Network connection method, connection system and storage medium

Abstract

The invention discloses a network connection method, a connection system and a storage medium. The network connection method comprises the following steps: determining the type of a current running application; determining a traffic demand level of the type according to the current bandwidth occupancy rate or the current network traffic rate; determining a Wi-Fi network signal strength switching threshold value according to the type and historical data of the current running application; and switching a network connection mode according to the traffic demand level and a Wi-Fi network signal strength switching threshold. Through the above mode, the network connection strategy can be dynamically adjusted in different traffic demand scenes, and performance improvement and energy consumption optimization are realized.

Description

Technical Field

[0001] The present application relates to the field of electronic circuits, and in particular to a network connection method, a connection system, and a storage medium. Background Art

[0002] Current mobile devices generally adopt a dual-network collaborative architecture of Wi-Fi and cellular networks to improve network availability. However, existing network connection technologies are limited by static decision-making logic and unbalanced resource adaptation, making it difficult to balance user experience and energy efficiency.

[0003] Existing network connection technologies usually switch networks based on basic indicators such as signal strength and packet loss rate, or fixed signal strength thresholds. They lack the ability to perceive the traffic characteristics of users' real-time business types and are prone to causing lag due to blindly switching to low-speed networks in high-bandwidth demand scenarios, or excessive consumption of data traffic in low-traffic demand scenarios. At the same time, in order to ensure network continuity, network switching is often frequent, resulting in increased device energy consumption. Summary of the Invention

[0004] To solve the above problems, the present application provides a network connection method, a connection system and a storage medium, which can dynamically adjust the network connection strategy according to real-time traffic demand and balance performance and resource consumption.

[0005] A technical solution adopted in this application is to provide a network connection method, the method comprising: determining the type of a currently running application; determining a traffic demand level of the type based on the current bandwidth occupancy rate or the current network traffic rate; determining a Wi-Fi network signal strength switching threshold based on the type and historical data of the currently running application; and switching the network connection mode based on the traffic demand level and the Wi-Fi network signal strength switching threshold.

[0006] In one embodiment, determining the type of the currently running application includes: obtaining a first type judgment result of the currently running application based on the currently active process, and calculating the confidence of the first type judgment result; obtaining a second type judgment result of the currently running application based on the current traffic characteristics, and calculating the matching degree between the second type judgment result and the preset reference result; in response to the confidence being greater than a first preset value, determining the type of the currently running application based on the first type judgment result; or in response to the matching degree being greater than a second preset value, determining the type of the currently running application based on the second type judgment result.

[0007] In one embodiment, obtaining a first type judgment result of a currently running application based on a currently active process includes: obtaining the currently active process and extracting the name of the currently active process based on the active process; obtaining a mapping relationship between the name and the application type; building an application type whitelist, and matching the name with the application type whitelist to obtain a first type judgment result of the currently running application.

[0008] In one embodiment, obtaining a second type judgment result of a currently running application based on current traffic characteristics includes: determining multiple categories of current traffic characteristics and obtaining a first characteristic item corresponding to each category; determining the type of the currently running application based on the first characteristic item to obtain a second type judgment result of the currently running application.

[0009] In one embodiment, the type of traffic demand level determined according to the current bandwidth occupancy rate or the current network traffic rate includes: in response to the current bandwidth occupancy rate being greater than or equal to the third preset value, or the current network traffic rate being greater than the fourth preset value, determining the traffic demand level to be the first level; in response to the current bandwidth occupancy rate being greater than or equal to the fifth preset value and less than the third preset value, or the current network traffic rate being greater than the sixth preset value and less than or equal to the fourth preset value, determining the traffic demand level to be the second level; in response to the current bandwidth occupancy rate being less than the fifth preset value, or the current network traffic rate being less than or equal to the sixth preset value, determining the traffic demand level to be the third level; wherein the first level is higher than the second level, and the second level is higher than the third level.

[0010] In one embodiment, determining a Wi-Fi network signal strength switching threshold based on a type and historical data of a currently running application includes: determining multiple categories of the historical data and obtaining a second feature item corresponding to each category; obtaining a monitoring indicator corresponding to the type; and determining the Wi-Fi network signal strength switching threshold based on the second feature item and the monitoring indicator.

[0011] In one embodiment, switching the network connection mode based on the traffic demand level and the Wi-Fi network signal strength switching threshold includes: in response to the traffic demand level being a first level, connecting to both the Wi-Fi network and the cellular network; in response to the traffic demand level being a second level, dynamically selecting between the Wi-Fi network and the cellular network based on the current network quality and the Wi-Fi network signal strength switching threshold; and in response to the traffic demand level being a third level, connecting to the Wi-Fi network and disabling the cellular network; wherein the first level is higher than the second level, and the second level is higher than the third level.

[0012] In one embodiment, in response to the traffic demand level being the first level, after simultaneously connecting to the Wi-Fi network and the cellular network, the method further includes: in response to the Wi-Fi network signal strength being less than a preset threshold, using the cellular network as the primary network and the Wi-Fi network as the secondary network.

[0013] The present application also provides a network connection system, which includes a processor and a memory, the memory is used to store program data, and the processor is used to execute the program data to implement the network connection method as described above.

[0014] The present application also provides a computer-readable and writable storage medium, in which program data is stored. When the program data is executed by a processor, it is used to implement the network connection method as described above.

[0015] This application employs a technical solution that provides a network connection method, comprising: determining the type of currently running application; determining the traffic demand level of the type based on the current bandwidth occupancy or the current network traffic rate; determining a Wi-Fi network signal strength switching threshold based on the type and historical data of the currently running application; and switching the network connection mode based on the traffic demand level and the Wi-Fi network signal strength switching threshold. This method enables dynamic adjustment of network connection strategies in different traffic demand scenarios, achieving performance improvements and optimizing energy consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0017] in:

[0018] Figure 1 This is a first flow chart of a network connection method provided in some embodiments of the present application;

[0019] Figure 2 Some embodiments of this application provide Figure 1 Schematic diagram of the sub-process of step S11;

[0020] Figure 3 Some embodiments of this application provide Figure 2 Schematic diagram of the sub-process of step S111;

[0021] Figure 4 Some embodiments of this application provide Figure 2 Schematic diagram of the sub-process of step S112;

[0022] Figure 5 Some embodiments of this application provide Figure 1 Schematic diagram of the sub-process of step S12;

[0023] Figure 6 Some embodiments of this application provide Figure 1 Schematic diagram of the sub-process of step S13;

[0024] Figure 7 Some embodiments of this application provide Figure 1Schematic diagram of the sub-process of step S14;

[0025] Figure 8 is a schematic diagram of the structure of a network connection system provided by some embodiments of the present application;

[0026] Figure 9 It is a schematic diagram of the structure of the computer-readable storage medium provided in some embodiments of the present application. DETAILED DESCRIPTION

[0027] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. It will be understood that the specific embodiments described herein are only used to explain the present application, rather than to limit the present application. It should also be noted that, for ease of description, only some, rather than all, structures related to the present application are shown in the drawings. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0028] The terms "first," "second," and the like in this application are used to distinguish between different objects, not to describe a particular order. Furthermore, the terms "including," "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or elements is not limited to the listed steps or elements, but may optionally include steps or elements not listed, or may optionally include other steps or elements inherent to the process, method, product, or apparatus.

[0029] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0030] The following combination Figure 1-Figure 7 , give a detailed description of the network connection method.

[0031] like Figure 1 As shown, Figure 1 : is a flowchart of a first embodiment of a network connection method provided by the present application, the method comprising:

[0032] Step S11: Determine the type of the currently running application.

[0033] Among them, the application types of mobile terminals can be divided according to functional use, technical architecture, etc. In one embodiment, they are divided into graphic and text applications, video applications, game applications, etc. according to content form.

[0034] In one embodiment, if Figure 2 As shown, step S11 includes the following steps:

[0035] Step S111: obtaining a first type judgment result of a currently running application according to a currently active process, and calculating a confidence level of the first type judgment result.

[0036] Among them, the currently active process refers to the process that the current user is interacting with (such as the currently open application), and the confidence level refers to the degree of certainty in judging the type of the currently running application based on the currently active process. The value range is usually [0, 1] (such as 0.9 represents 90% confidence).

[0037] In one embodiment, if Figure 3 As shown, step S111 includes the following steps:

[0038] Step S1111: Obtain the currently active process, and extract the name of the currently active process based on the active process.

[0039] The currently active process can be obtained by calling the operating system-level Application Programming Interface (API). Active processes typically contain metadata such as a process identifier, process name, and memory usage. By extracting these metadata, the name of the currently active process can be obtained. The process name is the application package name or executable file name, which is a unique identifier for the application in the operating system.

[0040] Among them, API is a collection of definitions, programs and protocols. At the operating system level, API provides applications with an interface to access the underlying resources of the operating system (such as file systems, networks, device drivers, etc.), allowing applications to call pre-packaged functions of the operating system to complete specific tasks without having to understand the complex details of the underlying implementation.

[0041] Step S1112: Acquire the mapping relationship between the name and the application type.

[0042] Among them, extracting the name of the currently active process and establishing a mapping relationship between it and the application type can achieve rapid classification of applications. By querying the mapping table, the system can determine in real time whether the currently running application belongs to the video, graphic and text type, etc., without relying on manual labeling or complex algorithms.

[0043] Step S1113: construct an application type whitelist, and match the name with the application type whitelist to obtain a first type judgment result of the currently running application.

[0044] Among them, the application type whitelist refers to a pre-defined rule database that only allows specific types of applications to run or access resources. Matching the name with the application type whitelist means matching the type of the currently running application with the application type whitelist, which can limit the use of potentially risky applications.

[0045] In one application scenario, you can use a key-value pair to match the name and application type whitelist, where the key is the process name and the value is the application type, as shown below:

[0046]

[0047] Among them, "com.tencent.tmgp.sgame" is the package name, which means the name of the currently active process, and "game" indicates the type of application corresponding to the process.

[0048] In some embodiments, after matching the name with the application type whitelist, it is usually necessary to further obtain the application's signature certificate and compare it with the system's preset official certificate hash value. If the hash value does not match, it is determined to be a counterfeit application, triggering security interception (such as denying access to sensitive permissions or resources) to ensure system security.

[0049] Step S112: obtaining a second type judgment result of the currently running application according to the current traffic characteristics, and calculating a matching degree between the second type judgment result and a preset reference result.

[0050] Among them, current traffic characteristics can include protocol characteristics, timing characteristics, load characteristics, and statistical characteristics. Different applications usually use specific network protocols. Protocol characteristics usually include data such as port numbers, protocol header fields, and flag bits. By parsing the protocol header and payload through deep packet inspection technology, it is possible to match the known protocol feature library. Timing characteristics are the distribution patterns of traffic of different applications in the time dimension, including packet interval time, continuous duration, etc. Timing patterns are extracted through time series analysis (such as autocorrelation function and Fourier transform) and can be compared with known application type characteristics. Application layer payloads may contain data in a specific format (such as JSON) or keywords (such as SQL statements). The payload content can be parsed using regular expressions, pattern matching, or machine learning models. Statistical characteristics represent the statistical properties of traffic (such as packet size distribution, traffic rate, etc.), which can reflect the application type. Traffic distribution characteristics are extracted through statistical modeling (such as Gaussian mixture model and cluster analysis).

[0051] The matching degree refers to the degree of matching between the judgment result of the type of the currently running application based on the current traffic characteristics and the business type database corresponding to the preset traffic characteristics. The value range is usually [0, 1] (such as 0.85 means 85% similarity).

[0052] Specifically, after the traffic features are extracted, rule-based matching is performed using a predefined feature library or a classification algorithm (such as deep learning, etc.) is used to train the model to identify unknown traffic. Based on the matching results or model output, the application type to which the traffic belongs is determined, that is, the second type judgment result of the currently running application is obtained, and the degree of match between the second type judgment result and the preset reference result is obtained.

[0053] In one embodiment, if Figure 4 As shown, step S112 includes the following steps:

[0054] Step S1121: Determine multiple categories of current traffic characteristics, and obtain the first characteristic item corresponding to each category.

[0055] Among them, the current traffic characteristics include multiple categories, such as protocol characteristics, timing characteristics, load characteristics and statistical characteristics. Each category has a corresponding first feature item, which represents the characteristics of each traffic feature used to identify the application type. By detecting and judging the data in the first feature item, the type of the currently running application can be determined.

[0056] Specifically, the first characteristic item of the protocol feature, such as the TLS SNI field and HTTP Host header, is used to identify the target service domain name; the first characteristic item of the timing feature, such as the mean and standard deviation of the packet arrival interval, is used to reflect the real-time and volatility of the traffic; the first characteristic item of the payload feature, such as the entropy value of the first 128 bytes of payload and keyword matching, is used to parse the payload content and match specific patterns; the first characteristic item of the statistical feature, such as the upstream / downstream traffic ratio and packet length distribution, is used to reflect the overall behavior pattern of the traffic.

[0057] Step S1122: Determine the type of the currently running application according to the first feature item to obtain a second type determination result of the currently running application.

[0058] Specifically, for the first feature item of the protocol signature, taking the example of determining that the currently running application is a video application using the TLS SNI field and the HTTP Host header field, if the SNI field contains a specific domain name, it can be inferred that the traffic is related to the service associated with that domain name. For example, v.snrpn.net is one of the domains of TikTok, used to distribute video content, so this feature directly points to the TikTok video stream.

[0059] For the first characteristic item of the timing feature, let's use the mean and standard deviation of the packet arrival interval to determine whether the currently running application is a game. Real-time transmission for games typically requires low latency and high real-time performance, so the packet interval is short. This interval can also vary significantly due to network fluctuations or game events. For example, if the mean of the monitored packet arrival interval is less than 50 milliseconds and the standard deviation is greater than 30 milliseconds, the currently running process is determined to be a game-type real-time transmission, and the currently running application type is a game.

[0060] For the first characteristic item of the payload feature, taking the example of judging that the currently running application is a video type by matching the entropy value of the first 128 bytes of the payload with keywords, the entropy value is used to measure the randomness of the data. A high entropy value usually indicates that the data is encrypted or compressed. The payload of a video on demand request may contain encrypted metadata or compressed video clips, so the entropy value is relatively high. A high entropy value itself is not enough to directly judge the application type, but combined with other features (such as keyword matching), the accuracy of the judgment can be enhanced. The application type can be identified by matching specific keywords in the payload (such as the URL path). For example, the keyword GET / v1 / play is a common API path in video on demand services, used to request video playback. Combining a high entropy payload and the GET / v1 / play keyword, it can be judged that the currently running application type is a video type.

[0061] For the first feature item of the statistical feature, taking the uplink / downlink traffic ratio and packet length as an example to determine that the currently running application is a video type, the uplink / downlink traffic ratio reflects the ratio of uplink traffic (sent by the client to the server) and downlink traffic (sent by the server to the client). In video streaming services, the client mainly receives video data (downlink traffic), while uplink traffic (such as control instructions) is relatively small; packet length distribution reflects the distribution of data packet lengths. In video streaming, downlink data packets (such as video clips) are usually larger, while uplink data packets (such as control instructions) are smaller. Combined with the uplink / downlink traffic ratio feature, it further supports the judgment that the currently running application type is a video type.

[0062] Step S113: In response to the confidence level being greater than the first preset value, the type of the currently running application is determined according to the first type determination result.

[0063] If the confidence level is less than the first preset value, step S114 is executed.

[0064] Step S114: In response to the matching degree being greater than the second preset value, the type of the currently running application is determined according to the second type determination result.

[0065] Specifically, when there is ambiguity between the first and second type judgment results, for example, if the first type judgment result determines that the currently running application type is video, while the second type judgment result determines that the currently running application type is graphic, the confidence level of the first type judgment result is compared with a first preset value, and the matching level is compared with a second preset value. If the confidence level is greater than the first preset value, the first type judgment result prevails; if the matching level is greater than the second preset value, the second type judgment result prevails.

[0066] Step S12: Determine the traffic demand level of the type according to the current bandwidth occupancy rate or the current network traffic rate.

[0067] Among them, the current bandwidth utilization rate indicates the ratio of the bandwidth occupied by the current network traffic to the total available network bandwidth, reflecting the busyness of the network link. For example, if the total network bandwidth is 100Mbps and the current traffic rate is 40Mbps, the bandwidth utilization rate is 40%; the current network traffic rate indicates the amount of data transmitted through the network link per unit time.

[0068] Specifically, in complex network environments, different applications have significantly different bandwidth and traffic requirements (for example, video conferencing requires high bandwidth and low latency, while email services have lower bandwidth requirements). Dynamically evaluating the traffic demand level of applications using current bandwidth utilization or current network traffic rate can optimize network resource allocation. This rule uses a dual judgment mechanism, taking into account both current bandwidth utilization and current network traffic rate, making it suitable for diverse network environments and application types.

[0069] In one embodiment, if Figure 5 As shown, step S12 includes the following steps:

[0070] Step S121: In response to the current bandwidth occupancy being greater than or equal to the third preset value, or the current network traffic rate being greater than the fourth preset value, determining the traffic demand level to be the first level.

[0071] Step S122: In response to the current bandwidth occupancy being greater than or equal to the fifth preset value and less than the third preset value, or the current network traffic rate being greater than the sixth preset value and less than or equal to the fourth preset value, determining the traffic demand level to be the second level.

[0072] Step S123: In response to the current bandwidth occupancy rate being less than the fifth preset value, or the current network traffic rate being less than or equal to the sixth preset value, determining the traffic demand level to be the third level.

[0073] Among them, the first level is higher than the second level, and the second level is higher than the third level.

[0074] Specifically, the first level indicates that the currently running application has a high demand for traffic and bandwidth, the second level indicates that the currently running application has a medium demand for traffic and bandwidth, and the third level indicates that the currently running application has a low demand for traffic and bandwidth.

[0075] In one embodiment, the level thresholds such as the third preset value, the fourth preset value, and the fifth preset value can be dynamically adjusted. For example, when network congestion is detected and the TCP (Transmission Control Protocol) retransmission rate is greater than the preset value (e.g., 5%), the level threshold is automatically increased.

[0076] In one embodiment, for video-sensitive services, such as high-definition live broadcast, since they are sensitive to network speed, even if the application traffic demand level is determined to be the second level, it needs to be upgraded to the first level.

[0077] Step S13: Determine a Wi-Fi network signal strength switching threshold based on the type and historical data of the currently running application.

[0078] In one embodiment, if Figure 6 As shown, step S13 includes the following steps:

[0079] Step S131: Determine multiple categories of historical data, and obtain the second feature item corresponding to each category.

[0080] The historical data includes multiple categories, such as usage habits, geographic location, device attributes, and user preferences. Each category has a corresponding second feature item, which represents the characteristics of each historical data category used to determine the Wi-Fi network signal strength switching threshold. For example, the second feature item corresponding to usage habits may include daily Wi-Fi connection duration and the number of cellular network switches; the second feature item corresponding to geographic location may include GPS (Global Positioning System Coordinates) coordinates and Wi-Fi BSSID (Basic Service Set Identifier).

[0081] Step S132: Obtain monitoring indicators corresponding to the type.

[0082] Different types of applications have different monitoring indicators. For example, video applications monitor their minimum bandwidth and maximum latency, gaming applications monitor their tolerable jitter and packet loss rate, and communication applications monitor their connection survival rate.

[0083] Step S133: Determine a Wi-Fi network signal strength switching threshold based on the second characteristic item and the monitoring indicator.

[0084] Among them, after obtaining the monitoring indicators corresponding to the second feature item and the currently running application type, based on the data analysis results within the second feature item and the monitoring indicators, multi-dimensional feature fusion and dynamic reinforcement learning model are used to perform real-time inference and adaptive optimization of the Wi-Fi signal strength switching threshold.

[0085] For example, statistics are collected on the daily Wi-Fi network connection duration of an application. If the application is in a weak signal for a long time, or for a high-sensitivity high-end network card, the Wi-Fi network signal strength switching threshold can be lowered.

[0086] In one embodiment, for manual switching records (such as forcibly maintaining a Wi-Fi network), if manual intervention is detected, the automatic adjustment time (such as 24 hours) is frozen to ensure the user experience.

[0087] Step S14: Switch the network connection mode according to the traffic demand level and the Wi-Fi network signal strength switching threshold.

[0088] In one embodiment, if Figure 7 As shown, step S14 includes the following steps:

[0089] Step S141: In response to the traffic demand level being the first level, connecting to the Wi-Fi network and the cellular network simultaneously.

[0090] In one embodiment, in response to the traffic demand level being the first level, after simultaneously connecting to the Wi-Fi network and the cellular network, the method further includes: in response to the Wi-Fi network signal strength being less than a preset threshold, using the cellular network as the primary network and the Wi-Fi network as the secondary network.

[0091] If the currently running application has high traffic and bandwidth requirements, multi-network collaboration is enabled, connecting to both Wi-Fi and cellular networks simultaneously. Furthermore, when the Wi-Fi network signal strength falls below a preset threshold (e.g., below -70dBm), the cellular network is prioritized, with Wi-Fi serving as a secondary network. This approach ensures smooth transmission of real-time services.

[0092] Step S142: In response to the traffic demand level being the second level, dynamically selecting a Wi-Fi network or a cellular network based on the current network quality and the Wi-Fi network signal strength switching threshold.

[0093] Among them, if the currently running application has medium demand for traffic and bandwidth, the Wi-Fi network and cellular network are dynamically selected. Specifically, the current network quality can be judged based on indicators such as signal strength (Wi-Fi network and cellular network signal strength), transmission quality (end-to-end delay, jitter, etc.), and bandwidth capacity (instantaneous throughput, available bandwidth estimation, etc.).

[0094] For example, end-to-end latency and jitter are core metrics for evaluating transmission quality. End-to-end latency (Round-Trip Time, RTT) refers to the total time it takes for a data packet to travel from the sender to the receiver and back again. Low latency (e.g., <50ms) is suitable for real-time interactive applications (such as online gaming and video conferencing); high latency (e.g., >200ms) may lead to a degraded user experience (such as video freezes and voice delays). Jitter refers to the variance in the latency of consecutive data packets and reflects latency stability. Low jitter (e.g., <10ms) is suitable for latency-sensitive applications (such as real-time audio and video, and industrial control); high jitter (e.g., >50ms) may result in packet disarray or loss, requiring optimization through caching or retransmission mechanisms.

[0095] The system weights network quality indicators based on the type of application currently running. For example, for video applications, latency is weighted 40%, jitter 30%, packet loss 20%, and bandwidth 10%. Data from each dimension is collected periodically (e.g., every 5 seconds) and combined with the weights to calculate a comprehensive score. The system dynamically selects between Wi-Fi and cellular networks, choosing the optimal connection method.

[0096] Step S143: In response to the traffic demand level being the third level, connecting to the Wi-Fi network and shutting down the cellular network.

[0097] Among them, the first level is higher than the second level, and the second level is higher than the third level.

[0098] Among them, the currently running application has low requirements for traffic and bandwidth, and only uses Wi-Fi connection. Even if the signal is weak, it remains connected to avoid unnecessary cellular network switching.

[0099] In the above solution, a multi-network collaboration mechanism is used to ensure smooth transmission of real-time services in high-traffic demand scenarios; in low-traffic scenarios, Wi-Fi networks are given priority to reduce cellular data traffic consumption, avoid unnecessary network switching and multi-network collaboration, and extend battery life; and strategies are dynamically adjusted according to real-time needs to adapt to complex network environments.

[0100] like Figure 8 As shown, Figure 8 1 is a schematic diagram of the structure of a network connection system provided in some embodiments of the present application. The network connection system 100 includes a processor 81 and a memory 82. The memory 82 is used to store program data, and the processor 81 is used to execute the program data to implement the following network connection method:

[0101] Determine the type of the currently running application; determine the traffic demand level of the type based on the current bandwidth usage or the current network traffic rate; determine the Wi-Fi network signal strength switching threshold based on the type and historical data of the currently running application; and switch the network connection mode based on the traffic demand level and the Wi-Fi network signal strength switching threshold.

[0102] In one embodiment, the processor 81 is further used to execute: obtaining a first type judgment result of the currently running application based on the currently active process, and calculating the confidence of the first type judgment result; obtaining a second type judgment result of the currently running application based on the current traffic characteristics, and calculating the matching degree between the second type judgment result and the preset reference result; in response to the confidence being greater than the first preset value, determining the type of the currently running application based on the first type judgment result; or in response to the matching degree being greater than the second preset value, determining the type of the currently running application based on the second type judgment result.

[0103] In one embodiment, the processor 81 is also used to execute: obtaining the currently active process and extracting the name of the currently active process based on the active process; obtaining the mapping relationship between the name and the application type; building an application type whitelist and matching the name with the application type whitelist to obtain the first type judgment result of the currently running application.

[0104] In one embodiment, the processor 81 is further used to execute: determining multiple categories of current traffic characteristics and obtaining a first characteristic item corresponding to each category; determining the type of the currently running application based on the first characteristic item to obtain a second type judgment result of the currently running application.

[0105] In one embodiment, the processor 81 is further used to execute: in response to the current bandwidth occupancy being greater than or equal to the third preset value, or the current network traffic rate being greater than the fourth preset value, determining the traffic demand level to be the first level; in response to the current bandwidth occupancy being greater than or equal to the fifth preset value and less than the third preset value, or the current network traffic rate being greater than the sixth preset value and less than or equal to the fourth preset value, determining the traffic demand level to be the second level; in response to the current bandwidth occupancy being less than the fifth preset value, or the current network traffic rate being less than or equal to the sixth preset value, determining the traffic demand level to be the third level; wherein the first level is higher than the second level, and the second level is higher than the third level.

[0106] In one embodiment, the processor 81 is further configured to: determine multiple categories of historical data and obtain a second feature item corresponding to each category; obtain a monitoring indicator corresponding to the type; and determine a Wi-Fi network signal strength switching threshold based on the second feature item and the monitoring indicator.

[0107] In one embodiment, the processor 81 is further configured to: in response to the traffic demand level being a first level, simultaneously connect to the Wi-Fi network and the cellular network; in response to the traffic demand level being a second level, dynamically select between the Wi-Fi network and the cellular network based on the current network quality and the Wi-Fi network signal strength switching threshold; in response to the traffic demand level being a third level, connect to the Wi-Fi network and shut down the cellular network; wherein the first level is higher than the second level, and the second level is higher than the third level.

[0108] In one embodiment, the processor 81 is further configured to execute: in response to the Wi-Fi network signal strength being less than a preset threshold, using the cellular network as the primary network and the Wi-Fi network as the secondary network.

[0109] like Figure 9 As shown, Figure 9 1 is a schematic diagram of the structure of a computer-readable storage medium provided in some embodiments of the present application. The computer-readable storage medium 1000 stores program data 110. When executed by a processor, the program data 110 is used to implement the following network connection method:

[0110] Determine the type of the currently running application; determine the traffic demand level of the type based on the current bandwidth usage or the current network traffic rate; determine the Wi-Fi network signal strength switching threshold based on the type and historical data of the currently running application; and switch the network connection mode based on the traffic demand level and the Wi-Fi network signal strength switching threshold.

[0111] In one embodiment, when the program data 110 is executed by the processor, it is used to implement: obtaining a first type judgment result of the currently running application based on the currently active process, and calculating the confidence of the first type judgment result; obtaining a second type judgment result of the currently running application based on the current traffic characteristics, and calculating the matching degree between the second type judgment result and the preset reference result; in response to the confidence being greater than the first preset value, determining the type of the currently running application based on the first type judgment result; or in response to the matching degree being greater than the second preset value, determining the type of the currently running application based on the second type judgment result.

[0112] In one embodiment, when the program data 110 is executed by the processor, it is used to implement: obtaining the current active process and extracting the name of the current active process based on the active process; obtaining the mapping relationship between the name and the application type; building an application type whitelist, and matching the name with the application type whitelist to obtain the first type judgment result of the currently running application.

[0113] In one embodiment, when the program data 110 is executed by the processor, it is used to implement: determining multiple categories of current traffic characteristics and obtaining the first characteristic item corresponding to each category; determining the type of the currently running application based on the first characteristic item to obtain the second type judgment result of the currently running application.

[0114] In one embodiment, when the program data 110 is executed by the processor, it is used to achieve: in response to the current bandwidth occupancy rate being greater than or equal to the third preset value, or the current network traffic rate being greater than the fourth preset value, determining the traffic demand level to be the first level; in response to the current bandwidth occupancy rate being greater than or equal to the fifth preset value and less than the third preset value, or the current network traffic rate being greater than the sixth preset value and less than or equal to the fourth preset value, determining the traffic demand level to be the second level; in response to the current bandwidth occupancy rate being less than the fifth preset value, or the current network traffic rate being less than or equal to the sixth preset value, determining the traffic demand level to be the third level; wherein the first level is higher than the second level, and the second level is higher than the third level.

[0115] In one embodiment, when executed by a processor, the program data 110 is used to: determine multiple categories of historical data and obtain a second characteristic item corresponding to each category; obtain a monitoring indicator corresponding to the category; and determine a Wi-Fi network signal strength switching threshold based on the second characteristic item and the monitoring indicator.

[0116] In one embodiment, when the program data 110 is executed by the processor, it is used to implement: in response to the traffic demand level being a first level, connecting to the Wi-Fi network and the cellular network simultaneously; in response to the traffic demand level being a second level, dynamically selecting the Wi-Fi network and the cellular network based on the current network quality and the Wi-Fi network signal strength switching threshold; in response to the traffic demand level being a third level, connecting to the Wi-Fi network and disabling the cellular network; wherein the first level is higher than the second level, and the second level is higher than the third level.

[0117] In one embodiment, when the program data 110 is executed by the processor, it is used to implement: in response to the Wi-Fi network signal strength being less than a preset threshold, using the cellular network as the primary network and the Wi-Fi network as the secondary network.

[0118] This application employs a technical solution that provides a network connection method, comprising: determining the type of currently running application; determining the traffic demand level of the type based on the current bandwidth occupancy or the current network traffic rate; determining a Wi-Fi network signal strength switching threshold based on the type and historical data of the currently running application; and switching the network connection mode based on the traffic demand level and the Wi-Fi network signal strength switching threshold. This method enables dynamic adjustment of network connection strategies in different traffic demand scenarios, achieving performance improvements and optimizing energy consumption.

[0119] In the several embodiments provided in this application, it should be understood that the disclosed methods and devices can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the modules or units is merely a logical functional division. In actual implementation, other division methods may be used, such as combining or integrating multiple units or components into another system, or ignoring or not implementing certain features.

[0120] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of this embodiment.

[0121] In addition, each functional unit in each embodiment of the present application may be integrated into a processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The above-mentioned integrated units may be implemented in the form of hardware or software functional units.

[0122] The above description is only an implementation method of the present application and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the description and drawings of this application, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A network connection method, characterized in that: The method comprises: Determine the type of the currently running application; Determining the traffic demand level of the type according to the current bandwidth occupancy rate or the current network traffic rate; Determining a Wi-Fi network signal strength switching threshold based on the type and historical data of the currently running application; The network connection mode is switched according to the traffic demand level and the Wi-Fi network signal strength switching threshold.

2. The network connection method according to claim 1, wherein: Determining the type of the currently running application includes: Obtaining a first type determination result of the currently running application according to the currently active process, and calculating a confidence level of the first type determination result; Obtaining a second type judgment result of the currently running application according to the current traffic characteristics, and calculating a matching degree between the second type judgment result and a preset reference result; In response to the confidence level being greater than a first preset value, determining the type of the currently running application according to the first type determination result; or In response to the matching degree being greater than a second preset value, the type of the currently running application is determined according to the second type determination result.

3. The network connection method according to claim 2, wherein: The obtaining, according to the currently active process, a first type determination result of the currently running application includes: Obtain the currently active process, and extract the name of the currently active process according to the active process; Obtaining a mapping relationship between the name and the application type; An application type whitelist is constructed, and the name is matched with the application type whitelist to obtain a first type determination result of the currently running application.

4. The network connection method according to claim 2, wherein: The obtaining, according to the current traffic characteristics, the second type determination result of the currently running application includes: Determine multiple categories of the current traffic characteristics, and obtain a first characteristic item corresponding to each category; The type of the currently running application is determined according to the first feature item to obtain a second type determination result of the currently running application.

5. The network connection method according to claim 1, wherein: The determining of the traffic demand level of the type according to the current bandwidth occupancy rate or the current network traffic rate includes: In response to the current bandwidth occupancy being greater than or equal to a third preset value, or the current network traffic rate being greater than a fourth preset value, determining the traffic demand level to be the first level; In response to the current bandwidth occupancy being greater than or equal to a fifth preset value and less than the third preset value, or the current network traffic rate being greater than a sixth preset value and less than or equal to the fourth preset value, determining the traffic demand level to be the second level; In response to the current bandwidth occupancy rate being less than the fifth preset value, or the current network traffic rate being less than or equal to the sixth preset value, determining the traffic demand level to be the third level; The first level is higher than the second level, and the second level is higher than the third level.

6. The network connection method according to claim 1, wherein: Determining a Wi-Fi network signal strength switching threshold according to the type and historical data of the currently running application includes: Determining multiple categories of the historical data, and obtaining a second feature item corresponding to each category; Obtain monitoring indicators corresponding to the type; The Wi-Fi network signal strength switching threshold is determined according to the second feature item and the monitoring indicator.

7. The network connection method according to claim 1, wherein: The switching of the network connection mode according to the traffic demand level and the Wi-Fi network signal strength switching threshold includes: In response to the traffic demand level being the first level, connecting to the Wi-Fi network and the cellular network simultaneously; In response to the traffic demand level being the second level, dynamically selecting the Wi-Fi network and the cellular network based on current network quality and the Wi-Fi network signal strength switching threshold; In response to the traffic demand level being the third level, connecting to the Wi-Fi network and shutting down the cellular network; wherein the first level is higher than the second level, and the second level is higher than the third level.

8. The network connection method according to claim 7, wherein: In response to the traffic demand level being the first level, after simultaneously connecting to the Wi-Fi network and the cellular network, the method further includes: In response to the Wi-Fi network signal strength being less than a preset threshold, the cellular network is used as a primary network and the Wi-Fi network is used as a secondary network.

9. A network connection system, characterized in that: The network connection system includes a processor and a memory, the memory is used to store program data, and the processor is used to execute the program data to implement the network connection method according to any one of claims 1 to 8.

10. A computer-readable and writable storage medium, characterized in that: The computer-readable and writable storage medium stores program data, and when the program data is executed by the processor, it is used to implement the network connection method according to any one of claims 1 to 8.

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