App startup page management method, device, equipment and medium

Abstract

The application discloses a kind of App startup page management method, device, equipment and medium.The method comprises: according to the network interaction information that App is started and carries out initial business processing with server, determine the network transmission delay parameter generated by App and server signaling transmission and the signaling processing delay parameter generated by server to signaling processing;According to the login account information of App, determine the display influencing factor of startup page, and determine the corresponding influencing factor delay parameter according to the display influencing factor of startup page;According to network transmission delay parameter, signaling processing delay parameter and influencing factor delay parameter, determine the startup time consumption estimation result of App, and determine the startup page of App according to startup time consumption estimation result.The technical scheme of the application, by the network interaction information of initial business processing, the countdown display of startup page is dynamically adjusted, and the accuracy of startup time consumption estimation result is improved.

Description

Technical Field

[0001] This invention relates to the field of App development technology, and in particular to a method, apparatus, device, and medium for managing App launch pages. Background Technology

[0002] With the widespread use of mobile applications (Apps) and the development of cloud server computing technology, more and more Apps rely on accessing cloud servers to perform their functions. For example, when an App starts, users typically need to log in to their account to retrieve the App's homepage display information associated with their account from the cloud server.

[0003] Due to network transmission and server deployment delays, the display of information on the app's homepage is often delayed. A common technique is to display a countdown timer on the app's launch screen as a transition. Currently, a fixed-length countdown timer is used as the launch screen, which cannot be dynamically adjusted based on the actual scenario. Furthermore, the fixed countdown timer often doesn't match the actual time required for the app to launch, resulting in the homepage information not being fully prepared by the end of the countdown, thus negatively impacting the user experience. Summary of the Invention

[0004] This invention provides a method, apparatus, device, and medium for managing App launch pages, in order to solve the problem of inaccurate countdowns on App launch pages.

[0005] According to one aspect of the present invention, a method for managing an App launch page is provided, comprising:

[0006] Based on the network interaction information between the App and the server during the initial business processing after the App starts, determine the network transmission delay parameters generated by the signaling transmission between the App and the server and the signaling processing delay parameters generated by the server processing the signaling.

[0007] The factors affecting the display of the launch page are determined based on the App's login account information, and the corresponding delay parameters for these factors are determined based on these factors.

[0008] The estimated startup time of the App is determined based on the network transmission delay parameter, the signaling processing delay parameter, and the influencing factor delay parameter, and the startup page of the App is determined based on the estimated startup time.

[0009] According to another aspect of the present invention, a management device for an App launch page is provided, comprising:

[0010] The interaction parameter determination module is used to determine the network transmission delay parameters generated by the signaling transmission between the App and the server and the signaling processing delay parameters generated by the server processing the signaling, based on the network interaction information between the App and the server during the initial business processing after the App starts.

[0011] The account parameter determination module is used to determine the factors affecting the display of the launch page based on the login account information of the App, and to determine the corresponding delay parameters of the factors affecting the display of the launch page based on the factors affecting the display of the launch page.

[0012] The launch page determination module is used to determine the estimated launch time of the App based on the network transmission delay parameter, the signaling processing delay parameter, and the influencing factor delay parameter, and to determine the launch page of the App based on the estimated launch time.

[0013] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0014] At least one processor; and

[0015] A memory communicatively connected to the at least one processor; wherein,

[0016] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the App launch page management method according to any embodiment of the present invention.

[0017] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions, the computer instructions being configured to cause a processor to execute and implement the APP launch page management method according to any embodiment of the present invention.

[0018] The technical solution of this invention dynamically adjusts the countdown display on the startup page using network interaction information from the initial business processing, improving the accuracy of the startup time estimation. Furthermore, because the initial business processing time is very short, it ensures that the startup page is prepared without the user's awareness. The startup time estimation also incorporates the effects of real-time network conditions, server real-time response speed, and account-related special requirements, further improving the accuracy of the estimation and avoiding unnecessary waiting time and the unpleasant user experience caused by the countdown ending before the homepage content is fully prepared.

[0019] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a flowchart of a method for managing an App launch page according to Embodiment 1 of the present invention;

[0022] Figure 2 This is a flowchart of another method for managing an App launch page according to Embodiment 2 of the present invention;

[0023] Figure 3 This is a timing diagram of the interaction between an App and an edge server and a cloud server after the App is launched, according to Embodiment 2 of the present invention.

[0024] Figure 4 This is a schematic diagram of the structure of an App launch page management device according to Embodiment 3 of the present invention;

[0025] Figure 5 This is a schematic diagram of the structure of an electronic device that implements the APP launch page management method of this embodiment of the invention. Detailed Implementation

[0026] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0027] It should be noted that the terms "candidate," "target," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0028] Example 1

[0029] Figure 1 This is a flowchart illustrating a method for managing an App launch page according to Embodiment 1 of the present invention. This embodiment is applicable to situations where the countdown display information of an App launch page needs to be determined. This method can be executed by an App launch page management device, which can be implemented in hardware and / or software. The App launch page management device can be configured on a mobile device such as a smartphone with the App installed, or installed on a server. Figure 1 As shown, the method includes:

[0030] S110. Based on the network interaction information between the App and the server for the initial business processing after the App starts, determine the network transmission delay parameters generated by the signaling transmission between the App and the server and the signaling processing delay parameters generated by the server processing the signaling.

[0031] After logging in, the app needs to undergo multiple business processing interactions with the server to obtain the complete homepage display information. If no intermediate edge server is deployed, the app directly interacts with the cloud server multiple times to obtain the complete homepage display information. If an intermediate edge server is deployed, the app, after logging in, uses the corresponding edge server as an intermediate signaling forwarder to interact with the cloud server. The edge server's forwarding and simple processing of signaling reduces the access pressure on the cloud server, improving the app's login efficiency. The number of business processing interactions between the app and the server upon login is pre-determined based on the app's homepage display information.

[0032] Initial business processing refers to the business processing interaction between the App and the cloud server or edge server caused by the first signaling issued by the App. Network interaction information refers to the time information of each end sending and receiving signaling during the interaction between the App and the server. Network transmission latency parameters refer to the latency parameters caused by signaling transmission between the sending and receiving signaling ends, such as the latency parameters caused by network transmission during the process of the App sending signaling to the cloud server. Signaling processing latency parameters refer to the latency parameters caused by the edge server or cloud server itself processing the signaling, such as the latency parameters caused by the edge server forwarding the signaling, or the latency parameters caused by the cloud server parsing and processing the received signaling and replying.

[0033] For example, if the App interacts directly with the cloud server, the process of the App sending the first signaling to the cloud server is defined as the first process; the process of the cloud server receiving and processing the first signaling is defined as the second process; and the process of the cloud server returning the signaling processing result to the App is defined as the third process. Then, the network transmission delay parameter is determined based on the first and third processes, and the signaling processing delay parameter is determined based on the second process. For instance, the first time the App sends the first signaling, the second time the cloud server receives the signaling, the third time the cloud server sends the signaling processing result, and the fourth time the App receives the signaling processing result are determined. The first time difference between the third and second times is determined, and the signaling processing delay parameter is determined based on this first time difference. The second time difference between the fourth and first times is determined, and the network transmission delay parameter is determined based on the difference between the second and first time differences.

[0034] The signaling processing delay parameter can be determined by the server and sent to the App as part of the signaling processing result. The App then determines the network transmission delay parameter based on this parameter. Alternatively, the server can directly include the network interaction information from the initial service processing in the signaling processing result and send it to the App, allowing the App to determine both the signaling processing delay parameter and the network transmission delay parameter. This embodiment of the invention does not limit the calculation end for the signaling processing delay parameter and the network transmission delay parameter. If the App is the calculation end, the corresponding time information is sent to the App; if the server is the calculation end, the corresponding time information is sent to the server; if both the App and the server are calculation ends, each end calculates the corresponding delay parameter and finally sends the delay parameter to the App.

[0035] Optionally, since the impact of real-time network status on the speed of business processing interaction varies greatly, while the server's signaling processing speed can be considered constant, the signaling processing delay parameter can be a fixed value determined based on the server's historical processing speed to improve the efficiency of the startup page determination.

[0036] S120. Determine the factors affecting the display of the startup page based on the App's login account information, and determine the corresponding delay parameters for the factors affecting the display of the startup page.

[0037] The factors affecting the startup page display refer to content related to the login account information that affects the information displayed on the homepage, such as fixed content bound to the account. This fixed content needs to be displayed on the homepage after startup, which will have a certain impact on the business processing interaction between the App and the server. The server needs to obtain the fixed content bound to the account to display on the App's homepage, which will inevitably bring some additional delay.

[0038] Specifically, the login account information is determined based on the App's login information, the bound fixed content is determined based on the login account information, the influencing factors of the launch page display related to the homepage display are determined based on the bound fixed content, and the influencing factor delay parameters required to display the influencing factors are calculated based on the influencing factors of the launch page display.

[0039] To reduce the computational load on the app, the delay parameters for influencing factors are determined by the server and sent to the app. For example, the app sends its login account information to the server and retrieves the delay parameters for influencing factors from the server. These delay parameters are determined by the server based on the influencing factors displayed on the launch page, which in turn are determined by the server based on the app's login account information.

[0040] S130. Determine the estimated startup time of the App based on the network transmission delay parameters, signaling processing delay parameters, and influencing factor delay parameters, and determine the startup page of the App based on the estimated startup time.

[0041] Network transmission latency parameter characterizes the impact of actual network conditions on the App's homepage display, signaling processing latency parameter characterizes the impact of server real-time data processing efficiency on the App's homepage display, and influencing factor latency parameter determines the impact of additional account content on the App's homepage display. Based on the joint determination of these three parameters, the App's startup time estimation result is improved, making the startup time estimation result more consistent with the user's current state when launching the App.

[0042] Specifically, a first delay parameter is determined by multiplying the sum of network transmission delay parameters and signaling processing delay parameters by the total number of App interactions. The startup time estimate is then determined by the sum of the first delay parameter and influencing factor delay parameters. Finally, the countdown display on the App's startup page is determined based on this startup time estimate. This ensures the countdown time better aligns with the user's current business scenario, and the countdown end time more closely matches the time it takes for the homepage information to be fully prepared. The total number of App interactions refers to the total number of business processing interactions the App needs to perform with the server to complete login.

[0043] The technical solution of this invention dynamically adjusts the countdown display on the startup page using network interaction information from the initial business processing, improving the accuracy of the startup time estimation. Furthermore, because the initial business processing time is very short, it ensures that the startup page is prepared without the user's awareness. The startup time estimation also incorporates the effects of real-time network conditions, server real-time response speed, and account-related special requirements, further improving the accuracy of the estimation and avoiding unnecessary waiting time and the unpleasant user experience caused by the countdown ending before the homepage content is fully prepared.

[0044] Example 2

[0045] Figure 2 This is a flowchart of a method for managing an App launch page according to Embodiment 2 of the present invention. This embodiment further refines the server in the above embodiment, which includes an edge server and a cloud server; the network transmission delay parameters include a first network transmission delay parameter and a second network transmission delay parameter, and the signaling processing delay parameters include an edge processing delay parameter and a cloud processing delay parameter.

[0046] In this context, a cloud server refers to the target server that processes the signaling sent by the app, while an edge server refers to a local server deployed in various regions that can forward the signaling sent by the app and perform simple processing operations. For example, the nearest edge server is determined based on the app's login address. The app interacts with the edge server, and the edge server interacts with the cloud server, thereby completing the business processing interaction between the app and the cloud server. Figure 3 The diagram shows a timing sequence of interactions between an app and an edge server and a cloud server after the app starts. The first network transmission delay parameter represents the delay caused by network transmission between the app and the edge server; the second network transmission delay parameter represents the delay caused by network transmission between the edge server and the cloud server; the edge processing delay parameter represents the response delay caused by the edge server processing signaling; and the cloud processing delay parameter represents the response delay caused by the cloud server processing signaling.

[0047] like Figure 2 As shown, the method includes:

[0048] S210. Based on the first network interaction information between the App and the edge server for initial business processing after the App starts, and the second network interaction information between the edge server and the cloud server for initial business processing, determine the first network transmission delay parameter generated by the signaling transmission between the App and the edge server, the second network transmission delay parameter generated by the signaling transmission between the edge server and the cloud server, the edge processing delay parameter generated by the edge server processing the signaling, and the cloud processing delay parameter generated by the cloud server processing the signaling.

[0049] The first network interaction information refers to the time information of each end sending and receiving signaling when the App and the edge server interact; the second network interaction information refers to the time information of each end sending and receiving signaling when the edge server and the cloud server interact.

[0050] Specifically, the edge processing delay parameter generated by the edge server processing the signaling is determined based on the first network interaction information; the cloud processing delay parameter generated by the cloud server processing the signaling is determined based on the second network interaction information; the second network transmission delay parameter is determined based on the second network interaction information and the cloud processing delay parameter; and the first network transmission delay parameter is determined based on the first network interaction information, the edge processing delay parameter, the cloud processing delay parameter, and the second network transmission delay parameter.

[0051] For example, such as Figure 3 As shown, the process of the App interacting with the cloud server through the edge server is as follows: Step 1 is the process of the App sending the first signaling to the edge server; Step 2 is the process of the edge server receiving and processing the first signaling; Step 3 is the process of the edge server sending the first signaling to the cloud server; Step 4 is the process of the cloud server processing the first signaling; Step 5 is the process of the cloud server returning the signaling processing result to the edge server; Step 6 is the process of the edge server processing the signaling processing result; and Step 7 is the process of the edge server sending the signaling processing result back to the App.

[0052] Edge processing latency parameters are used to characterize the total processing time of the edge server itself during the initial business processing, such as... Figure 3 The sum of the time consumed in steps 2 and 6 of the initial business processing interaction between the App and the edge server / cloud server is the edge processing latency parameter. Specifically, the first time when the edge server corresponding to step 2 receives the signaling sent by the App and the second time when the edge server corresponding to step 2 sends the signaling to the cloud server are determined in the first business processing interaction. The first time difference is determined based on the time difference between the first time and the second time. The third time when the edge server corresponding to step 6 receives the signaling processing result sent by the cloud server and the fourth time when the edge server corresponding to step 6 sends the signaling processing result to the App are determined in the first business processing interaction. The second time difference is determined based on the time difference between the third time and the fourth time. The sum of the first time difference and the second time difference is the edge processing latency parameter for the initial business processing interaction. At the same time, since the work done by the edge server is generally forwarding signaling, the forwarding time can be simplified to a constant to reduce the time consumed by latency calculation. The constant value can be determined based on historical values, for example, set to 10ms.

[0053] The cloud processing latency parameter is used to characterize the total processing time of the cloud server itself during the initial business processing, such as... Figure 3The sum of the time consumed in step 4 during the initial business interaction between the App and the edge server and cloud server is the cloud processing latency parameter. Specifically, the fifth time when the cloud server receives the signaling sent by the edge server in step 4 of the first business interaction is determined, and the sixth time when the cloud server sends the signaling processing result to the edge server is determined. The third time difference is determined based on the time difference between the fifth time and the sixth time, and the third time difference is the cloud processing latency parameter.

[0054] The second network transmission latency parameter is used to characterize the network latency between the edge server and the cloud server, such as... Figure 3 The sum of the time consumed in steps 3 and 5 during the initial business interaction between the App and the edge server and cloud server is the second network transmission delay parameter. Specifically, the seventh time when the edge server sends the signaling to the cloud server in step 3 of the first business interaction is determined, and the eighth time when the edge server receives the signaling processing result sent by the cloud server in step 5 is determined. The fourth time difference is determined based on the eighth time and the seventh time, and the second network transmission delay parameter is determined based on the difference between the fourth time difference and the cloud processing delay parameter.

[0055] The first network transmission latency parameter is used to characterize the network latency between the App and the edge server, such as... Figure 3 The sum of the time consumed in steps 1 and 7 during the initial business interaction between the App and the edge server and cloud server is the first network transmission delay parameter. Specifically, the ninth time when the App sends the signaling to the edge server in step 1 of the first business interaction is determined, and the tenth time when the App receives the signaling processing result sent by the edge server in step 7 is determined. The fifth time difference is determined based on the tenth time and the ninth time. The first network transmission delay parameter is determined based on the result of subtracting the fourth time difference and the edge processing delay parameter from the fifth time difference.

[0056] Optionally, the edge processing delay parameter and the second network transmission delay parameter can be determined by the edge server and sent to the App. The cloud processing delay parameter can be determined by the cloud server and sent to the App via the edge server. The first network transmission delay parameter can be determined by the App itself. Optionally, the server directly carries the network interaction information of the initial service processing in the signaling processing result and sends it to the App, whereby the App determines the first network transmission delay parameter, the second network transmission delay parameter, the edge processing delay parameter, and the cloud processing delay parameter. This embodiment of the invention does not limit the calculation end of the signaling processing delay parameter and the network transmission delay parameter. If the App is the calculation end, the corresponding time information is sent to the App. If the edge server or the cloud server is the calculation end, the corresponding time information is sent to the edge server or the cloud server. If the App, the edge server, and the cloud server are all calculation ends, each end calculates the corresponding delay parameter and finally sends the delay parameter to the App.

[0057] S220. Determine the factors affecting the display of the startup page based on the App's login account information, and determine the corresponding delay parameters for the factors affecting the display of the startup page.

[0058] In one feasible embodiment, the factors influencing the display of the launch page include at least fixed information associated with the account.

[0059] Accordingly, the delay parameters for the influencing factors are determined based on the influencing factors displayed on the startup page, including:

[0060] The delay parameter, which is the first influencing factor for displaying fixed account-related information, is determined based on the account-associated fixed display information.

[0061] Among them, the fixed display information associated with an account refers to the information that needs to be displayed on the homepage associated with that account. The fixed display information associated with an account is determined according to the user's settings to ensure the user's personalized needs. For example, the fixed display information associated with an account may include the number of items followed by the account, such as the number of stocks followed by the account.

[0062] The time taken to display a single fixed piece of information is predetermined, and the delay parameter of the first influencing factor is determined by multiplying the time taken to display a single fixed piece of information by the time taken to display fixed information associated with the account.

[0063] By using account-linked fixed display information to determine the delay parameters, the startup time estimation results include the delay caused by the display of users' personalized settings, rather than just the delay caused by the display of general information for all users, thus further improving the accuracy of the startup time estimation results.

[0064] In one feasible embodiment, the account association information is fixed to the number of managed devices associated with the account;

[0065] Accordingly, based on the fixed display information associated with the account, the delay parameter for the first influencing factor affecting the display of the fixed display information associated with the account is determined, including:

[0066] The delay parameter for the first influencing factor is determined based on the number of managed devices and the business preparation time for a single device.

[0067] Here, the App refers to a device management App. The number of managed devices associated with an account refers to the number of managed devices bound to the device management App. For example, if the App is a surveillance camera management software, the number of managed devices associated with an account is the number of cameras bound to the App's login account; or if the App is a home device smart management software, the number of managed devices associated with an account is the number of home smart devices bound to the App's login account, such as the total number of robot vacuum cleaners, curtain devices, and lighting devices.

[0068] The preparation time for a single device is determined based on the business readiness time of the managed devices. This preparation time can be determined based on empirical or historical values. Then, the delay parameter of the first influencing factor is determined by multiplying the number of managed devices by the preparation time of a single device. For example, the delay parameter D_device = numOfAirDevices * t0 is the estimated processing time for displaying information related to the managed devices associated with the account on the homepage, where numOfAirDevices is the number of managed devices associated with the account, and t0 is the preparation time of a single device, which represents the business readiness time of the managed device (such as P2P time). The initial value can be set to 0.5 seconds.

[0069] In one feasible embodiment, the influencing factors displayed on the launch page include at least regional restriction influencing factors and / or user-personalized influencing factors;

[0070] Accordingly, the delay parameters for the influencing factors are determined based on the influencing factors displayed on the startup page, including:

[0071] Determine the time delay parameter of the second influencing factor generated by the regional limitation influence factor based on the regional limitation influence factor; and / or

[0072] The delay parameter of the third influencing factor generated by the user-personalized influencing factor is determined based on the user-personalized influencing factor.

[0073] Among them, the regional restriction impact factor is used to characterize the special requirements for homepage display corresponding to the user's login region; for example, the regional display impact factor is the number of regional target policies displayed, that is, the number of target policies that are additionally displayed on the homepage of the App when the user logs in the target region.

[0074] User personalization influencing factors are used to characterize the personalized display needs of individual users on their homepages; for example, user personalization influencing factors include the number of target ad displays, which is the number of target ads that are additionally displayed on the homepage of the target user's app.

[0075] Specifically, the estimated latency is determined based on the regional display impact factor, serving as the second impact factor latency parameter; and the estimated latency is determined based on the user's personalized impact factor, serving as the third impact factor latency parameter. For example, latency parameters are determined based on the region and the user's personalized customization needs, which are then reflected in the final startup time estimation result, improving the accuracy of the startup time estimation result.

[0076] For example, the delay parameters for the first, second, and third influencing factors are determined by the cloud server and sent to the app via the edge server. When the app starts, it sends a login request to the cloud server via the edge server. This login request includes the user's IP address and account information. After receiving the request, the cloud server resolves the user's geographical location through the IP address, determines the regional restriction influencing factor based on the geographical location, and determines the user's personalized influencing factor based on the account information.

[0077] S230. Determine the first network influence weight and the second network influence weight; determine the first delay parameter based on the product of the first network influence weight and the first network transmission delay parameter; determine the second delay parameter based on the product of the second network influence weight and the second network transmission delay parameter; determine the total interaction delay parameter based on the product of the sum of the first delay parameter and the second delay parameter and the total number of App interactions; determine the total processing delay parameter based on the product of the sum of the edge processing delay parameter and the cloud processing delay parameter and the total number of App interactions; determine the estimated startup time of the App based on the sum of the total interaction delay parameter, the total processing delay parameter, and the delay parameters of the influencing factors.

[0078] Since the first network transmission latency parameter represents the network latency between the App and the edge server, and the second network transmission latency parameter represents the network latency between the edge server and the cloud server, and network stability varies between different devices, corresponding weights are assigned to the first and second network transmission latency parameters to balance network stability across different devices. The weights for the first and second network impacts can be determined empirically; for example, the initial value can be set to equal the first network impact weight and the second network impact weight, which equals 0.5, meaning the sum of the first and second network impact weights is 1. The total number of App interactions is... Figure 3 n in the context.

[0079] The estimated startup time of the app is determined using the following formula:

[0080] T=(a*D_edge+b*D_backbone)*I_interaction+(OpTime_edge+OpTime_backbone)*I_interaction+t;

[0081] Where T represents the estimated startup time, D_edge represents the first network transmission latency parameter, a represents the first network influence weight, b represents the second network influence weight, D_backbone represents the second network transmission latency parameter, I_interaction represents the total number of App interactions, OpTime_edge represents the edge processing latency parameter, OpTime_backbone represents the cloud processing latency parameter, and t represents the influencing factor latency parameter.

[0082] Optionally, the estimated startup time of the app can be determined according to the following formula:

[0083] T=(a*D_edge+b*D_backbone)*I_interaction+(OpTime_edge+OpTime_backbone)*I_interaction+D_device+R_region+U_user;

[0084] Where D_device represents the delay parameter of the first influencing factor, R_region represents the delay parameter of the second influencing factor, and U_user represents the delay parameter of the third influencing factor.

[0085] S240. Determine the App's launch page based on the estimated startup time.

[0086] Calculate the final estimated startup time T and use it as the countdown time for the App's startup page.

[0087] In one feasible embodiment, after determining the App's launch page based on the estimated launch time, the method further includes:

[0088] Determine the actual startup time of the app;

[0089] Determine whether to optimize the influence weights of the first network and the second network based on the periodic statistical results of the actual startup time and the estimated startup time.

[0090] If so, determine the direction and amount of weight optimization, and update the periodic statistical results of the actual startup time and startup time prediction based on the optimized first network influence weight and second network influence weight.

[0091] The direction and amount of weight optimization are updated based on the updated periodic statistical results.

[0092] After the app launches, it determines the actual launch time and sends it to the server. The server periodically analyzes the actual launch time and the estimated launch time to obtain periodic statistical results. For example, the periodic statistical results are the mean squared deviation of the actual launch time and the estimated launch time.

[0093] If the periodic statistical results indicate a large deviation between the actual startup time and the estimated startup time, such as a mean squared error greater than a preset threshold, then it is determined that the influence weights of the first and second networks should be optimized. If the periodic statistical results indicate a small deviation between the actual startup time and the estimated startup time, such as a mean squared error less than or equal to a preset threshold, then it is determined that the influence weights of the first and second networks should not be optimized.

[0094] Since the network between the edge server and the cloud server is relatively more stable, while the network between the app and the edge server is more volatile, the initial weight optimization direction is determined to be to increase the influence weight of the first network and decrease the influence weight of the second network. The optimization amount is a preset step size, such as 0.05. The step size can be adjusted according to the actual situation and is not restricted here.

[0095] The adjusted first and second network influence weights are sent to the App, allowing the App to redetermine the startup time estimate based on these optimized weights. The App continues to statistically analyze the startup time estimate and actual startup time at preset intervals, determining updated periodic statistical results. If the updated periodic statistical results show a decrease in the deviation between the actual and estimated startup time (e.g., the mean squared error is greater than a preset threshold but less than the mean squared error of the previous periodic statistical results), the weight optimization direction remains unchanged, the optimization amount is increased, and periodic statistics continue until the updated periodic statistical results show a small deviation. Conversely, if the updated periodic statistical results show an increase in the deviation between the actual and estimated startup time (e.g., the mean squared error is greater than a preset threshold and greater than the mean squared error of the previous periodic statistical results), the weight optimization direction is adjusted: the first network influence weight is decreased, the second network influence weight is increased, the optimization amount is maintained, and periodic statistics continue until the updated periodic statistical results show a small deviation.

[0096] By optimizing the weight parameters, the impact of network fluctuations between different devices is reduced, and the accuracy of startup time estimation results is improved.

[0097] The technical solution of this invention determines the network transmission latency parameters and signaling processing latency parameters between the App, edge server, and cloud server, and determines the corresponding network impact weights based on the different network stability between different devices. This makes the startup time estimation result take into account the impact of the number of business interactions, network latency, server response latency, and the display latency of personalized account association requirements, thereby improving the accuracy of the startup time estimation result and thus improving the user experience.

[0098] Example 3

[0099] Figure 4 This is a schematic diagram of the structure of a management device for an App launch page provided in Embodiment 3 of the present invention. Figure 4 As shown, the device includes:

[0100] The interaction parameter determination module 410 is used to determine the network transmission delay parameters generated by the signaling transmission between the App and the server and the signaling processing delay parameters generated by the server processing the signaling, based on the network interaction information between the App and the server for the initial business processing after the App starts.

[0101] The account parameter determination module 420 is used to determine the factors affecting the display of the startup page based on the login account information of the App, and to determine the corresponding delay parameters of the factors affecting the display of the startup page.

[0102] The startup page determination module 430 is used to determine the estimated startup time of the App based on network transmission delay parameters, signaling processing delay parameters, and influencing factor delay parameters, and to determine the startup page of the App based on the estimated startup time.

[0103] The technical solution of this invention dynamically adjusts the countdown display on the startup page using network interaction information from the initial business processing, improving the accuracy of the startup time estimation. Furthermore, because the initial business processing time is very short, it ensures that the startup page is prepared without the user's awareness. The startup time estimation also incorporates the effects of real-time network conditions, server real-time response speed, and account-related special requirements, further improving the accuracy of the estimation and avoiding unnecessary waiting time and the unpleasant user experience caused by the countdown ending before the homepage content is fully prepared.

[0104] Optionally, the servers include edge servers and cloud servers; the network transmission latency parameters include a first network transmission latency parameter and a second network transmission latency parameter, and the signaling processing latency parameters include edge processing latency parameters and cloud processing latency parameters;

[0105] Correspondingly, the interaction parameter determination module is specifically used for:

[0106] Based on the first network interaction information between the App and the edge server for initial business processing after the App starts, and the second network interaction information between the edge server and the cloud server for initial business processing, the first network transmission delay parameter generated by the signaling transmission between the App and the edge server, the second network transmission delay parameter generated by the signaling transmission between the edge server and the cloud server, the edge processing delay parameter generated by the edge server processing the signaling, and the cloud processing delay parameter generated by the cloud server processing the signaling are determined.

[0107] Optionally, the factors displayed on the launch page should include at least the fixed information associated with the account.

[0108] Correspondingly, the account parameter determination module, including the first influencing factor delay parameter determination unit, is used for:

[0109] The delay parameter, which is the first influencing factor for displaying fixed account-related information, is determined based on the account-associated fixed display information.

[0110] Optionally, the account association information will always display the number of managed devices associated with the account;

[0111] Correspondingly, the unit for determining the delay parameter of the first influencing factor is specifically used for:

[0112] The delay parameter for the first influencing factor is determined based on the number of managed devices and the business preparation time for a single device.

[0113] Optionally, the influencing factors displayed on the launch page may include at least regional restriction influencing factors and / or user-personalized influencing factors;

[0114] Correspondingly, the account parameter determination module, including the other influencing factor delay parameter determination unit, is used for:

[0115] Determine the time delay parameter of the second influencing factor generated by the regional limitation influence factor based on the regional limitation influence factor; and / or

[0116] The delay parameter of the third influencing factor generated by the user-personalized influencing factor is determined based on the user-personalized influencing factor.

[0117] Optional, a startup page confirmation module, specifically used for:

[0118] Determine the influence weights of the first network and the second network;

[0119] The first delay parameter is determined by multiplying the first network influence weight and the first network transmission delay parameter.

[0120] The second delay parameter is determined by multiplying the second network influence weight and the second network transmission delay parameter.

[0121] The total interaction delay parameter is determined by multiplying the sum of the first delay parameter and the second delay parameter by the total number of App interactions.

[0122] The total processing latency parameter is determined by multiplying the sum of the edge processing latency parameter and the cloud processing latency parameter by the total number of App interactions.

[0123] The estimated startup time of the App is determined by summing the total interaction latency parameter, the total processing latency parameter, and the latency parameters of influencing factors.

[0124] Optionally, the device also includes a weight optimization module for...

[0125] After determining the app's launch page based on the estimated launch time,

[0126] Determine the actual startup time of the app;

[0127] Determine whether to optimize the influence weights of the first network and the second network based on the periodic statistical results of the actual startup time and the estimated startup time.

[0128] If so, determine the direction and amount of weight optimization, and update the periodic statistical results of the actual startup time and startup time prediction based on the optimized first network influence weight and second network influence weight.

[0129] The direction and amount of weight optimization are updated based on the updated periodic statistical results.

[0130] The App launch page management device provided in this embodiment of the invention can execute the App launch page management method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0131] The acquisition, storage, use, and processing of data in this application comply with relevant national laws and regulations and do not violate public order and good morals.

[0132] Example 4

[0133] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0134] Figure 5 A schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0135] like Figure 5 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0136] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0137] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as the management methods of the App launch page.

[0138] In some embodiments, the App launch page management method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the App launch page management method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to execute the App launch page management method by any other suitable means (e.g., by means of firmware).

[0139] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific reference products (ASSPs), systems-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transferring data and instructions to the storage system, the at least one input device, and the at least one output device.

[0140] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0141] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0142] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0143] The systems and technologies described herein can be implemented in computing systems that include back-end components (e.g., as data servers), or computing systems that include switching components (e.g., application servers), or computing systems that include front-end components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such back-end, switching, or front-end components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0144] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0145] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0146] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for managing an App launch page, characterized in that, The method includes: Based on the network interaction information between the App and the server during the initial business processing after the App starts, determine the network transmission delay parameters generated by the signaling transmission between the App and the server and the signaling processing delay parameters generated by the server processing the signaling. The factors affecting the display of the launch page are determined based on the App's login account information, and the corresponding delay parameters for these factors are determined based on these factors. The estimated startup time of the App is determined based on the network transmission delay parameter, the signaling processing delay parameter, and the influencing factor delay parameter, and the startup page of the App is determined based on the estimated startup time.

2. The method according to claim 1, characterized in that, in, The server includes an edge server and a cloud server; the network transmission delay parameters include a first network transmission delay parameter and a second network transmission delay parameter; the signaling processing delay parameters include an edge processing delay parameter and a cloud processing delay parameter. Accordingly, based on the network interaction information between the App and the server during the initial business processing after the App starts, the network transmission delay parameters generated by the signaling transmission between the App and the server and the signaling processing delay parameters generated by the server processing the signaling are determined, including: Based on the first network interaction information between the App and the edge server for initial business processing after the App starts, and the second network interaction information between the edge server and the cloud server for initial business processing, the first network transmission delay parameter generated by the signaling transmission between the App and the edge server, the second network transmission delay parameter generated by the signaling transmission between the edge server and the cloud server, the edge processing delay parameter generated by the edge server processing the signaling, and the cloud processing delay parameter generated by the cloud server processing the signaling are determined.

3. The method according to claim 1, characterized in that, The factors affecting the display of the launch page include at least the fixed display information associated with the account; Accordingly, based on the influencing factors displayed on the launch page, the corresponding influencing factor delay parameters are determined, including: The delay parameter, which is the first influencing factor for displaying the fixed display information associated with the account, is determined based on the fixed display information associated with the account.

4. The method according to claim 3, characterized in that, The account association information is fixed to display the number of managed devices associated with the account; Accordingly, based on the fixed display information associated with the account, a first influencing factor delay parameter is determined for displaying the fixed display information associated with the account, including: The delay parameter of the first influencing factor is determined based on the number of managed devices and the business preparation time of a single device.

5. The method according to claim 1, characterized in that, The factors displayed on the launch page include at least regional restriction factors and / or user-personalized factors. Accordingly, based on the influencing factors displayed on the launch page, the corresponding influencing factor delay parameters are determined, including: Determine the delay parameter of the second influencing factor generated by the regional limitation influence factor based on the regional limitation influence factor; and / or The delay parameter of the third influencing factor generated by the user personalization influencing factor is determined based on the user personalization influencing factor.

6. The method according to claim 2, characterized in that, The estimated startup time of the App is determined based on the network transmission delay parameters, the signaling processing delay parameters, and the influencing factor delay parameters, including: Determine the influence weights of the first network and the second network; The first delay parameter is determined by the product of the first network influence weight and the first network transmission delay parameter; The second delay parameter is determined by multiplying the second network influence weight and the second network transmission delay parameter. The total interaction delay parameter is determined by multiplying the sum of the first delay parameter and the second delay parameter by the total number of App interactions. The total processing latency parameter is determined by multiplying the sum of the edge processing latency parameter and the cloud processing latency parameter by the total number of App interactions. The estimated startup time of the App is determined based on the sum of the total interaction latency parameter, the total processing latency parameter, and the latency parameters of the influencing factors.

7. The method according to claim 6, characterized in that, After determining the App's launch page based on the estimated launch time, the method further includes: Determine the actual startup time of the app; Based on the periodic statistical results of the actual startup time and the startup time prediction results, determine whether to optimize the influence weights of the first network and the second network. If so, determine the direction and amount of weight optimization, and update the periodic statistical results of the actual startup time and the startup time prediction result based on the optimized first network influence weight and second network influence weight. The optimization direction and amount of the weights are updated based on the updated periodic statistical results.

8. A management device for an App launch page, characterized in that, The device includes: The interaction parameter determination module is used to determine the network transmission delay parameters generated by the signaling transmission between the App and the server and the signaling processing delay parameters generated by the server processing the signaling, based on the network interaction information between the App and the server during the initial business processing after the App starts. The account parameter determination module is used to determine the factors affecting the display of the launch page based on the login account information of the App, and to determine the corresponding delay parameters of the factors affecting the display of the launch page based on the factors affecting the display of the launch page. The launch page determination module is used to determine the estimated launch time of the App based on the network transmission delay parameter, the signaling processing delay parameter, and the influencing factor delay parameter, and to determine the launch page of the App based on the estimated launch time.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the management method of the App launch page according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, implement the management method for the App launch page as described in any one of claims 1-7.

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