pre-perceived data has been completed, the target cache result is deleted from the data cache query result, or the result related to the target data identifier is deleted from Table 1 in the aforementioned example. For example, if the target data identifier is URI_1, and the acquisition and display of the target interface data with the data identifier URI_1 has been completed, the relevant information of the row containing URI_1 is deleted from Table 1.

[0161] Alternatively, in step 804, for each prediction interface data, after reaching the timeout threshold matched by the prediction interface data, the cached result corresponding to the data identifier of each prediction interface data is deleted from the data cache query result.

[0162] The timeout threshold (T_threshold) is a pre-configured threshold for each prediction interface data. In this embodiment, the timeout threshold can be configured to 10 seconds by default. Specifically, since data pre-sensing is performed for each prediction interface data, that is, the cached result corresponding to the data identifier of each prediction interface data in the data cache query result stored in the client 102, and if the triggering operation of the target object does not actually perform any related operations on the prediction interface data, then the pre-sensed data is data that does not need to be browsed and displayed temporarily, so as to avoid the cached result of the prediction interface data caching occupying memory. At this time, a timeout threshold can be configured for each prediction interface data. Then, after the timeout threshold matched by the prediction interface data is reached, if no data acquisition operation is performed on the prediction interface data, the cached result corresponding to the data identifier of each prediction interface data can be deleted from the data cache query result.

[0163] Optionally, the client can maintain a timer for each cached query result and configure a timeout threshold for each cached query result. That is, the timeout threshold configured for prediction interface data belonging to the same cached query result is the same.

[0164] It should be understood that the corresponding examples in the embodiments of this application are used to understand this solution, but should not be construed as specific limitations on this solution.

[0165] In this embodiment, memory usage is reduced by deleting cached results of retrieved and displayed interface data from the data cache query results. Secondly, memory usage is further reduced by configuring timeout thresholds to prevent cached results of interface data from occupying memory. This ensures the reliability of client-side memory processing and, consequently, the reliability of client-side data request processing.

[0166] Based on the detailed description of the foregoing embodiments, the complete process of the data acquisition method in the embodiments of this application will be described below. In one embodiment, such as Figure 9 As shown, a data acquisition method is provided, which is applied to... Figure 1 Taking client 102 as an example, it can be understood that this method can also be applied to a system including client 102, target edge cloud node 104, edge cloud auxiliary node 106, and data service node 108, and is implemented through the interaction of client 102, target edge cloud node 104, edge cloud auxiliary node 106, and data service node 108. In this embodiment, the method includes the following steps:

[0167] Step 901: Display the browsing interface that the target object is browsing, determine the set of prediction interfaces related to the browsing interface, and the prediction interface data displayed on each prediction interface.

[0168] Step 902: If the object information of the target object meets the object filtering conditions, send a pre-awareness request message to the target edge cloud node related to the client; if the request message type in the pre-awareness request message is a redirection type, the target edge cloud node constructs a redirection data message based on the pre-awareness request message and sends the redirection data message to the edge cloud auxiliary node.

[0169] Step 903: Obtain the data cache query results for the pre-sensing request message received by the target edge cloud node from the edge cloud auxiliary node.

[0170] Step 904: Determine the target interface triggered by the target object from the set of predicted interfaces, and determine the target data identifier of the target interface data of the target interface.

[0171] Step 905: Obtain the target cache result of the target data identifier from the data cache query results using the target data identifier.

[0172] Step 906: If the target cache result indicates that the target edge cloud node has cached target interface data, send a data request message to the target edge cloud node; the data request message includes the target data identifier and the target cache result; receive the target interface data fed back by the target edge cloud node.

[0173] Step 907: If the target cache result indicates that the target edge cloud node has not cached the target interface data, obtain the target data loading method of the target data identifier from the data cache query result.

[0174] Step 908: When the target data loading method is characterized by loading data through the target edge cloud node, a data request message is sent to the target edge cloud node so that the target edge cloud node can obtain the target interface data from the cache edge cloud node; the data request message includes the target data identifier and the target cache result; the cache edge cloud node caches the target interface data; and the target interface data fed back by the target edge cloud node is received.

[0175] Step 909: When the target data loading method is characterized by loading data through a cached edge cloud node, obtain the address and port number of the cached edge cloud node from the data cache query results; the cached edge cloud node caches the target interface data; based on the address and port number of the cached edge cloud node, send a data request message to the cached edge cloud node; the data request message includes the target data identifier and the data caching result of the cached edge cloud node for the target interface data; receive the target interface data fed back by the cached edge cloud node.

[0176] Step 910: Display the target interface data on the target interface.

[0177] It should be understood that the specific implementation methods of steps 901 to 910 are similar to the data acquisition implementation methods described in the foregoing embodiments, and will not be repeated here.

[0178] The following describes the method for querying cached data, illustrated in the following example: In one example, as follows... Figure 10 As shown, a method for caching data queries is provided, which can be applied to... Figure 1Taking the edge cloud auxiliary node 106 as an example, it can be understood that this method can also be applied to a system including client 102, target edge cloud node 104, edge cloud auxiliary node 106, and data service node 108, and is implemented through the interaction of client 102, target edge cloud node 104, edge cloud auxiliary node 106, and data service node 108. In this embodiment, the method includes the following steps:

[0179] Step 1002: Receive a redirected data message sent by the target edge cloud node; the redirected data message includes at least: a pre-awareness request message sent by the client to the target edge cloud node.

[0180] The redirected data message includes at least a pre-sensing request message sent by the client to the target edge cloud node. As described in the foregoing embodiments, the redirected data message also includes the address and port number of the target edge cloud node, and the address and port number of the edge cloud auxiliary node. Specifically, when the object information of the target object meets the object filtering conditions, the client 102 sends a pre-sensing request message to the target edge cloud node 104 connected to the client 102. If the target edge cloud node 104 determines that the request message type in the pre-sensing request message is a redirection type, the target edge cloud node 104 constructs a redirected data message based on the pre-sensing request message and sends the redirected data message to the edge cloud auxiliary node 106. At this time, the edge cloud auxiliary node 106 can receive the redirected data message sent by the target edge cloud node 104. It is understood that the method and prerequisites for constructing and sending the redirected data message are similar to those described in the foregoing embodiments, and will not be repeated here.

[0181] Step 1004: Extract the data identifier of each prediction interface data from the pre-sensing request message.

[0182] Specifically, since the redirected data message includes at least a pre-sensing request message sent by the client to the target edge cloud node, and the pre-sensing request message includes at least: request message type, request message identifier, the number of pre-sensed prediction interface data, and the data identifier of each prediction interface data, the edge cloud auxiliary node 106 extracts the pre-sensing request message from the redirected data message, and then extracts the data identifier of each prediction interface data from the pre-sensing request message. The prediction interface data and data identifier are similar to those described in the previous embodiments, and will not be repeated here.

[0183] Step 1006: Based on the data identifier of each prediction interface data, perform data query on the caching status of each prediction interface data at each edge cloud node, determine the caching result corresponding to the data identifier of each prediction interface data, and construct the data cache query result.

[0184] Specifically, the caching status of each prediction interface data at each edge cloud node is as follows: the cache record of which edge cloud node the prediction interface data is cached in. For example, taking the prediction interface data in the aforementioned example, which includes prediction interface data A4, prediction interface data A5, prediction interface data A6, prediction interface data A7, prediction interface data A8, prediction interface data A9, prediction interface data A10, and prediction interface data A11, as an example for explanation.

[0185] If there exist edge cloud nodes B1, B2, and B3, and edge cloud node B1 caches prediction interface data A4, A5, and A6; edge cloud node B2 caches prediction interface data A4, A8, and A9; and edge cloud node B3 caches prediction interface data A10 and A11, then for prediction interface data A4, the caching situation for each edge cloud node is specifically cached in edge cloud nodes B1 and B2. For prediction interface data A5, the caching situation for each edge cloud node is specifically cached in edge cloud node B1. And so on, without further explanation.

[0186] Secondly, the data cache query results should include at least the cached results corresponding to the data identifier of each prediction interface data. Furthermore, if the target edge cloud node does not cache the target interface data, the data cache query results should also include: the data loading method of the prediction interface data. And if the data loading method indicates that the client requests prediction interface data from the cache edge cloud node, the data cache query results should also include: the address and port number of the cache edge cloud node.

[0187] Specifically, in this embodiment, the edge cloud auxiliary node 106 can manage and monitor the node status of multiple edge cloud nodes, including node operation status and node data caching status. That is, the edge cloud auxiliary node 106 can record the caching status of each interface data in multiple edge cloud nodes. This caching status can be achieved through periodic information synchronization between the edge cloud auxiliary node 106 and multiple edge cloud nodes, or it can be achieved by the edge cloud auxiliary node 106 requesting caching status information from each edge cloud node through object control operations. Therefore, the implementation method for the edge cloud auxiliary node 106 to obtain the caching status of each interface data in the edge cloud nodes is not limited here.

[0188] To facilitate understanding of the caching situation for data on each interface, such as Figure 11The diagram illustrates the caching configuration of each edge cloud node. Edge cloud auxiliary node 1101 has communication connections with edge cloud nodes 1102, 1103, and 1104. Edge cloud node 1102 caches interface data identified by data identifier UR_1 and interface data identified by data identifier UR_2. Edge cloud node 1103 caches interface data identified by data identifier UR_2 and interface data identified by data identifier UR_5. Edge cloud node 1104 caches interface data identified by data identifier UR_3 and interface data identified by data identifier UR_4.

[0189] Therefore, if node identifier Edge_1 is used to identify edge cloud node 1102, node identifier Edge_2 is used to identify edge cloud node 1103, and node identifier Edge_3 is used to identify edge cloud node 1104, then edge cloud auxiliary node 1101 can record the caching status of each prediction interface data in each edge cloud node.<UR_1,Edge_1> ,<UR_2,Edge_1,Edge_2> ,<UR_3,Edge_3> ,<UR_4,Edge_3> ,<UR_5,Edge_2> The caching status of the aforementioned edge cloud nodes is characterized as follows: Interface data identified by data identifier UR_1 is cached in edge cloud node 1102 identified by node identifier Edge_1. Interface data identified by data identifier UR_2 is cached in edge cloud node 1102 and edge cloud node 1103 identified by node identifier Edge_2. Interface data identified by data identifier UR_3 is cached in edge cloud node 1104 identified by node identifier Edge_3. Interface data identified by data identifier UR_4 is cached in edge cloud node 1104 identified by node identifier Edge_3. Interface data identified by data identifier UR_5 is cached in edge cloud node 1103 identified by node identifier Edge_2.

[0190] Furthermore, the edge cloud auxiliary node 106, through the recorded caching status of each interface data among multiple edge cloud nodes, performs data queries for the predicted interface data identified by each data identifier to determine the caching result corresponding to the data identifier of each predicted interface data. This determines the edge cloud node storing the predicted interface data; the edge cloud node storing the predicted interface data can be the target edge cloud node or any other edge cloud node. Based on this, the edge cloud auxiliary node 106 determines the caching result corresponding to the data identifier of each predicted interface data based on the edge cloud node storing the predicted interface data, and constructs a data cache query result. At this point, the data cache query result includes at least the caching result corresponding to the data identifier of each predicted interface data.

[0191] Understandably, in practical applications, there may be situations where multiple edge cloud nodes do not store prediction interface data. In such cases, it is necessary to load data through the data source node that matches the prediction interface data. For this prediction interface data, the data cache query result will carry the node information (address and port number) of the data source node that matches the prediction interface data.

[0192] The following details how to determine the cached result corresponding to the data identifier of the prediction interface data: In a specific embodiment, based on the data identifier of each prediction interface data, a data query is performed on the caching status of each prediction interface data at each edge cloud node to determine the cached result corresponding to the data identifier of each prediction interface data. This includes: performing a data query on the caching status of each prediction interface data at each edge cloud node for the data identifier of each prediction interface data to determine the target caching status on the target edge cloud node; and determining the cached result corresponding to the data identifier of each prediction interface data based on the target caching status of each prediction interface data.

[0193] The target caching status can be characterized as follows: either the target edge cloud node caches the prediction interface data, or the target edge cloud node does not cache the prediction interface data. In the latter case, the target caching status can further characterize the edge cloud node that caches the prediction interface data. Even if the target edge cloud node does not cache the prediction interface data, the target caching status will still characterize the edge cloud node that stores the prediction interface data. Considering that in practical applications there may be a situation where no edge cloud node caches the prediction interface data, the target caching status will then characterize the situation where no edge cloud node caches the prediction interface data.

[0194] Specifically, the edge cloud auxiliary node 106 queries the predicted interface data identified by each data identifier by recording the caching status of each interface data in multiple edge cloud nodes, specifically determining the target caching status of each predicted interface data on the target edge cloud node, and then determining the caching result corresponding to the data identifier of each predicted interface data based on the target caching status of each predicted interface data.

[0195] If the target edge cloud node caches the prediction interface data, then the target caching status indicates that the target edge cloud node caches the prediction interface data. In this case, the caching result of the data identifier of the prediction interface data can be used to indicate that the target edge cloud node caches the prediction interface data. Conversely, if the target edge cloud node does not cache the prediction interface data, then the target caching status indicates that the target edge cloud node does not cache the prediction interface data. Further data queries based on the data identifier of the prediction interface data are performed to determine the cached edge cloud node that caches the prediction interface data. In this case, the target caching status will also indicate the cached edge cloud node that caches the prediction interface data. At this point, it is necessary to consider how to load the prediction interface data. Therefore, even if the target edge cloud node does not cache the target interface data, the data caching query result also includes the data loading method for that prediction interface data.

[0196] Secondly, if, for the predicted interface data, no edge cloud node is found to have cached the predicted interface data in the cache information of multiple edge cloud nodes recorded by the edge cloud auxiliary node 106, then the target caching situation indicates that no edge cloud node caches the predicted interface data. In the case where no edge cloud node caches the predicted interface data, the data cache query result also includes the data loading method for that predicted interface data. This data loading method indicates that data will be obtained through the data source node of the predicted interface data, which is the node information of the data source node of the predicted interface data.

[0197] Step 1008: Send the data cache query result to the target edge cloud node so that the target edge cloud node can feed back the data cache query result to the client.

[0198] Specifically, the edge cloud auxiliary node 106 sends the data cache query result to the target edge cloud node 104, so that the target edge cloud node 104 feeds back the data cache query result to the client 102, so that the client 102 stores the data cache query result locally, and obtains the target cache result of the target data identifier from the data cache query result through the data acquisition method described in the previous embodiment, and obtains the target interface data through the target cache result, and displays the target interface data on the target interface. The specific real-time method is similar to that in the previous embodiment, and will not be repeated here.

[0199] It should be understood that the corresponding examples in the embodiments of this application are used to understand this solution, but should not be construed as specific limitations on this solution.

[0200] In the aforementioned method of cached data querying, the cache query for the predicted interface data is performed by redirecting data packets before the client browses and displays the interface data. This determines the node where each predicted interface data is cached, resulting in pre-obtained and accurate cached data query results, ensuring the reliability of the cached data query. Furthermore, the client can use the pre-obtained cached data query results for more accurate and targeted data retrieval, avoiding repeated data requests to different edge cloud nodes, thus saving data retrieval time and improving data retrieval efficiency.

[0201] In one embodiment, such as Figure 12 As shown, in step 1006, based on the target caching status of each prediction interface data, the caching result corresponding to the data identifier of each prediction interface data is determined, including:

[0202] Step 1202: For each predicted interface data, if the target caching situation indicates that the target edge cloud node has the predicted interface data cached, determine the caching result of the data identifier of the predicted interface data to indicate that the target edge cloud node has the predicted interface data cached.

[0203] Specifically, for each prediction interface data, if the target edge cloud auxiliary node 106 indicates that the prediction interface data is cached by the target edge cloud node 104, it means that the client 102 can directly obtain the prediction interface data from the target edge cloud node 104. Therefore, the cache result of the prediction interface data being cached by the target edge cloud node is determined as the data identifier of the prediction interface data.

[0204] For ease of understanding, Figure 11 To illustrate, if the target edge cloud node 104 is specifically edge cloud node 1102, and the predicted interface data is the interface data identified by data identifier UR_1, then through... Figure 11 As shown in the example, the interface data identified by data identifier UR_1 is cached in the edge cloud node 1102 identified by node identifier Edge_1. This means the target caching situation indicates that the target edge cloud node (edge ​​cloud node 1102) caches the predicted interface data (the interface data identified by data identifier UR_1). Therefore, the cache result is determined by the data identifier of the predicted interface data cached in the target edge cloud node. In other words, the caching result can be obtained as: {UR_1, HIT_1=1}, meaning the target edge cloud node caches the predicted interface data uniquely identified by data identifier UR_1.

[0205] Step 1204: For each predicted interface data, if the target edge cloud node does not cache the predicted interface data, determine the caching result of the data identifier of the predicted interface data to represent: the target edge cloud node does not cache the target interface data.

[0206] Specifically, for each prediction interface data, if the target edge cloud node 104 cannot directly obtain the prediction interface data from the client 102 when the target caching status indicates that the target edge cloud node has not cached the prediction interface data, then the target edge cloud node 106 determines the cached result of the data identifier of the prediction interface data as the target edge cloud node not caching the target interface data.

[0207] For ease of understanding, Figure 11 To illustrate, if the target edge cloud node 104 is specifically edge cloud node 1102, and the predicted interface data is the interface data identified by data identifier UR_3, then through... Figure 11 As shown in the example, the interface data identified by data identifier UR_3 is cached in the edge cloud node 1104 identified by node identifier Edge_3. This means the target caching status indicates that the target edge cloud node (edge ​​cloud node 1102) does not cache the predicted interface data (the interface data identified by data identifier UR_3). Therefore, the fact that the target edge cloud node does not cache the target interface data is determined as the caching result of the data identifier of this predicted interface data. In other words, the caching result can be obtained as: {UR_3, HIT_1=0}, which means the target edge cloud node does not cache the predicted interface data uniquely identified by data identifier UR_3.

[0208] It should be understood that the corresponding examples in the embodiments of this application are used to understand this solution, but should not be construed as specific limitations on this solution.

[0209] In this embodiment, the determination of the cached result of the data identifier of the predicted interface data is made by checking whether the target edge cloud node has cached the predicted interface data, thus ensuring the reliability of the data cache query. Furthermore, the cache result can be used to determine whether the client can directly obtain the required interface data from the cache of the target edge cloud node. If the data is cached, the interface data can be directly extracted and obtained, thereby improving the efficiency and reliability of data acquisition.

[0210] Since the target interface data is not cached by the target edge cloud node, the client can obtain data from other edge cloud nodes through the target edge cloud node, or the client can directly obtain data from other edge cloud nodes. Therefore, to ensure that the client can directly load data from more efficient and reliable nodes, the following provides a detailed description of the aforementioned situation. In one embodiment, such as... Figure 13 As shown, methods for caching data queries also include:

[0211] Step 1302: If the target edge cloud node does not cache the target interface data, determine the cached edge cloud node that caches the predicted interface data.

[0212] Specifically, when the target edge cloud node does not cache the target interface data, the edge cloud auxiliary node 106 determines the cached edge cloud node that caches the predicted interface data from other non-edge cloud nodes. For ease of understanding, based on the example of step 1204, since the target caching situation indicates that the target edge cloud node (edge ​​cloud node 1102) does not cache the predicted interface data (the interface data identified by data identifier UR_3), and the interface data identified by data identifier UR_3 is specifically cached in the edge cloud node 1104 identified by node identifier Edge_3, the edge cloud node 1104 identified by node identifier Edge_3 can be determined as the cached edge cloud node of the predicted interface data (the interface data identified by data identifier UR_3).

[0213] It is understandable that if the target caching situation represents the absence of edge cloud node caching for prediction interface data, then the data loading method for the prediction interface data in the data cache query result indicates that the data is obtained through the data source node of the prediction interface data, and will also carry the node information of the data source node of the prediction interface data.

[0214] Step 1304: Obtain the first latency of the client obtaining the prediction interface data through the target edge cloud node, and the second latency of the client obtaining the prediction interface data through the cached edge cloud node.

[0215] The first delay (delay_edge) is the delay at which the client obtains prediction interface data from the target edge cloud node. This process involves two steps: data request interaction between the target edge cloud node and the client, and data request interaction between the target edge cloud node and the cache edge cloud node. Therefore, the first delay includes the first round-trip delay (delay_cur_client) between the target edge cloud node and the client, and the second round-trip delay (delay_cur_source) between the target edge cloud node and the cache edge cloud node. In other words, the first delay is the sum of the first and second round-trip delays (delay_edge = delay_cur_client + delay_cur_source).

[0216] Secondly, the second delay (delay_source) is the delay when the client obtains the prediction interface data through the cached edge cloud node. At this time, there is no need for the target edge cloud node to relay the data request. Therefore, the second delay is specifically the round-trip delay between the client and the cached edge cloud node to obtain the prediction interface data.

[0217] Specifically, the edge cloud auxiliary node 106 determines the first round-trip time between the target edge cloud node and the client to obtain prediction interface data, and the second round-trip time between the target edge cloud node and the cached edge cloud node to obtain prediction interface data. The sum of the first and second round-trip times is then determined as the first delay for obtaining prediction interface data through the target edge cloud node. Similarly, the edge cloud auxiliary node 106 determines the round-trip time between the client and the cached edge cloud node to obtain prediction interface data, and determines this round-trip time as the second delay for the client to obtain prediction interface data through the cached edge cloud node.

[0218] Step 1306: Based on the first delay and the second delay, determine the data loading method of the data identifier of the prediction interface data; wherein, in the case that the target edge cloud node does not cache the target interface data, the data cache query result also includes: the data loading method of the prediction interface data.

[0219] In cases where the target edge cloud node does not cache the target interface data, the data caching query results also include: the data loading method for the predicted interface data. Furthermore, the data loading method can be any of the following: loading data from the cached edge cloud node via the target edge cloud node (i.e., requesting predicted interface data), or loading data from the cached edge cloud node via the client (i.e., requesting predicted interface data). Considering the possibility that multiple edge cloud nodes may not store predicted interface data, the data loading method can also be loading data from the data source node matched by the predicted interface data.

[0220] Specifically, the edge cloud auxiliary node 106 determines the data loading method for the data identifier of the prediction interface data based on the first latency and the second latency. That is, the edge cloud auxiliary node 106 judges the latency of the first latency and the second latency, and selects the node with the smaller latency value as the data loading node for the client. This will be explained in detail below:

[0221] In one specific embodiment, the data loading method for determining the data identifier of the prediction interface data based on the first delay and the second delay includes: when the first delay is less than or equal to the second delay, the client requests the prediction interface data from the cache edge cloud node through the target edge cloud node as the data loading method; when the first delay is less than or greater than the second delay, the client requests the prediction interface data from the cache edge cloud node as the data loading method; wherein, when the data loading method indicates that the client requests the prediction interface data from the cache edge cloud node, the data cache query result also includes: the address and port number of the cache edge cloud node.

[0222] Specifically, when the first latency is less than the second latency (i.e., the latency for the client to obtain prediction interface data through the target edge cloud node is less than the latency for obtaining prediction interface data through the cached edge cloud node), the client requests prediction interface data from the cached edge cloud node through the target edge cloud node as the data loading method. However, since the target edge cloud node 104 is an associated edge cloud node with which the client 102 has already established a communication connection, when the first latency equals the second latency, considering the reliability of data interaction between the edge cloud node and the client, the client still requests prediction interface data from the cached edge cloud node through the target edge cloud node as the data loading method. In this case, the data loading method is specifically Method_load_0, meaning that Method_load_0 is used to represent data loading through the target edge cloud node.

[0223] Secondly, if the first latency is greater than the second latency, it indicates that the client's latency in obtaining prediction interface data through the cached edge cloud node is lower. In this case, requesting prediction interface data from the cached edge cloud node by the client is taken as the data loading method. Specifically, the data loading method is Method_load_1, meaning that Method_load_1 represents data loading through the cached edge cloud node. Since the client needs to request prediction interface data from the cached edge cloud node, but there may not be a communication connection between the client and the cached edge cloud node, the data cache query result also needs to include the node information (address and port number) of the cached edge cloud node matched by Method_load_1, given that Method_load_1 represents the client requesting prediction interface data from the cached edge cloud node.

[0224] As described above, if all edge nodes store prediction interface data, then data loading is determined to be performed through the data source node of the prediction interface data. Specifically, the data loading method is Method_load_2, which indicates that data is loaded through the data source node. Since the data source node caches the source data of the prediction interface data, it also carries the node information (address and port number) of the data source node.

[0225] Therefore, since different prediction interface data have different caching results, the data cache query result can include the caching results of each prediction interface data separately, and the data cache query result for the pre-sensing request message should at least include the following: 1. The request message type of the pre-sensing request message corresponding to the data cache query result. 2. Data caching query results pre-awareness of request message identifiers. 3. The number of pre-sensed interface data predicted in the data caching query result pre-sensing request message. 4. Data Identifiers for Prediction Interface Data Corresponding cached results 5. Data loading method 6. Node information of the data service node storing the prediction interface data. The aforementioned data service node can be either a data source node or an edge cloud node.

[0226] Based on this, the data cache query results can be exemplified using the following formula (3):

[0227]

[0228] (3)

[0229] in, This indicates that the query results are cached. The request message type that indicates the pre-sensing request message. The request message identifier that represents the pre-sensing request message. This indicates the number of pre-sensed interface data points in the pre-sensing request message. This represents the data identifier used to predict interface data in the pre-sensing request message. Indicates the data loading method. This indicates the node information of the data service node that stores the prediction interface data.

[0230] And in formula (3) The representation is that data is loaded through the target edge cloud node. The representation loads data through cached edge cloud nodes, at which point... Specifically, it represents the node information of the cached edge cloud nodes. The representation loads data through the data source node, at which point... Specifically, it represents the node information of the data source node.

[0231] It should be understood that the corresponding examples in the embodiments of this application are used to understand this solution, but should not be construed as specific limitations on this solution.

[0232] In this embodiment, the latency of obtaining prediction interface data through the target edge cloud node and the latency of obtaining prediction interface data through the cached edge cloud node are specifically considered. The data loading method with lower latency is selected to locate the specific node, so as to ensure that the required data is obtained in a more stable and efficient data loading method in actual applications, thereby further improving the data acquisition efficiency and reliability.

[0233] Based on the detailed description of the foregoing embodiments, the complete process of the cached data query method in the embodiments of this application will be described below. In one embodiment, such as Figure 14 As shown, a method for caching data queries is provided, which can be applied to... Figure 1 Taking the edge cloud auxiliary node 106 as an example, it can be understood that this method can also be applied to a system including client 102, target edge cloud node 104, edge cloud auxiliary node 106, and data service node 108, and is implemented through the interaction of client 102, target edge cloud node 104, edge cloud auxiliary node 106, and data service node 108. In this embodiment, the method includes the following steps:

[0234] Step 1401: Receive a redirected data message sent by the target edge cloud node; the redirected data message includes at least: a pre-awareness request message sent by the client to the target edge cloud node.

[0235] Step 1402: Extract the data identifier of each prediction interface data from the pre-sensing request message.

[0236] Step 1403: For each prediction interface data, perform a data query on the caching status of each prediction interface data at each edge cloud node to determine the target caching status on the target edge cloud node.

[0237] Step 1404: For each predicted interface data, if the target caching situation indicates that the target edge cloud node has the predicted interface data cached, determine the caching result of the data identifier of the predicted interface data to indicate that the target edge cloud node has the predicted interface data cached.

[0238] Step 1405: For each predicted interface data, if the target edge cloud node does not cache the predicted interface data, determine the caching result of the data identifier of the predicted interface data to represent: the target edge cloud node does not cache the target interface data.

[0239] Step 1406: If the target edge cloud node does not cache the target interface data, determine the cached edge cloud node that caches the predicted interface data; wherein, if the target edge cloud node does not cache the target interface data, the data cache query result also includes: the data loading method of the predicted interface data.

[0240] Step 1407: Obtain the first latency of the client obtaining the prediction interface data through the target edge cloud node, and the second latency of the client obtaining the prediction interface data through the cached edge cloud node.

[0241] Step 1408: If the first delay is less than or equal to the second delay, the client requests the predicted interface data from the cached edge cloud node through the target edge cloud node as the data loading method.

[0242] Step 1409: If the first delay is less than or greater than the second delay, the client requests the prediction interface data from the cache edge cloud node as the data loading method; wherein, when the data loading method represents the client requesting the prediction interface data from the cache edge cloud node, the data cache query result also includes: the address and port number of the cache edge cloud node.

[0243] Step 1410: Construct the data cache query results; send the data cache query results to the target edge cloud node so that the target edge cloud node can feed back the data cache query results to the client.

[0244] It should be understood that the specific implementation methods of steps 1401 to 1410 are similar to the implementation methods of cached data query described in the foregoing embodiments, and will not be repeated here.

[0245] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps.

[0246] Based on the same inventive concept, this application also provides a data acquisition apparatus for implementing the data acquisition method described above. The solution provided by this apparatus is similar to the implementation scheme described in the above method; therefore, the specific limitations in one or more data acquisition apparatus embodiments provided below can be found in the limitations of the data acquisition method described above, and will not be repeated here.

[0247] In one embodiment, such as Figure 15 As shown, a data acquisition device is provided, deployed on a client side, including: an interface data processing module 1502, a cache query result acquisition module 1504, an interface data determination module 1506, a cache result acquisition module 1508, and a data acquisition module 1510, wherein:

[0248] The interface data processing module 1502 is used to display the browsing interface that the target object is browsing, determine the set of prediction interfaces related to the browsing interface, and the prediction interface data displayed on each prediction interface respectively.

[0249] The cache query result acquisition module 1504 is used to send a pre-sensing request message to the target edge cloud node related to the client and acquire the data cache query result for the pre-sensing request message; the data cache query result includes at least the cache result corresponding to the data identifier of each prediction interface data;

[0250] The interface data determination module 1506 is used to determine the target interface triggered by the target object from the predicted interface set, and to determine the target data identifier of the target interface data of the target interface.

[0251] The cache result acquisition module 1508 is used to obtain the target cache result of the target data identifier from the data cache query result by means of the target data identifier;

[0252] The data acquisition module 1510 is used to acquire target interface data through target cache results and display the target interface data on the target interface.

[0253] In one embodiment, the cache query result acquisition module is specifically used to send a pre-awareness request message to the target edge cloud node related to the client when the object information of the target object meets the object filtering conditions; when the request message type in the pre-awareness request message is a redirection type, the target edge cloud node constructs a redirection data message based on the pre-awareness request message and sends the redirection data message to the edge cloud auxiliary node; and acquires the data cache query result received by the target edge cloud node from the edge cloud auxiliary node for the pre-awareness request message.

[0254] In one embodiment, the data acquisition module is specifically used to send a data request message to the target edge cloud node when the target cache result indicates that the target edge cloud node has cached target interface data; the data request message includes the target data identifier and the target cache result; and to receive the target interface data fed back by the target edge cloud node.

[0255] In one embodiment, the data acquisition module is specifically used to obtain the target data loading method of the target data identifier from the data cache query results when the target cache result indicates that the target edge cloud node has not cached the target interface data; and to obtain the target interface data through the target data loading method.

[0256] In one embodiment, the data acquisition module is specifically used to send a data request message to the target edge cloud node when the target data loading method is characterized by data loading through the target edge cloud node, so that the target edge cloud node can obtain the target interface data from the cache edge cloud node; the data request message includes the target data identifier and the target cache result; the cache edge cloud node caches the target interface data; and receives the target interface data fed back by the target edge cloud node.

[0257] In one embodiment, the data acquisition module is specifically used to obtain the address and port number of the cached edge cloud node from the data cache query results when the target data loading method is characterized by data loading through the cached edge cloud node; the cached edge cloud node caches the target interface data; based on the address and port number of the cached edge cloud node, send a data request message to the cached edge cloud node; the data request message includes the target data identifier and the data caching result of the cached edge cloud node for the target interface data; and receive the target interface data fed back by the cached edge cloud node.

[0258] In one embodiment, the data acquisition device further includes a data caching processing module;

[0259] The data caching processing module is used to delete the target cache result from the data cache query result after the target interface data is displayed on the target interface; or, for each prediction interface data, after the timeout threshold matched by the prediction interface data is reached, delete the cache result corresponding to the data identifier of each prediction interface data from the data cache query result.

[0260] In one embodiment, such as Figure 16 As shown, a cached data query device is provided, deployed on an edge cloud auxiliary node, including: a data packet receiving module 1602, a data identifier extraction module 1604, a cached data query module 1606, and a cached result feedback module 1608, wherein:

[0261] The data packet receiving module 1602 is used to receive redirected data packets sent by the target edge cloud node; the redirected data packet includes at least: a pre-awareness request packet sent by the client to the target edge cloud node;

[0262] The data identifier extraction module 1604 is used to extract the data identifier of each prediction interface data from the pre-sensing request message.

[0263] The cached data query module 1606 is used to query the cache status of each prediction interface data at each edge cloud node based on the data identifier of each prediction interface data, determine the cache result corresponding to the data identifier of each prediction interface data, and construct the data cache query result.

[0264] The cached result feedback module 1608 is used to send the data cache query results to the target edge cloud node, so that the target edge cloud node can feed back the data cache query results to the client.

[0265] In one embodiment, the cached data query module is specifically used to query the caching status of each prediction interface data at each edge cloud node based on the data identifier of each prediction interface data, and determine the target caching status on the target edge cloud node; based on the target caching status of each prediction interface data, determine the caching result corresponding to the data identifier of each prediction interface data.

[0266] In one embodiment, the cached data query module is specifically used to, for each predicted interface data, determine the cache result of the data identifier of the predicted interface data to indicate that the target edge cloud node has cached the predicted interface data, if the target caching situation indicates that the target edge cloud node has cached the predicted interface data; and for each predicted interface data, determine the cache result of the data identifier of the predicted interface data to indicate that the target edge cloud node has not cached the target interface data, if the target caching situation indicates that the target edge cloud node has not cached the target interface data.

[0267] In one embodiment, the cached data query module is further configured to: determine the cached edge cloud node that caches the predicted interface data when the target edge cloud node does not cache the target interface data; obtain the first latency of the client obtaining the predicted interface data through the target edge cloud node and the second latency of the client obtaining the predicted interface data through the cached edge cloud node; and determine the data loading method of the data identifier of the predicted interface data based on the first latency and the second latency; wherein, when the target edge cloud node does not cache the target interface data, the data cache query result also includes: the data loading method of the predicted interface data.

[0268] In one embodiment, the cached data query module is specifically used to load data by the client requesting predicted interface data from the cached edge cloud node through the target edge cloud node when the first delay is less than or equal to the second delay; and to load data by the client requesting predicted interface data from the cached edge cloud node when the first delay is less than or greater than the second delay. Wherein, when the data loading method represents the client requesting predicted interface data from the cached edge cloud node, the data cache query result also includes the address and port number of the cached edge cloud node.

[0269] In one embodiment, a computer device is provided, which can be a server or a terminal. This embodiment uses a server as an example for description, and its internal structure diagram is as follows: Figure 17 As shown, the computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage medium. The database stores interface data and cached query results, as well as other data related to the embodiments of this application. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network connection. When executed by the processor, the computer program implements a data acquisition method and a cached data query method.

[0270] Those skilled in the art will understand that Figure 17 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0271] In one embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0272] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the steps in the above method embodiments.

[0273] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0274] It should be noted that the data acquisition (including but not limited to object device information, object personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the object or fully authorized by all parties, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0275] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data acquisition logic devices, etc., and are not limited to these.

[0276] The technical features in the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0277] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for data acquisition, characterized in that, The method is applied to a client, and the method includes: Display the browsing interface that the target object is browsing, determine the set of prediction interfaces related to the browsing interface, and display the prediction interface data for each of the prediction interfaces. Send a pre-awareness request message to the target edge cloud node associated with the client, and obtain the data cache query result for the pre-awareness request message; the data cache query result includes at least the cache result corresponding to the data identifier of each of the prediction interface data; Determine the target interface triggered by the target object from the set of predicted interfaces, and determine the target data identifier of the target interface data of the target interface; Using the target data identifier, obtain the target cache result of the target data identifier from the data cache query result; The target interface data is obtained through the target cache result and displayed on the target interface.

2. The method according to claim 1, characterized in that, Sending a pre-awareness request message to the target edge cloud node associated with the client includes: If the object information of the target object meets the object filtering conditions, a pre-sensing request message is sent to the target edge cloud node related to the client. The step of obtaining the data cache query result for the pre-sensing request message includes: If the request message type in the pre-sensing request message is a redirection type, the target edge cloud node constructs a redirection data message based on the pre-sensing request message and sends the redirection data message to the edge cloud auxiliary node. Obtain the data cache query results of the pre-sensing request message received by the target edge cloud node from the edge cloud auxiliary node.

3. The method according to claim 1, characterized in that, The step of obtaining the target interface data through the target cache result includes: If the target cache result indicates that the target edge cloud node has cached the target interface data, a data request message is sent to the target edge cloud node; the data request message includes the target data identifier and the target cache result. Receive the target interface data fed back by the target edge cloud node.

4. The method according to claim 1, characterized in that, The step of obtaining the target interface data through the target cache result includes: If the target cache result indicates that the target edge cloud node does not cache the target interface data, the target data loading method of the target data identifier is obtained from the data cache query result; The target interface data is obtained through the target data loading method.

5. The method according to claim 4, characterized in that, The step of obtaining the target interface data through the target data loading method includes: When the target data loading method is characterized by loading data through a target edge cloud node, a data request message is sent to the target edge cloud node so that the target edge cloud node can obtain the target interface data from the cache edge cloud node; the data request message includes the target data identifier and the target cache result; the cache edge cloud node caches the target interface data; Receive the target interface data fed back by the target edge cloud node.

6. The method according to claim 4, characterized in that, The step of obtaining the target interface data through the target data loading method includes: When the target data loading method is characterized by loading data through a cached edge cloud node, the address and port number of the cached edge cloud node are obtained from the data cache query results; the cached edge cloud node caches the target interface data. Based on the address and port number of the cache edge cloud node, a data request message is sent to the cache edge cloud node; the data request message includes the target data identifier and the data caching result of the cache edge cloud node for the target interface data; Receive the target interface data fed back by the cache edge cloud node.

7. The method according to any one of claims 1 to 6, characterized in that, The method further includes: After the target interface data is displayed on the target interface, the target cache result is deleted from the data cache query result; Alternatively, for each prediction interface data, after reaching the timeout threshold matched by the prediction interface data, the cached result corresponding to the data identifier of each prediction interface data is deleted from the data cache query result.

8. A method for caching data retrieval, characterized in that, The method is applied to edge cloud auxiliary nodes, and the method includes: Receive a redirected data packet sent by the target edge cloud node; the redirected data packet includes at least: a pre-awareness request packet sent by the client to the target edge cloud node; Extract the data identifier of each prediction interface data from the pre-sensing request message; Based on the data identifier of each prediction interface data, a data query is performed on the caching status of each prediction interface data at each edge cloud node to determine the caching result corresponding to the data identifier of each prediction interface data, and a data caching query result is constructed. The data cache query result is sent to the target edge cloud node so that the target edge cloud node can return the data cache query result to the client.

9. The method according to claim 8, characterized in that, The step of querying the cache status of each prediction interface data at each edge cloud node based on its respective data identifier to determine the cache result corresponding to the data identifier of each prediction interface data includes: For each of the predicted interface data's respective data identifiers, a data query is performed on the caching status of each of the predicted interface data at each edge cloud node to determine the target caching status on the target edge cloud node; Based on the target caching status of each of the predicted interface data, the cache result corresponding to the data identifier of each of the predicted interface data is determined.

10. The method according to claim 9, characterized in that, The step of determining the cache result corresponding to the data identifier of each prediction interface data based on the target cache status of each prediction interface data includes: For each of the predicted interface data, if the target caching situation indicates that the target edge cloud node has cached the predicted interface data, the caching result of the data identifier of the predicted interface data is used to indicate that: the target edge cloud node has cached the predicted interface data. For each predicted interface data, if the target caching situation indicates that the target edge cloud node has not cached the predicted interface data, the caching result of the data identifier of the predicted interface data is determined to indicate that the target edge cloud node has not cached the target interface data.

11. The method according to claim 10, characterized in that, The method further includes: If the target edge cloud node does not cache the target interface data, determine the cached edge cloud node that caches the predicted interface data; The first latency for the client to obtain the prediction interface data through the target edge cloud node, and the second latency for the client to obtain the prediction interface data through the cache edge cloud node; Based on the first delay and the second delay, the data loading method of the data identifier of the prediction interface data is determined; wherein, when the target edge cloud node does not cache the target interface data, the data cache query result also includes: the data loading method of the prediction interface data.

12. The method according to claim 11, characterized in that, The data loading method for determining the data identifier of the prediction interface data based on the first delay and the second delay includes: If the first delay is less than or equal to the second delay, the client requests the prediction interface data from the cache edge cloud node through the target edge cloud node as the data loading method; If the first delay is less than or greater than the second delay, the client requests the prediction interface data from the cache edge cloud node as the data loading method. Wherein, when the data loading method represents the client requesting the prediction interface data from the cache edge cloud node, the data cache query result also includes: the address and port number of the cache edge cloud node.

13. A data acquisition device, characterized in that, The device is deployed on a client side, and the device includes: The interface data processing module is used to display the browsing interface that the target object is browsing, determine the set of prediction interfaces related to the browsing interface, and display prediction interface data in each of the prediction interfaces. The cache query result acquisition module is used to send a pre-sensing request message to the target edge cloud node related to the client, and acquire the data cache query result for the pre-sensing request message; the data cache query result includes at least the cache result corresponding to the data identifier of each of the prediction interface data; The interface data determination module is used to determine the target interface triggered by the target object from the predicted interface set, and to determine the target data identifier of the target interface data of the target interface. The cache result acquisition module is used to obtain the target cache result of the target data identifier from the data cache query result using the target data identifier; The data acquisition module is used to acquire the target interface data through the target cache result and display the target interface data on the target interface.

14. A cached data query device, characterized in that, The device is deployed on an edge cloud auxiliary node, and the device includes: A data packet receiving module is used to receive redirected data packets sent by a target edge cloud node; the redirected data packet includes at least: a pre-awareness request packet sent by the client to the target edge cloud node; The data identifier extraction module is used to extract the data identifier of each prediction interface data from the pre-sensing request message. The cached data query module is used to query the cache status of each prediction interface data at each edge cloud node based on the data identifier of each prediction interface data, determine the cache result corresponding to the data identifier of each prediction interface data, and construct the data cache query result. The cache result feedback module is used to send the data cache query result to the target edge cloud node, so that the target edge cloud node will feed back the data cache query result to the client.

15. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 12.

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