Vehicle-mounted desktop display method and related product

Abstract

The invention discloses a vehicle-mounted desktop display method and a related product. The method comprises the following steps: determining a real-time network quality index according to an obtained wireless link index and vehicle dynamic data; then, based on a pre-trained network quality prediction model, determining predicted network quality in a future preset time period according to the real-time network quality index; if the predicted network quality is greater than or equal to a preset network quality threshold value, acquiring real-time desktop data through an edge node corresponding to the vehicle-mounted terminal; if the predicted network quality is smaller than a preset network quality threshold value, obtaining offline desktop data through a vehicle end mirror image in the vehicle-mounted terminal; wherein the real-time desktop data is used for displaying a corresponding real-time vehicle-mounted desktop through the vehicle-mounted terminal; the offline desktop data is used for displaying a corresponding offline vehicle-mounted desktop through the vehicle-mounted terminal. Therefore, the user experience and the service continuity are improved.

Description

Technical Field

[0001] This application relates to the field of vehicle networking technology, and in particular to an in-vehicle desktop display method and related products. Background Technology

[0002] With the rapid development of vehicle networking technology, the relevant technologies generally adopt a centralized architecture of "vehicle-side light client + cloud virtual desktop". The vehicle connects to the cloud data center or edge node through wireless networks (5G, Wi-Fi, C-V2X, etc.) to receive the desktop image stream generated by the cloud and display it on the vehicle.

[0003] However, when vehicles are in environments with high-speed movement, frequent base station switching, and large fluctuations in network quality, issues such as desktop stream interruption, latency accumulation, and session loss may occur, resulting in differences between the in-vehicle desktop and the cloud desktop, which in turn leads to a decrease in user experience. Furthermore, the mode of operation that relies entirely on the cloud is highly sensitive to network connectivity, and network interruptions or edge node anomalies will affect business continuity. Summary of the Invention

[0004] To address the aforementioned issues, this application provides an in-vehicle desktop display method and related products, aiming to improve user experience and enhance business continuity.

[0005] The embodiments of this application disclose the following technical solutions:

[0006] In a first aspect, embodiments of this application provide an in-vehicle desktop display method, which is applied to an in-vehicle terminal and includes:

[0007] Acquire wireless link metrics and vehicle dynamic data;

[0008] The real-time network quality index is determined based on wireless link metrics and vehicle dynamic data.

[0009] Based on a pre-trained network quality prediction model, the predicted network quality within a preset time period is determined according to the real-time network quality index.

[0010] If the predicted network quality is greater than or equal to the preset network quality threshold, then real-time desktop data is obtained through the edge node corresponding to the vehicle terminal; the real-time desktop data is used to display the corresponding real-time vehicle desktop through the vehicle terminal.

[0011] If the predicted network quality is less than the preset network quality threshold, offline desktop data is obtained through the vehicle-side mirror in the vehicle terminal; the offline desktop data is used to display the corresponding offline vehicle desktop through the vehicle terminal.

[0012] Optionally, after obtaining the offline desktop data, the method further includes:

[0013] If the new predicted network quality is greater than or equal to the preset network quality threshold, the local difference log is compared with the edge mirror state corresponding to the edge node to obtain the minimum difference packet.

[0014] The minimum difference packet is synchronized to the cloud via the edge node.

[0015] Optionally, the local difference logs are compared with the edge mirror status corresponding to the edge nodes to obtain the minimum difference packet, including:

[0016] Obtain the first hash value of the current page based on the local difference log;

[0017] Obtain the second hash value of the edge page based on the edge mirror state;

[0018] The difference subpage is determined based on the first hash value and the second hash value to obtain the difference set; wherein the difference subpage represents the subpage that differs from the current page and the edge page; the difference set includes at least one difference subpage;

[0019] The minimum difference packet is determined based on the difference set.

[0020] Optionally, if the predicted network quality is less than a preset network quality threshold, the method further includes:

[0021] Freeze the target thread associated with the cloud and record interaction information and state change information.

[0022] Secondly, embodiments of this application provide an in-vehicle desktop display device, which is applied to an in-vehicle terminal and includes:

[0023] The acquisition unit is used to acquire wireless link indicators and vehicle dynamic data.

[0024] The determination unit is used to determine the real-time network quality index based on wireless link indicators and vehicle dynamic data.

[0025] The prediction unit is used to determine the predicted network quality within a preset time period based on a pre-trained network quality prediction model and the real-time network quality index.

[0026] The first display unit is used to obtain real-time desktop data through the edge node corresponding to the vehicle terminal if the predicted network quality is greater than or equal to a preset network quality threshold; the real-time desktop data is used to display the corresponding real-time vehicle desktop through the vehicle terminal.

[0027] The second display unit is used to obtain offline desktop data through the vehicle-side mirror in the vehicle terminal if the predicted network quality is less than a preset network quality threshold; the offline desktop data is used to display the corresponding offline vehicle desktop through the vehicle terminal.

[0028] Optionally, after the second display unit, the device further includes: a differential write-back unit, for:

[0029] If the new predicted network quality is greater than or equal to the preset network quality threshold, the local difference log is compared with the edge mirror state corresponding to the edge node to obtain the minimum difference packet.

[0030] The minimum difference packet is synchronized to the cloud via the edge node.

[0031] Optionally, the differential write-back unit is used for:

[0032] Obtain the first hash value of the current page based on the local difference log;

[0033] Obtain the second hash value of the edge page based on the edge mirror state;

[0034] The difference subpage is determined based on the first hash value and the second hash value to obtain the difference set; wherein the difference subpage represents the subpage that differs from the current page and the edge page; the difference set includes at least one difference subpage;

[0035] The minimum difference packet is determined based on the difference set.

[0036] Optionally, if the predicted network quality is less than a preset network quality threshold, the device further includes: a freeze and record unit, used for:

[0037] Freeze the target thread associated with the cloud and record interaction information and state change information.

[0038] Thirdly, embodiments of this application provide a control device, including a processor and a memory, wherein the memory is used to store programs, instructions or code, and the processor is used to execute the programs, instructions or code in the memory to complete the in-vehicle desktop display method as described in the first aspect.

[0039] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program, which is loaded by a processor to execute the in-vehicle desktop display method as described in the first aspect.

[0040] Beneficial effects:

[0041] The in-vehicle desktop display method provided in this application determines a real-time network quality index based on acquired wireless link metrics and vehicle dynamic data; then, based on a pre-trained network quality prediction model, it determines the predicted network quality within a preset future time period based on the real-time network quality index; if the predicted network quality is greater than or equal to a preset network quality threshold, real-time desktop data is obtained through the edge node corresponding to the in-vehicle terminal; if the predicted network quality is less than the preset network quality threshold, offline desktop data is obtained through the vehicle-side mirror in the in-vehicle terminal; wherein, the real-time desktop data is used to display the corresponding real-time in-vehicle desktop through the in-vehicle terminal; and the offline desktop data is used to display the corresponding offline in-vehicle desktop through the in-vehicle terminal.

[0042] In this way, by determining the real-time network quality index based on real-time wireless link indicators and vehicle dynamic data, the predicted network quality within a preset time period can be obtained, enabling the prediction of network conditions. The desktop data acquisition method can be adjusted according to the network conditions. When the network quality is good, real-time desktop data is acquired to ensure that the in-vehicle desktop is real-time, up-to-date, and has a fast operation response. When the network quality is poor, offline desktop data is switched to avoid slow desktop loading, lag, or even failure to display due to network problems, thereby improving user experience and business continuity. Attached Figure Description

[0043] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 A flowchart illustrating an in-vehicle desktop display method provided in an embodiment of this application;

[0045] Figure 2 This is a schematic diagram of a vehicle-cloud collaborative system provided in an embodiment of this application;

[0046] Figure 3 This is a schematic diagram of the structure of an in-vehicle desktop display device provided in an embodiment of this application;

[0047] Figure 4 This is a schematic diagram of the structure of a control device provided in an embodiment of this application. Detailed Implementation

[0048] As described earlier, related technologies can deploy desktop caching or use breakpoint resume mechanisms at edge nodes to improve the availability of desktop services. However, these technologies generally remain at the synchronization level between edge nodes and the cloud, failing to fully utilize the local storage and computing capabilities of the vehicle.

[0049] However, when the network is interrupted, existing in-vehicle cloud desktop systems usually terminate the session directly, lacking an offline degradation mechanism, which cannot guarantee the continuity of critical tasks or maintenance operations, and at the same time reduces the user experience.

[0050] Based on this, embodiments of this application provide an in-vehicle desktop display method and related products. The method includes: determining a real-time network quality index based on acquired wireless link metrics and vehicle dynamic data; then, based on a pre-trained network quality prediction model, determining the predicted network quality within a preset future time period based on the real-time network quality index; if the predicted network quality is greater than or equal to a preset network quality threshold, acquiring real-time desktop data through the edge node corresponding to the in-vehicle terminal; if the predicted network quality is less than the preset network quality threshold, acquiring offline desktop data through the vehicle-side mirror in the in-vehicle terminal; wherein, the real-time desktop data is used to display the corresponding real-time in-vehicle desktop through the in-vehicle terminal; and the offline desktop data is used to display the corresponding offline in-vehicle desktop through the in-vehicle terminal.

[0051] In this way, by determining the real-time network quality index based on real-time wireless link indicators and vehicle dynamic data, the predicted network quality within a preset time period can be obtained, enabling the prediction of network conditions. The desktop data acquisition method can be adjusted according to the network conditions. When the network quality is good, real-time desktop data is acquired to ensure that the in-vehicle desktop is real-time, up-to-date, and has a fast operation response. When the network quality is poor, offline desktop data is switched to avoid slow desktop loading, lag, or even failure to display due to network problems, thereby improving user experience and business continuity.

[0052] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0053] The collection and processing of relevant data (including but not limited to experimental data, test data, simulation data, user data, etc.) involved in this application shall strictly comply with the requirements of national laws and regulations when applied in the following embodiments, obtain the informed consent or separate consent of the subject obtaining the data information, and carry out data use and processing within the scope of laws and regulations and the authorization of the subject.

[0054] See Figure 1 This figure is a flowchart illustrating an in-vehicle desktop display method provided in an embodiment of this application. Combined with... Figure 1As shown in the embodiment of this application, the onboard desktop display method is applied to an in-vehicle terminal and includes:

[0055] S11: Acquire wireless link metrics and vehicle dynamic data.

[0056] Wireless link metrics may include parameters that reflect the condition of a wireless network, such as signal strength, signal quality, network bandwidth, and latency.

[0057] Vehicle dynamic data may include information such as vehicle position, speed, direction of travel, and acceleration. This data is collected through sensors, network monitoring tools, and other equipment to provide a foundation for subsequent analysis and decision-making.

[0058] It should be understood that comprehensively collecting data related to networks and vehicles provides a wealth of information for accurately assessing real-time network quality indices. Wireless link metrics directly reflect the quality of network connectivity, while vehicle dynamic data can affect network signal reception (e.g., a vehicle driving into an area with weak signal coverage). Taking these factors into account can make the assessment results more closely reflect reality.

[0059] S12: Determine the real-time network quality index based on wireless link metrics and vehicle dynamic data.

[0060] It should be understood that the embodiments of this application can comprehensively analyze and process the acquired wireless link indicators and vehicle dynamic data to determine the real-time network quality index, so as to reflect the real-time quality status of the current network by implementing the network quality index.

[0061] S13: Based on a pre-trained network quality prediction model, the predicted network quality within a preset time period is determined according to the real-time network quality index.

[0062] A pre-trained network quality model refers to a model used to predict network quality over a predetermined future time period.

[0063] It should be understood that network quality models can predict future network quality, enabling network condition forecasting. This provides forward-looking information for adjusting desktop data acquisition methods based on network conditions, allowing the system to take proactive measures and avoid adverse effects caused by sudden network changes.

[0064] S14: If the predicted network quality is greater than or equal to the preset network quality threshold, then real-time desktop data is obtained through the edge node corresponding to the vehicle terminal.

[0065] Real-time desktop data is used to display the corresponding real-time in-vehicle desktop through the in-vehicle terminal.

[0066] It should be understood that when the predicted future network quality is good (greater than or equal to a preset threshold), the system selects to obtain real-time desktop data through the edge node connected to the in-vehicle terminal. Edge nodes are typically located at the network edge, close to the user, and can provide low-latency data transmission services. The obtained real-time desktop data can promptly display the latest in-vehicle desktop on the in-vehicle terminal, including various applications and interface elements. Thus, under good network quality conditions, selecting to obtain real-time desktop data ensures that the in-vehicle desktop is always up-to-date and operates quickly; simultaneously, users can obtain the latest information and services in a timely manner, improving convenience and efficiency, and meeting users' needs for real-time interaction.

[0067] S15: If the predicted network quality is less than the preset network quality threshold, then obtain offline desktop data through the vehicle-side mirror in the vehicle terminal.

[0068] Offline desktop data is used to display the corresponding offline in-vehicle desktop through the in-vehicle terminal.

[0069] It should be understood that when poor network quality is predicted in the future (below a preset threshold), the system switches to obtaining offline desktop data from the vehicle-side image stored internally in the in-vehicle terminal. This offline desktop data is pre-stored in the vehicle-side image and does not rely on a real-time network connection, allowing it to be used normally even with unstable or interrupted networks. By displaying the offline in-vehicle desktop through the in-vehicle terminal, users can still perform some basic operations and view information.

[0070] In this way, switching to offline desktop data when network quality is poor avoids situations where the desktop loads slowly, lags, or even fails to display due to network issues. This ensures business continuity; even in poor network conditions, users can still use the basic functions of the in-vehicle terminal, improving the user experience and preventing complete inaccessibility of the device due to network problems.

[0071] In this embodiment, a real-time network quality index is determined based on real-time wireless link metrics and vehicle dynamic data. This allows for prediction of network quality within a preset time period, enabling the system to anticipate network conditions and adjust desktop data acquisition methods accordingly. When network quality is good, real-time desktop data is acquired to ensure the in-vehicle desktop is up-to-date and responds quickly. When network quality is poor, offline desktop data is switched to avoid slow loading, lag, or even failure to display the desktop due to network issues, thus improving user experience and business continuity.

[0072] In one possible implementation of the in-vehicle desktop display method provided by the above embodiments, after obtaining offline desktop data, the method further includes: if the new predicted network quality is greater than or equal to a preset network quality threshold, then comparing the local difference log with the edge mirror state corresponding to the edge node to obtain the minimum difference packet; and synchronizing the minimum difference packet to the cloud through the edge node.

[0073] The minimum difference packet refers to the smallest set of data containing the differences between the vehicle-side image and the edge image. It should be understood that after acquiring offline desktop data, if the subsequent new prediction network quality recovers to a good state (greater than or equal to a preset network quality threshold), the local difference log can be compared with the edge image status corresponding to the edge node. The local difference log records the difference information between the vehicle-side image and the edge image; by comparing them, the differences can be identified, thus obtaining the minimum difference packet. This minimum difference packet is then synchronized to the cloud through the edge node to ensure that the data in the cloud is consistent with the vehicle-side data.

[0074] In this way, by comparing the local difference logs and the edge mirror status to obtain the minimum difference packet, the amount of data to be synchronized can be reduced. Synchronizing only the differing parts, rather than the entire mirror, greatly improves the efficiency and speed of data synchronization, saving network bandwidth and time costs. At the same time, synchronizing data to the cloud ensures data backup and consistency, facilitating subsequent data management and recovery.

[0075] Based on the in-vehicle desktop display method provided in the above embodiments, in one possible implementation, comparing the local difference log with the edge mirror state corresponding to the edge node to obtain the minimum difference packet may include: obtaining a first hash value of the current page based on the local difference log; obtaining a second hash value of the edge page based on the edge mirror state; determining the difference subpage based on the first hash value and the second hash value to obtain a difference set; and determining the minimum difference packet based on the difference set. Here, the difference subpage represents a subpage where there is a difference between the current page and the edge page; the difference set includes at least one difference subpage.

[0076] A hash value is an algorithm that maps data of arbitrary length to a fixed-length value. By performing a hash calculation on the data of the current page in the local difference log, a first hash value is obtained that uniquely identifies the state of the data on that page. Similarly, a second hash value is obtained by performing a hash calculation on the corresponding edge page data in the edge mirror.

[0077] It should be understood that by comparing two hash values, if they are different, it indicates that there is a difference in the page. This further identifies the specific subpages with differences, and these differing subpages are grouped into a difference set. Then, the differing subpages in the difference set are organized and optimized to remove redundant information, resulting in a minimum difference packet containing the least amount of data.

[0078] It should be understood that in this embodiment, the hash value comparison method can accurately and quickly identify the differing subpages between the current page and the edge page. The hash algorithm is unique and efficient, capable of efficiently processing large amounts of data and ensuring the accuracy of difference detection. The method of determining the minimum difference packet further optimizes data synchronization, reduces unnecessary data transmission, and improves the efficiency and performance of data synchronization.

[0079] In one possible implementation of the in-vehicle desktop display method based on the above embodiments, if the predicted network quality is less than a preset network quality threshold, the method further includes: freezing the target thread associated with the cloud and recording interaction information and state change information.

[0080] The target thread may be responsible for data interaction and synchronization with the cloud. Simultaneously, it records interaction information and state change information. Interaction information may include records of user interactions with the cloud application, and state change information may include changes in system state, application state, etc.

[0081] It should be understood that freezing the target thread can prevent data errors or loss caused by unstable data transmission when network quality is poor. Recording interaction information and state change information provides a basis for restoring to the previous state after network recovery. When network quality is restored, data synchronization and state restoration can be performed again based on this recorded information, ensuring business continuity and data consistency.

[0082] Based on the in-vehicle desktop display method provided in the above embodiments, in one possible implementation, it is combined with... Figure 2 As shown in the illustration, this application also provides an in-vehicle desktop system, which may include a network quality detection module, a session / mirror management module, a mirror projection module, an offline operation module, a differential write-back module, and a consistency coordination module. The in-vehicle desktop system provided in this application can achieve the in-vehicle desktop display method provided in this application through the individual functions of each module or the collaborative cooperation between modules.

[0083] The Network Quality Monitor (NQM) module is responsible for collecting real-time network quality parameters of the vehicle, including signal strength, latency, packet loss rate, bandwidth utilization, base station handover frequency, etc.

[0084] The network quality detection module periodically calculates the Network Quality Index (NQI). When the NQI falls below the threshold T1, it triggers the "mirror degradation operation mode"; when the NQI recovers and rises above the threshold T2, it triggers "differential write-back synchronization".

[0085] As an example, the input to the network quality detection module can be wireless link metrics, vehicle dynamics, and a weak coverage knowledge base; among which, wireless link metrics can include, but are not limited to, RSRP / RSRQ, SINR, RTT, packet loss rate pl, available bandwidth bw, and handover frequency hfr; vehicle dynamics can include, but are not limited to, vehicle speed v, heading change rate θ̇, and geographical location (lat, lon); and the weak coverage knowledge base can be a geographic weak network grid G.

[0086] As an example, the output of the network quality detection module can be the real-time network quality index NQI(t) and the predicted network quality ŇQI(t+Δ).

[0087] As an example, the network quality detection module can also output a switching policy signal, which can be any one of the following signals: PREHEAT=1 (preheating trigger), DOWNGRADE=1 (degradation trigger), or RECOVER=1 (recovery trigger).

[0088] It should be understood that, in this embodiment, mirroring and state projection can be triggered a few seconds before network outage, avoiding "post-incident remediation" and improving user experience. Simultaneously, by combining geographical weak network hotspots with vehicle speed / switching frequency for short-term prediction, it is more suitable for vehicle-to-everything (V2X) scenarios. Furthermore, by setting different thresholds (T1 and T2) to create hysteresis, false triggers caused by network quality index fluctuations are reduced.

[0089] As an example, network quality can be evaluated in real time, future network status can be predicted, and handover strategy signals can be issued based on wireless link metrics, vehicle dynamic information, and weak coverage knowledge base data, using normalization, exponential smoothing, and short-term prediction algorithms.

[0090] Normalization and exponential smoothing refer to linearly / piecewise normalizing each indicator to [0,1], such as bandwidth normalization b̂w=min(bw / Bmax,1); using EWMA: x̃_t=α·x_t+(1-α)·x̃_{t-1} (α∈(0,1), recommended 0.3~0.6).

[0091] Overall Quality Index (Example):

[0092] ;

[0093] Among them, weight The weights can be adjusted offline by region / vehicle type.

[0094] The pre-trained network quality model (such as Kalman or lightweight LSTM) can output ŇQI(t+Δ) (Δ = 3 - 5 s). Among them, when ŇQI < T1 → issue PREHEAT; NQI < T2 → issue DOWNGRADE, where T2 < T1 forms a hysteresis to reduce jitter, for example, T1 = 0.55 and T2 = 0.45.

[0095] The Session / Image Management Module (DIM, Desktop Image Manager) is responsible for maintaining three-layer images among the cloud, edge nodes, and vehicle terminals: the cloud master image (MasterImage), the edge relay image (EdgeReplica), and the vehicle-terminal local image (LocalCacheImage).

[0096] The desktop running environment is encapsulated using lightweight containers, enabling the images to be loaded in layers and migrated with differences. The Session / Image Management Module supports multi-version control, timestamp identification, and incremental snapshot recording.

[0097] As an example, the inputs to the Session / Image Management Module can be: user identity UID, vehicle identity VIN / SCV_ID, image layer description (system layer L0 / application layer L1 / user layer L2), version ver, and snapshot index S.

[0098] The snapshot structure is represented as Snap={ver,layer∈{L0 / L1 / L2},hash_root,ts,sig};

[0099] The inter-layer reference is represented as Ref(L2→L1→L0);

[0100] The runtime verification is represented as hash(Li)==hash_root_i;

[0101] The takeover recovery priority is represented as L0 (local SSD mapping) → L1 (edge cache) → L2 (RAM synthesis), and the total delay is approximately sub-second level.

[0102] As an example, the outputs of the Session / Image Management Module can be: the three-layer image mapping of the vehicle / edge / cloud, the active snapshot handle, and the inter-layer reference table.

[0103] It should be understood that the Session / Image Management Module can be responsible for managing information such as user identity, vehicle identity, and image layer description, outputting the three-layer image mapping of the vehicle / edge / cloud, the active snapshot handle, and the inter-layer reference table, and realizing the unified assembly, inspection, and rollback of the images. In this way, through the three-layer separated snapshots (L0 system, L1 application, L2 user) + cross-layer reference table, the takeover delay is significantly reduced. At the same time, only the high-frequency changing L2 is mirrored in real time, and L0 / L1 use caching / references, reducing resource consumption.

[0104] The Image Projection Module (IPM) is used by the system, with edge nodes as the primary computing end, to project the desktop's running state (window information, UI state, memory page differences, cached data) to the vehicle's local cache in real time when the network is good. This projection is a non-blocking asynchronous transmission, employing a Write-Ahead Log (WAL) mechanism to ensure state consistency.

[0105] As an example, the inputs to the mirroring projection module are the PREHEAT signal and the edge runtime state (window tree, memory page differences, and input event logs).

[0106] As an example, the output of the mirror projection module is the vehicle-side hot standby mirror cache (including state levels: UI / memory / events).

[0107] The projection queue is scheduled according to priority: events > memory pages > UI;

[0108] Event layer target latency: P95≤50ms; memory page packet size: 4MB page / block; UI layer cycle time: 200~500ms;

[0109] WAL structure:<seq,op,addr / page_id,payload_hash,ts> ACK after the plate is placed.

[0110] The mirroring module can project the edge-end runtime state (such as window tree, memory page differences, and input event logs) to the vehicle end based on the PREHEAT signal when network conditions are still available, forming a hot standby mirror cache. Different projection frequencies can be set according to the importance of the state (low-frequency UI, medium-frequency memory, and high-frequency events) to optimize resource utilization. At the same time, write-alive logging (WAL) and asynchronous pre-ordered queues can ensure state consistency without blocking the main session, improving system stability.

[0111] The Offline Execution Module (OEM) is used to automatically migrate the desktop system from the edge node to the vehicle-side image to continue running when a network quality degradation or interruption is detected.

[0112] The offline execution module can restore the desktop runtime environment based on the latest snapshot, entering "offline degradation mode": disabling functions that rely on real-time networks, such as remote collaboration and video conferencing; retaining local computing, data browsing, and document editing functions; and recording all operation changes as local difference logs (LocalDiffLog). This improves offline availability.

[0113] The inputs to the offline running module can be the DOWNGRADE signal and the vehicle-side hot standby mirror handle.

[0114] The output of the offline running module can be either offline running state or local differential log (LDL).

[0115] The dual-track differential log includes parallel recording of the interaction track (UI / input) and the state track (page change), which facilitates playback.

[0116] As an example, if entering offline mode, you can: freeze threads that depend on the cloud, and open two logging channels: an interactive channel and an interactive channel.<ts,win_id,input_type,payload> and status channels:<ts,page_id,hash_before,hash_after> It records the log write-to-disk cycle: 100~200ms; single file scrolling limit: 128MB.

[0117] Upon receiving the DOWNGRADE signal, the offline running module enters the offline running state using the vehicle-side hot standby image handle and records a local differential log (LDL) to maintain editability and operability under network outage / weak network conditions.

[0118] The Differential Write-Back Module (DCM) is used to compare the difference logs generated on the vehicle with the edge mirror status after network recovery. A minimum difference packet is generated using an algorithm combining page-level comparison and operation sequence replay. After verification, the minimum difference packet is written back to the edge mirror and synchronized from the edge nodes to the cloud master mirror, completing the state merging.

[0119] As an example, the inputs to the differential write-back module can be: the RECOVER signal, the vehicle-side LDL, the vehicle-side current page hash H_c, and the edge page hash H_e.

[0120] As an example, the output of the differential write-back module can be the minimum differential packet Δ and the merged state. Its purpose is to minimize transmission volume during offline write-back to the edge / cloud.

[0121] As an example, the image can be paginated according to a page size P = 4MB and a total number of pages N. The page hash is represented as h_i = H(page_i), and the Merkle tree root R = H(h_1||...||h_N) is constructed; the difference set is represented as D = {i|h_i^c≠h_i^e}; the minimum difference packet is represented as Δ = {(i,page_i^c,h_i^c,ts_i)|i∈D}. LZ4 / Zstd compression can be used, and HMAC-SHA256(Δ) transmission verification can be employed.

[0122] It should be understood that by transmitting only the differing leaf pages through page-level Merkle differential, a large amount of redundant data can be eliminated (up to 90%+ redundancy elimination), reducing bandwidth consumption. At the same time, by reusing the same page fingerprint, duplicate uploads are avoided, further improving transmission efficiency.

[0123] In one possible implementation, the in-vehicle desktop system may also include the following modules:

[0124] The Consistency Coordination Module (COM) is responsible for processing the differential and operation logs of the vehicle and edge ends. It automatically determines conflict relationships through operation cause-effect graphs and vector timestamps, and generates a merged unified state.

[0125] As an example, the inputs to the consistency coordination module can be vehicle-side differential Δ_c, edge differential Δ_e, operation log set OL_c / OL_e, and snapshot index S.

[0126] As an example, the output of the consistency coordination module can be the merged unified state, conflicting branches (if necessary), and a new snapshot.

[0127] As an example, the consistency coordination module can use an operational causal graph with vector timestamp annotations to automatically determine parallel / conflict relationships; among them, a backtrackable branch mirror is used to retain branch snapshots for manual decision-making when conflicts cannot be resolved automatically.

[0128] As an example, the implementation process of the consistency coordination module can be as follows:

[0129] For each operation, assign a VT (vector timestamp) and a resource key K;

[0130] If VT_c || VT_e (parallel and K disjoint) → safe parallel merging;

[0131] If K is the same and VT_c ⧸ ⧹ VT_e (not synchronized) → trigger conflict strategy:

[0132] Strategy 1 (Configuration): Override with the latest TypeScript;

[0133] Strategy 2 (Document Class): Create branches {branchA, branchB} and prompt the user;

[0134] Generate a merged snapshot S' and write it to SSM.

[0135] It should be understood that this module ensures consistency, reduces manual intervention, and improves the system's automation level through automatic conflict detection and merging. Simultaneously, when conflicts cannot be resolved automatically, branch snapshots are retained for manual decision-making, enhancing system flexibility.

[0136] The Security and Snapshot Management (SSM) module is responsible for managing snapshots, differentials, and signing keys, generating signed snapshot chains and integrity certificates, providing rollback points, and ensuring the security and traceability of images.

[0137] As an example, the inputs to the security and snapshot management module can be snapshot (Snap), differential (Δ), signature key (K), and remote proof report (RA).

[0138] As an example, the output of the security and snapshot management module can be a signed snapshot chain, integrity proof, and rollback point.

[0139] As an example, the security and snapshot management module can be implemented using the following algorithm:

[0140] Snapshot signature: sig=Sign_K(hash_root||ver||ts||meta)

[0141] Chained verification: S_i.hash_prev==H(S_{i-1})

[0142] Rollback strategy: If the verification fails or the RA is abnormal, rollback to S_{last_good}.

[0143] By using a three-layer signature snapshot chain—vehicle-side snapshot 1, edge-side snapshot 3, and cloud-side full history—different numbers of snapshots can be saved at the vehicle-side, edge, and cloud, forming a complete trust chain.

[0144] "Dirty merge" is prevented by ensuring the integrity of differential applications through remote proof.

[0145] The Strategy and Telemetry Module (PTM) is used to collect indicator data from NQM and other modules. Through algorithms, it dynamically adjusts thresholds, page sizes, frequency parameters, etc., to achieve adaptive optimization and operational visibility.

[0146] As an example, the inputs to the strategy and telemetry module can be NQM and the metrics of each module (startup time, P95 latency, differential volume, failure rate).

[0147] As an example, the output of the policy and telemetry module can be a dynamic threshold (T1 / T2), page size P, frequency parameters, QoS priority, and alarms.

[0148] As an example, the policy and telemetry module can implement its functionality in the following way:

[0149] Periodic optimization: Use the metrics from the past 7 days to perform a Bayesian / grid search to obtain the parameter set;

[0150] Strategy implementation: Segment configuration based on region and vehicle type tags (A / B).

[0151] It should be understood that threshold profiling based on time period / geographic region can more accurately adapt to parameter requirements in different scenarios. Simultaneously, through metric-driven parameter self-tuning, parameters can be automatically adjusted based on real-time metrics, improving system performance and stability.

[0152] Based on the in-vehicle desktop display method provided in the above embodiments, see [link to relevant documentation]. Figure 3 This application also provides a schematic diagram of the structure of an in-vehicle desktop display device.

[0153] Combination Figure 3 As shown, the in-vehicle desktop display device 30 provided in this application embodiment is applied to an in-vehicle terminal and includes:

[0154] Acquisition unit 31 is used to acquire wireless link indicators and vehicle dynamic data;

[0155] Determining unit 32 is used to determine the real-time network quality index based on wireless link indicators and vehicle dynamic data;

[0156] Prediction unit 33 is used to determine the predicted network quality within a preset time period based on a pre-trained network quality prediction model and the real-time network quality index.

[0157] The first display unit 34 is used to obtain real-time desktop data through the edge node corresponding to the vehicle terminal if the predicted network quality is greater than or equal to a preset network quality threshold; the real-time desktop data is used to display the corresponding real-time vehicle desktop through the vehicle terminal.

[0158] The second display unit 35 is used to obtain offline desktop data through the vehicle-side mirror in the vehicle terminal if the predicted network quality is less than a preset network quality threshold; the offline desktop data is used to display the corresponding offline vehicle desktop through the vehicle terminal.

[0159] As one possible implementation, after the second display unit 35, the device further includes: a differential write-back unit, used for:

[0160] If the new predicted network quality is greater than or equal to the preset network quality threshold, the local difference log is compared with the edge mirror state corresponding to the edge node to obtain the minimum difference packet.

[0161] The minimum difference packet is synchronized to the cloud via the edge node.

[0162] As one possible implementation, the differential write-back unit is used for:

[0163] Obtain the first hash value of the current page based on the local difference log;

[0164] Obtain the second hash value of the edge page based on the edge mirror state;

[0165] The difference subpage is determined based on the first hash value and the second hash value to obtain the difference set; wherein the difference subpage represents the subpage that differs from the current page and the edge page; the difference set includes at least one difference subpage;

[0166] The minimum difference packet is determined based on the difference set.

[0167] As one possible implementation, if the predicted network quality is less than a preset network quality threshold, the device further includes: a freezing and recording unit, used for:

[0168] Freeze the target thread associated with the cloud and record interaction information and state change information.

[0169] It should be noted that the vehicle desktop display device provided in this application embodiment has the same beneficial effects as the vehicle desktop display method provided in the above embodiments, and therefore will not be described again.

[0170] In one possible implementation, see Figure 4 The figure is a schematic diagram of a control device provided in an embodiment of this application.

[0171] The control device may include a memory 411 and a processor 412. For example... Figure 4 As shown, the memory can be random access memory (RAM), flash memory, read-only memory (ROM), EPROM, non-volatile read-only memory (Electronic Programmable ROM), registers, hard disks, removable disks, etc.

[0172] The memory 411 can store computer instructions. When the computer instructions stored in the memory 411 are executed by the processor 412, the processor 412 can be used to execute the in-vehicle desktop display method. The memory 411 can also store data, such as information like the preset network quality threshold involved in the above embodiments.

[0173] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of this application is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape) or a semiconductor medium (e.g., solid-state disk (SSD)).

[0174] This application also provides a readable storage medium for storing the methods provided in the above embodiments. Examples include random access memory (RAM), flash memory, read-only memory (ROM), EPROM, non-volatile read-only memory (EPROM), registers, hard disks, removable disks, or any other form of storage medium in the art.

[0175] In the embodiments of this application, the terms "first" and "second" (if they exist) are used only as name identifiers and do not represent the order of first and second.

[0176] It should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. Regarding the methods disclosed in the embodiments, since they correspond to the product embodiments disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to in the description of the product embodiments.

[0177] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for displaying a vehicle-mounted desktop, characterized in that, The method is applied to an in-vehicle terminal and includes: Acquire wireless link metrics and vehicle dynamic data; The real-time network quality index is determined based on the wireless link metrics and the vehicle dynamic data. Based on the pre-trained network quality prediction model, the predicted network quality within a future preset time period is determined according to the real-time network quality index. If the predicted network quality is greater than or equal to a preset network quality threshold, then real-time desktop data is obtained through the edge node corresponding to the vehicle terminal; the real-time desktop data is used to display the corresponding real-time vehicle desktop through the vehicle terminal. If the predicted network quality is less than a preset network quality threshold, then offline desktop data is obtained through the vehicle-mounted mirror in the vehicle terminal; the offline desktop data is used to display the corresponding offline vehicle desktop through the vehicle terminal.

2. The in-vehicle desktop display method according to claim 1, characterized in that, After acquiring the offline desktop data, the method further includes: If the new predicted network quality is greater than or equal to the preset network quality threshold, the local difference log is compared with the edge mirror state corresponding to the edge node to obtain the minimum difference packet. The minimum difference packet is synchronized to the cloud through the edge node.

3. The in-vehicle desktop display method according to claim 2, characterized in that, The step of comparing the local difference log with the edge mirror state corresponding to the edge node to obtain the minimum difference packet includes: Obtain the first hash value of the current page based on the local difference log; Obtain the second hash value of the edge page based on the edge mirror state; The difference subpage is determined based on the first hash value and the second hash value to obtain a difference set; wherein the difference subpage represents a subpage that differs from the current page and the edge page; the difference set includes at least one difference subpage; The minimum difference packet is determined based on the difference set.

4. The in-vehicle desktop display method according to claim 1, characterized in that, If the predicted network quality is less than a preset network quality threshold, the method further includes: Freeze the target thread associated with the cloud and record interaction information and state change information.

5. A vehicle-mounted desktop display device, characterized in that, The device is applied to an in-vehicle terminal and includes: The acquisition unit is used to acquire wireless link indicators and vehicle dynamic data. A determining unit is configured to determine a real-time network quality index based on the wireless link indicators and the vehicle dynamic data; The prediction unit is used to determine the predicted network quality within a preset time period based on the pre-trained network quality prediction model and the real-time network quality index. The first display unit is used to obtain real-time desktop data through the edge node corresponding to the vehicle terminal if the predicted network quality is greater than or equal to a preset network quality threshold; the real-time desktop data is used to display the corresponding real-time vehicle desktop through the vehicle terminal. The second display unit is used to obtain offline desktop data through the vehicle-side mirror in the vehicle terminal if the predicted network quality is less than a preset network quality threshold; the offline desktop data is used to display the corresponding offline vehicle desktop through the vehicle terminal.

6. The vehicle-mounted desktop display device according to claim 5, characterized in that, Following the second display unit, the device further includes: a differential write-back unit, used for: If the new predicted network quality is greater than or equal to the preset network quality threshold, the local difference log is compared with the edge mirror state corresponding to the edge node to obtain the minimum difference packet. The minimum difference packet is synchronized to the cloud through the edge node.

7. The vehicle-mounted desktop display device according to claim 6, characterized in that, The differential write-back unit is used for: Obtain the first hash value of the current page based on the local difference log; Obtain the second hash value of the edge page based on the edge mirror state; The difference subpage is determined based on the first hash value and the second hash value to obtain the difference set; The difference subpage represents a subpage that differs from the current page and the edge page; the difference set includes at least one difference subpage; The minimum difference packet is determined based on the difference set.

8. The vehicle-mounted desktop display device according to claim 5, characterized in that, If the predicted network quality is less than a preset network quality threshold, the device further includes: a freezing and recording unit, used for: Freeze the target thread associated with the cloud and record interaction information and state change information.

9. A control device, characterized in that, It includes a processor and a memory, the memory being used to store programs, instructions, or code, and the processor being used to execute the programs, instructions, or code in the memory to perform the in-vehicle desktop display method as described in any one of claims 1-4.

10. A computer-readable storage medium, characterized in that, The system contains a computer program that is loaded by a processor to execute the in-vehicle desktop display method as described in any one of claims 1-4.

Images