A cross-domain information distribution method and system for multi-link cooperative networking

Abstract

This application discloses a method and system for cross-domain information distribution in multi-link collaborative networking, relating to the field of network communication technology. The method, applied to the information sending end, includes: dynamically selecting a primary transmission path and at least one backup path for cross-domain information from all data transmission links based on the computing power level of the information receiving end and the link quality prediction results of each data transmission link. Based on the link quality of the primary transmission path, the data to be distributed is fragmented and encoded to obtain multiple data packets to be distributed. The data packets to be distributed are transmitted to the information receiving end through the primary and backup paths, allowing the information receiving end to decode and reassemble the data packets. This application effectively improves the stability, real-time performance, and resource utilization efficiency of cross-domain information distribution in multi-link collaborative networking, significantly improving the transmission performance of cross-domain data transmission.

Description

Technical Field

[0001] This application relates to the field of network communication technology, and in particular to a cross-domain information distribution method and system for multi-link collaborative networking. Background Technology

[0002] With the rapid development of network and communication technologies, cross-domain information distribution based on multi-link collaborative networking is increasingly being used in fields such as emergency communication and command and control. However, the quality differences and dynamic changes of different network data transmission links, as well as the limitations of terminal device computing power, pose significant challenges to reliable cross-domain data transmission.

[0003] In related technologies, cross-domain data transmission typically relies on a pre-defined single path and fixed encoding strategy, failing to adequately consider real-time prediction of the status of each data transmission link. The encoding mechanism also lacks adaptability to different packet loss conditions. When dealing with packet loss, most methods still employ feedback retransmission strategies. When the number of data receivers is large or the packet loss rate is high, repeated data identification and retransmission are necessary, generating a large amount of redundant data within the transmission network. Therefore, how to efficiently achieve cross-domain data distribution and recovery is a pressing issue that needs to be addressed in current cross-domain information distribution technologies for multi-link collaborative networking. Summary of the Invention

[0004] The main objective of this application is to provide a method and system for cross-domain information distribution in multi-link collaborative networking, aiming to solve the technical problem of low efficiency in cross-domain information distribution in related technologies for multi-link collaborative networking. The method includes:

[0005] A cross-domain information distribution method for multi-link collaborative networking, characterized by comprising:

[0006] Based on the computing power level of the information receiving end and the link quality prediction results of each data transmission link, the main transmission path and at least one backup path for cross-domain information are dynamically selected from all data transmission links.

[0007] Based on the link quality of the main transmission path, the data to be distributed is fragmented and encoded to obtain multiple data packets to be distributed; the encoding method includes one of no encoding, erasure coding, and fountain coding.

[0008] The data packets to be distributed are transmitted to the information receiving end through the main transmission path and the backup path, so that the information receiving end can decode and reassemble the data packets to be distributed.

[0009] In one embodiment, the step of dynamically selecting the primary transmission path and at least one backup path for cross-domain information based on the computing power level of the information receiving end and the data transmission link quality prediction results of each data transmission link includes:

[0010] The computing power level of the information receiver is determined based on its hardware performance indicators and actual decoding capabilities.

[0011] For each data transmission link, the link state is modeled using a two-state Markov chain model, and the state transition probability and packet loss rate of each data transmission link state are statistically analyzed; the link state includes a good state or a deteriorated state.

[0012] Based on the state transition probability and packet loss rate, the link packet loss rate within the prediction time window is determined; wherein, the length of the prediction time window is negatively correlated with the state transition probability.

[0013] Based on the real-time quality parameters and predicted packet loss rate of the data transmission link, a link quality evaluation function is constructed to determine the real-time link quality score; wherein, the weight of each parameter of the link quality evaluation function is determined based on the computing power level of the information receiving end;

[0014] Based on real-time link quality scoring, the primary transmission path and at least one backup path for cross-domain information are dynamically selected.

[0015] In one embodiment, the step of dynamically selecting the primary transmission path and at least one backup path for cross-domain information based on real-time link quality scoring includes:

[0016] If the backup path with the highest real-time link quality score has a higher link quality score than the primary transmission path for a certain period of time, then the backup path with the highest real-time link quality score will be switched to the primary transmission path.

[0017] In one embodiment, the step of fragmenting and encoding the data to be distributed based on the link quality of the main transmission path to obtain multiple data packets to be distributed includes:

[0018] Determine the packet loss rate of the main transmission path. If the packet loss rate is lower than the first threshold, then use an adaptive side-length fragmentation method to fragment the data to be distributed.

[0019] If the link packet loss rate is not lower than the first threshold and is lower than the second threshold, the data to be distributed is fragmented and then interleaved and rearranged, and then each rearranged data fragment is encoded based on Reed-Solomon erasure coding.

[0020] If the packet loss rate is not lower than the second threshold, the data to be distributed is fragmented and then each data fragment is encoded based on the RaptorQ fountain code.

[0021] In one embodiment, the step of transmitting the data packet to be distributed to the information receiving end via the main transmission path and the backup path includes:

[0022] After the data packets to be sent are split according to the link quality prediction results of the main transmission path and the backup path, they are transmitted through different transmission paths.

[0023] Determine the priority of the data packets to be sent;

[0024] Copy the high-priority core data packets and send all core data packets to the data receiving end in parallel through the main transmission path and the backup transmission path;

[0025] In one embodiment, to achieve the above objective, this application further provides a cross-domain information distribution method for multi-link cooperative networking, applied at the information receiving end, the method comprising:

[0026] The data packets are sorted according to their sequence numbers. Based on the encoding and fragmentation methods of the data packets, the data packets are decoded and reassembled to obtain complete data.

[0027] Perform end-to-end integrity checks on complete data.

[0028] Secondly, to achieve the above objectives, this application further provides a cross-domain information distribution system for multi-link collaborative networking, the system comprising:

[0029] The transmission path determination module is used to dynamically select the main transmission path and at least one backup path for cross-domain information from all data transmission links based on the computing power level of the information receiving end and the link quality prediction results of each data transmission link.

[0030] The data processing module is used to perform fragmentation and encoding processing on the data to be distributed based on the link quality of the main transmission path, to obtain multiple data packets to be distributed; wherein the encoding method includes one of no encoding, erasure coding, and fountain coding;

[0031] The data sending module is used to transmit the data packets to be distributed to the information receiving end through the main transmission path and the backup path, so that the information receiving end can decode and reassemble the data packets to be distributed.

[0032] The data receiving module is used to sort data packets according to sequence number identifiers, and perform data packet decoding and reassembly processing based on the data packet encoding and fragmentation methods to obtain complete data.

[0033] The integrity verification module is used to perform end-to-end integrity verification on complete data.

[0034] One or more technical solutions proposed in this application have at least the following technical effects:

[0035] This application achieves high efficiency and reliability in the entire process of cross-domain information distribution for multi-link collaborative networking by introducing a link quality prediction-driven dynamic path selection mechanism and a coding strategy based on packet loss rate adaptive adjustment. Firstly, by combining the receiver's computing power level, link state transition probability, and predicted packet loss rate, the optimal primary path can be selected in real time and backup paths can be switched promptly, significantly reducing transmission performance fluctuations caused by link degradation. Secondly, a hierarchical adaptive coding mechanism using no coding, erasure coding, and fountain coding ensures optimal balance between redundancy overhead and decoding efficiency under different packet loss environments, improving the robustness of cross-domain transmission. Thirdly, multi-path diversion based on quality prediction and parallel redundant transmission of high-priority data further reduce the risk of critical data loss. Fourthly, a unified fragmentation / coding identification, decoding reassembly, and integrity verification process at the receiver ensures the reliability of end-to-end data recovery. In summary, this application effectively improves the stability, real-time performance, and resource utilization efficiency of cross-domain information distribution for multi-link collaborative networking, significantly improving the transmission performance of cross-domain data transmission. Attached Figure Description

[0036] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0037] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the accompanying drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, those skilled in the art can obtain other drawings based on these drawings without creative effort.

[0038] Figure 1 This is a flowchart illustrating the cross-domain information distribution method and system for multi-link collaborative networking proposed in this application.

[0039] Figure 2 This is a schematic diagram of the cross-domain information distribution system for multi-link collaborative networking in this application.

[0040] Figure 3 This is a schematic diagram of the cross-domain information distribution terminal for multi-link collaborative networking applied to the information sending end in this application.

[0041] Figure 4 This is a schematic diagram of the cross-domain information distribution terminal for multi-link collaborative networking applied to the information receiving end in this application.

[0042] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0043] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0044] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0045] The main solution of this application embodiment is as follows: by combining receiver computing power level evaluation, Markov prediction modeling of link status, and real-time link quality scoring, the optimal primary path and backup path are dynamically selected for cross-domain data transmission. Different encoding methods, such as no encoding, erasure coding, or fountain coding, are adaptively selected based on the packet loss rate of the primary path to ensure optimal reliability and transmission efficiency under different network quality conditions. Simultaneously, the solution also ensures robust transmission of critical data in complex cross-domain environments through prediction-driven multi-path routing and parallel redundant transmission of high-priority data. At the receiver, a unified decoding and reassembly mechanism restores complete data. Overall, this achieves an efficient, reliable, and intelligent cross-domain information distribution method for complex links and multi-receiver scenarios, oriented towards multi-link collaborative networking.

[0046] Specifically, most current data transmission schemes typically rely on pre-defined single paths and fixed encoding strategies, failing to adequately consider real-time prediction of link states. The encoding mechanisms also lack adaptability to different packet loss conditions. When dealing with packet loss, most methods still employ feedback retransmission strategies. When the number of data receivers is large or the packet loss rate is high, repeated data identification and retransmission are necessary, generating a large amount of redundant data within the transmission network. Classic TCP uses sequence number verification for data segmentation and reassembly, but it is poorly adapted to high packet loss scenarios. Erasure coding performs well in distributed storage and transmission, but lacks an adaptive adjustment mechanism based on the receiver's computing power and link states.

[0047] To address these issues, this embodiment provides a cross-domain information distribution method for multi-link collaborative networking. It combines link status prediction, terminal computing power grading, and adaptive coding decision-making to form a collaborative optimization mechanism, referring to... Figure 1 , Figure 1 This is a schematic diagram of the cross-domain information distribution process for multi-link collaborative networking in this embodiment.

[0048] Reference Figure 1 In this embodiment, the cross-domain information distribution method for multi-link collaborative networking includes steps S10 to S50:

[0049] Step S10: Based on the computing power level of the information receiving end and the link quality prediction results of each data transmission link, dynamically select the main transmission path and at least one backup path for cross-domain information from all data transmission links.

[0050] It should be noted that the computing power level of the information receiving end is determined based on the computing capability information of the information receiving end. In this embodiment, the computing power level can be divided into three levels (L1, L2 and L3). For example, information receiving ends with weak computing power, such as smartphones and ordinary PCs, are classified as L1 level, workstations and small servers with medium performance are classified as L2 level, and information receiving ends with strong computing power, such as L3 high-performance servers or cloud nodes, are classified as L3 level.

[0051] It should also be noted that information such as packet loss rate, latency, and jitter of the transmission link can reflect the link quality, and the distinction between the primary transmission path and the backup path is dynamically made based on the link quality of each transmission link.

[0052] In one feasible implementation, step S10 includes steps A10 to A50:

[0053] Step A10: Determine the computing power level of the information receiving end based on its hardware performance indicators and actual decoding capabilities.

[0054] Step A20: For each data transmission link, perform link state modeling using a two-state Markov chain model, and statistically analyze the state transition probability of each data transmission link and the packet loss rate under each link state; where the link state includes a good state or a deteriorated state.

[0055] Step A30: Based on the state transition probability and packet loss rate, determine the link packet loss rate within the prediction time window; wherein, the length of the prediction time window is negatively correlated with the state transition probability.

[0056] Step A40: Based on the real-time quality parameters and predicted packet loss rate of the data transmission link, construct a link quality evaluation function to determine the real-time link quality score; wherein, the weights of each parameter in the link quality evaluation function are determined based on the computing power level of the information receiving end.

[0057] Step A50: Based on the real-time link quality score, dynamically select the primary transmission path and at least one backup path for cross-domain information.

[0058] Specifically, the hardware performance indicators of the information receiving end can include CPU clock speed, number of cores, memory capacity, etc., and the actual decoding capability is represented by the actual decoding capability test results. For example, the computing power level of the information receiving end can be determined by setting threshold conditions.

[0059] For link quality assessment, this implementation uses the Gilbert-Elliott dual-state Markov model to model the packet loss state of each transmission link. The success / loss of link packets within a certain period is statistically analyzed by a sliding time window. The number of switching between good and degraded states is recorded. Maximum likelihood estimation is used to calculate the transition probability from good to degraded state and from degraded to good state, and the packet loss rate in each state is determined.

[0060] After determining the state transition probability and packet loss rate, the packet loss trend (predicted packet loss rate) within the prediction time window is determined based on the packet loss rate. In this embodiment, the link state data observed within the prediction time window is used to predict the short-term packet loss trend. Specifically, for situations with drastic changes in the network environment (high state transition probability, such as high-speed mobile scenarios or complex electromagnetic environments), the window time is shortened; when the data transmission link is in a relatively stable environment, the window time can be increased to reduce errors.

[0061] Furthermore, based on the real-time quality parameters of the data transmission link and the predicted packet loss rate, a link quality evaluation function is constructed to determine the real-time link quality score.

[0062] For example, for each data transmission link, its real-time packet loss rate (PLR), latency (RTT), jitter, bandwidth utilization (bps), and other quality parameters are measured, and a link score is calculated by combining load balancing weights and predicted packet loss rate, which can be specifically expressed as:

[0063]

[0064] Where Slink represents the link quality score, A, B, C and D represent the corresponding load balancing weights, A+B+C+D=1, and P represents the predicted packet loss rate.

[0065] The load balancing weights are dynamically adjusted based on the computing power level of the data receiver. For example, for L1 level data receivers, the score of high packet loss links is reduced (that is, the weight of A is reduced) to avoid selecting paths that require large-scale error correction. For L3 level data receivers, the best path with low latency and high bandwidth can be selected (that is, the weight of A and B is increased).

[0066] Subsequently, the link with the highest link quality score is selected as the primary transmission path, and the link with the second-highest score is selected as the backup transmission path when needed, so as to perform backup or parallel redundant transmission.

[0067] In this embodiment, step A50 includes step A51:

[0068] Step A51: If the link quality score of the backup path with the highest real-time link quality score is higher than that of the primary transmission path for a certain period of time, then the backup path with the highest real-time link quality score will be switched to the primary transmission path.

[0069] Specifically, to prevent frequent switching of link selection, this implementation introduces a decision-making switching lag strategy. When the quality of the backup link is slightly better than that of the main link, the system will not switch immediately. The switch will only be performed after the advantage reaches a certain threshold and remains stable for a period of time.

[0070] Understandably, using the Gilbert-Elliott model to predict the short-term state of a link can help anticipate the risk of sudden packet loss. By introducing the Gilbert-Elliott two-state model, we define two states for the link: a good state and a bad state. In the good state, the link has a low packet loss rate, mainly consisting of random single packet losses. In the bad state, the link experiences sudden high packet loss. By using a sliding window to statistically analyze the packet transmission and reception of the link, we can dynamically estimate the state transition probability of the model and the packet loss rate in each state. This allows us to infer the probability that the link will be in a good or bad state within the future prediction time window, thereby predicting the packet loss rate and its trend in the short term.

[0071] This implementation also introduces a combination of primary and backup paths. When the conditions of the suboptimal link are also good, it can be set as the backup path. The backup link is activated when the primary path experiences anomalies or insufficient bandwidth, or it can run in parallel with the primary path to share some traffic when higher bandwidth is required. In an example scenario, available cross-domain links include 5G cellular networks, low-Earth orbit satellite links, and wired fiber optic networks. The transmitting end applies the above method to assess the quality of each link. Currently, the 5G link has a packet loss rate of only 0.5% and low latency, the satellite link has a packet loss rate of 5% and high latency, and the fiber optic network has almost no packet loss but its bandwidth utilization is close to saturation. The Gilbert-Elliott model predicts that the 5G link is highly likely to maintain a good state in the short term, while the satellite link may experience a brief period of bad state. The receiving end's computing power level is L2 (medium). Taking all factors into consideration, the transmitting end selects the 5G link as the primary path. Since the satellite link has a relatively high packet loss rate and L2 computing power can handle some error correction overhead, it is chosen as the secondary path for parallel transmission to send some redundant data in case of occasional interruptions to the primary link. The fiber optic network was not selected due to congestion. In subsequent steps, the coding scheme will also adaptively adjust to this link condition.

[0072] Step S20: Based on the link quality of the main transmission path, the data to be distributed is fragmented and encoded to obtain multiple data packets to be distributed; wherein, the encoding method includes one of no encoding, erasure coding, and fountain coding.

[0073] This step is mainly used to determine the data encoding and packetization scheme based on the link quality of the selected main transmission path and the computing power level of the information receiving end, and to appropriately split and encode the data to be distributed.

[0074] In one feasible implementation, step S20 includes steps B10 to B30:

[0075] Step B10: Determine the packet loss rate of the main transmission path. If the packet loss rate is lower than the first threshold, then use an adaptive side-length fragmentation method to fragment the data to be distributed.

[0076] Step B20: If the link packet loss rate is not lower than the first threshold and is lower than the second threshold, the data to be distributed is fragmented and then interleaved and rearranged, and then each rearranged data fragment is encoded based on Reed-Solomon erasure coding.

[0077] Step B30: If the packet loss rate is not lower than the second threshold, then after the data to be distributed is fragmented, each data fragment is encoded based on the RaptorQ fountain code.

[0078] In this embodiment, the first threshold and the second threshold are used to determine the fragmentation method and encoding method of the data to be distributed, and are generally empirical thresholds.

[0079] For example, the first threshold can be 1%, and the second threshold can be 10%. Specifically, if the packet loss rate of the data transmission link is ≤1%, the data packets are split using an adaptive side-length fragmentation method; if the packet loss rate is between 1% and 10%, the data is redundantly encoded using an improved Reed-Solomon erasure coding method; if the packet loss rate is ≥10%, the data is encoded using RaptorQ fountain codes.

[0080] Understandably, this example sets packet loss rate thresholds at 1% and 10%, respectively defining the network link as "good" and "poor." When the packet loss rate is below 1%, users will hardly perceive any impact. When the packet loss rate exceeds 1%, users will clearly perceive a decrease in quality. At 10%, the application becomes unusable. Using 1% and 10% as trigger points, a forward error correction redundancy mechanism is activated when the packet loss rate exceeds 1%, and a fountain code with higher redundancy is switched when it exceeds 10%, to ensure reliable data transmission under high packet loss conditions. Understandably, the thresholds can be adjusted according to different application scenarios.

[0081] Furthermore, in this example, for cases where the link packet loss rate is lower than the first threshold, adaptive variable-length fragmentation coding is adopted. The fragment size is dynamically determined based on the maximum transmission unit of the transmission path minus the protocol header overhead. The fragment length can be reduced according to the application's latency requirements to reduce transmission delay. Each fragment is appended with a sequence number and a checksum so that the receiver can detect loss and request retransmission of missing segments through the ARQ mechanism.

[0082] For cases where the link packet loss rate is not lower than the first threshold and lower than the second threshold, a combination of interleaving and Reed-Solomon erasure coding is used. The original data is divided into n data blocks, and their order is shuffled by interleaving. Then, Reed-Solomon coding is used to generate k redundant check blocks for the interleaved data blocks. The interleaving depth is adjusted according to the burst packet loss length estimated by the Gilbert-Elliott model (adaptively selected between 2 and 10 by default). Specifically, the interleaving depth is dynamically set according to the average burst packet loss length predicted by the Gilbert-Elliott model. If the burst packet loss duration is expected to be long, a larger interleaving depth (e.g., 8 or 10) is used to ensure that the continuously lost blocks are distributed into different check groups after interleaving; otherwise, a smaller depth can be used to reduce latency.

[0083] It's worth noting that the Reed-Solomon encoding parameters n and k are selected based on link reliability requirements. As long as the receiver successfully receives at least n blocks of any combination, the original data can be reconstructed. For scenarios requiring a reception success rate of at least 99%, appropriate redundancy can be selected based on the average packet loss rate of the link. On links with an average packet loss of around 5%, approximately 20% redundant encoding blocks can be configured to ensure a decoding success rate of over 99% at this actual packet loss rate. In severe environments, the redundancy ratio should be increased accordingly. If the receiver detects that the number of lost data blocks exceeds the number of redundant check blocks k, a retransmission request is triggered to obtain additional data blocks for recovery.

[0084] For cases where the packet loss rate is not lower than the second threshold, the original data is encoded into a potentially infinite number of encoded packets. During transmission, a certain redundancy is added based on the predicted packet loss rate. The redundancy transmission ratio is adaptively determined based on the predicted packet loss rate P. Considering the superlinear relationship between the fountain code redundancy rate and the link packet loss rate, a redundancy slightly higher than P needs to be sent. Specifically, the actual redundancy factor is set to approximately 103%-110%. The sender can also dynamically adjust the actual number of encoded packets sent based on the predicted link packet loss rate: if the predicted packet loss rate is p, approximately n / (1-p) encoded packets can be sent to ensure, with a high probability, that the receiver receives at least n different encoded packets. For example, when the predicted P is approximately 10%, the redundancy rate can be set to around 15%, meaning that approximately 15 redundant fragments are generated from the original 100 data fragments and sent, ensuring that the receiver still has sufficient redundant fragments for decoding and recovery. In addition, for L1 terminals with low computing power, fountain codes should generally be avoided unless the link conditions are extremely different and there is no other choice, so as to avoid overburdening the terminal due to the high complexity of the decoding process.

[0085] It is worth mentioning that in practical applications, link quality may change dynamically. This invention can periodically re-evaluate and adjust the coding scheme according to the new link status. When the packet loss rate of the current main path is detected to have increased from 0.5% to 5%, the sender can switch from pure fragmentation mode to a mode combining data interleaving and Reed-Solomon erasure coding in subsequent data transmission. If the packet loss rate continues to rise above 15%, it will further switch to fountain code mode to ensure reliability. This dynamic adaptive coding adjustment can be triggered automatically by a pre-set trigger threshold by the system, or it can be triggered by instructions from the network control node, thus always matching the current network conditions during long-term operation.

[0086] Step S30: The data packet to be distributed is transmitted to the information receiving end through the main transmission path and the backup path, so that the information receiving end can decode and reassemble the data packet to be distributed.

[0087] This step is used to integrate and transmit the encoded data through multiple network links, making full use of the multi-source transmission capabilities in a cross-domain environment to improve throughput and reliability.

[0088] In one feasible implementation, step S30 includes steps C10 to C30:

[0089] Step C10 involves splitting the data packets to be sent according to the link quality prediction results of the main transmission path and the backup path, and then transmitting them through different transmission paths.

[0090] Step C20: Determine the priority of the data packets to be sent.

[0091] Step C30: Copy the high-priority core data packets and send all core data packets in parallel to the data receiving end through the main transmission path and the backup transmission path.

[0092] Specifically, core data packets are prioritized for transmission via the main path. Simultaneously, when a backup path is available, a portion of the data or redundant encoded packets are transmitted in parallel via a backup link, achieving load balancing or redundancy backup. If multiple available links exist, data can be split into multiple sub-streams and transmitted via different links according to the bandwidth ratio or quality indicators of each link. For high-priority critical data, its encoded fragments are replicated and redundantly transmitted via multiple links, ensuring data can still be obtained through other links even if one link experiences performance degradation. Understandably, if only a single link is available, all data packets are transmitted via that link.

[0093] Understandably, the information sender utilizes multiple link resources in a cross-domain environment to distribute or replicate encoded data packets across multiple links for parallel transmission, thereby enhancing transmission performance. Based on the number of selected primary and backup transmission paths, appropriate strategies are adopted. When only a single path is available, the sender transmits all data packets sequentially through that path in the original order; this stage degenerates into conventional single-link transmission. When two or more available links exist, the sender splits and schedules the data stream.

[0094] It is worth mentioning that the sending end can dynamically adjust the allocation strategy of each path based on the link status prediction results. If it is predicted that a backup link is about to enter a deteriorating state, the proportion of data transmitted through that link will be temporarily reduced or only redundant coded packets will be allocated to reduce the risk of main data relying on this unstable link. Conversely, if it is predicted that the quality of a path will improve, the data traffic it carries will be increased accordingly. By incorporating the link prediction results into multi-path scheduling, the overall reliability and robustness of cross-domain transmission can be further improved.

[0095] It is also worth mentioning that during multi-link parallel transmission, the sending end also needs to pay attention to the fact that the difference in latency between different links may cause the receiving order to be out of order. The embodiment solves the out-of-order problem to a certain extent by using the inherent properties of encoding schemes such as fountain codes at the receiving end. Therefore, the sending end does not need to be strictly synchronized, but only needs to make the best use of the bandwidth and latency characteristics of each link to send its own data.

[0096] This implementation method fully utilizes the heterogeneous resources of the cross-domain network environment through multi-channel integrated transmission, improves the overall data transmission rate, and ensures that data on other links can still be delivered when a certain link is congested or interrupted, thereby improving the robustness of the system.

[0097] Step S40: Sort the data packets according to the sequence number identifier, and perform data packet decoding and data packet reassembly processing based on the data packet encoding method and fragmentation method to obtain complete data;

[0098] Step S50: Perform end-to-end integrity verification on the complete data.

[0099] Specifically, the receiving end receives and processes the data transmitted through each path, and performs corresponding decoding and data reassembly strategies according to the encoding and packetization methods used in the above implementation method to restore the original information;

[0100] Data packets are sorted according to their sequence numbers in fragments or encoded packets. An appropriate decoding process is applied to each encoding scheme. For data sent using adaptive fragmentation, the integrity of the sequence number and checksum of each fragment are checked. If a missing or corrupted fragment is found, a retransmission request is sent to the sender via the ARQ mechanism. For data encoded using improved Reed-Solomon erasure coding, deinterleaving is performed to restore the data order, and then the decoding capability of Reed-Solomon erasure coding is used to recover lost data blocks (if the number of lost data blocks does not exceed the erasure coding redundancy capacity k, all original data can be directly recovered; otherwise, a retransmission request is triggered). For data using RaptorQ fountain codes, after a sufficient number of encoded packets are received, the RaptorQ decoding algorithm is used to reconstruct the original data. When the number of received encoded packets is insufficient for decoding, the sender is requested to send additional packets until decoding is successful.

[0101] After the data reconstruction is completed, the terminal performs an end-to-end integrity check on the recovered complete data to ensure that the data has not been tampered with and has no residual errors during transmission.

[0102] It is understood that this embodiment, by integrating receiver computing power hierarchical evaluation, link state Markov prediction, and real-time quality scoring mechanism, achieves dynamic path selection and adaptive coding strategies (such as no coding, erasure coding, or fountain coding), significantly improving the reliability and efficiency of cross-domain data transmission. Especially in scenarios with high packet loss and multiple receivers, it avoids the feedback retransmission redundancy of traditional solutions and reduces network load. At the same time, multi-path diversion and priority redundant transmission ensure robust transmission of critical data, and unified decoding and reassembly at the receiver further guarantee data integrity. Overall, it is suitable for complex heterogeneous network environments and provides an efficient and intelligent cross-domain information distribution solution for multi-link collaborative networking.

[0103] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the cross-domain information distribution method for multi-link collaborative networking in this application. Any simple modifications based on this technical concept are within the protection scope of this application.

[0104] This application also provides a cross-domain information distribution system for multi-link collaborative networking. Please refer to... Figure 2The functional module structure of the system is shown. The data sending end of the cross-domain information distribution system for multi-link collaborative networking is equipped with the following functional modules:

[0105] The transmission path determination module 10 is used to dynamically select the main transmission path and at least one backup path for cross-domain information from all data transmission links based on the computing power level of the information receiving end and the link quality prediction results of each data transmission link.

[0106] The data processing module 20 is used to perform fragmentation and encoding processing on the data to be distributed based on the link quality of the main transmission path, to obtain multiple data packets to be distributed; wherein the encoding method includes one of no encoding, erasure coding and fountain coding;

[0107] The data sending module 30 is used to send the data packets to be distributed to the information receiving end through the main transmission path and the backup path, so that the information receiving end can decode and reassemble the received data packets to be distributed.

[0108] The data receiving module 40 is used to sort data packets according to sequence number identifiers, and perform data packet decoding and data packet reassembly processing based on the data packet encoding method and fragmentation method to obtain complete data;

[0109] The integrity verification module 50 is used to perform end-to-end integrity verification on complete data.

[0110] The transmission path determination module is also used for:

[0111] The computing power level of the information receiver is determined based on its hardware performance indicators and actual decoding capabilities.

[0112] For each data transmission link, the link state is modeled using a two-state Markov chain model, and the state transition probability and packet loss rate of each data transmission link state are statistically analyzed; the link state includes good state and deteriorated state.

[0113] Based on the state transition probability and packet loss rate, the link packet loss rate within the prediction time window is determined; wherein, the length of the prediction time window is negatively correlated with the state transition probability.

[0114] Based on the real-time quality parameters and predicted packet loss rate of the data transmission link, a link quality evaluation function is constructed to determine the real-time link quality score; wherein, the weight of each parameter of the link quality evaluation function is determined based on the computing power level of the information receiving end;

[0115] Based on real-time link quality scoring, the primary transmission path and at least one backup path for cross-domain information are dynamically selected.

[0116] If the backup path with the highest real-time link quality score has a higher link quality score than the primary transmission path for a certain period of time, then the backup path will be switched to the primary transmission path.

[0117] The data processing module is also used for:

[0118] Determine the packet loss rate of the main transmission path. If the packet loss rate is lower than the first threshold, then use an adaptive side-length fragmentation method to fragment the data to be distributed.

[0119] If the link packet loss rate is not lower than the first threshold and is lower than the second threshold, the data to be distributed is fragmented and then interleaved and rearranged, and then each rearranged data fragment is encoded based on Reed-Solomon erasure coding.

[0120] If the link packet loss rate is not lower than the second threshold, then after the data to be distributed is fragmented, each data fragment is encoded based on the RaptorQ fountain code.

[0121] The cross-domain information distribution system for multi-link collaborative networking provided in this application adopts the aforementioned cross-domain information distribution method for multi-link collaborative networking, which can solve the technical problem of low efficiency in cross-domain information distribution for multi-link collaborative networking in related technologies. Compared with related technologies, the beneficial effects of the cross-domain information distribution system for multi-link collaborative networking provided in this application are the same as those of the cross-domain information distribution method for multi-link collaborative networking provided in the above embodiments, and other technical features of this cross-domain information distribution system for multi-link collaborative networking are the same as those disclosed in the above method embodiments, and will not be repeated here.

[0122] The cross-domain information distribution system for multi-link collaborative networking described in this application can be implemented through a combination of hardware and software. In an exemplary embodiment, the system can be deployed on a data sending terminal and a data receiving terminal, each terminal including: at least one processor and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the processor to cause the processor to perform the steps of the cross-domain information distribution method for multi-link collaborative networking described above.

[0123] The following is for reference. Figure 3 and Figure 4 The diagrams show a cross-domain information distribution terminal suitable for implementing the embodiments of this application, which is applied to a data sending end for multi-link collaborative networking and a cross-domain information distribution terminal applied to a data receiving end for multi-link collaborative networking.

[0124] In the embodiments of this application, the data sending terminal and / or data receiving terminal may include, but are not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Description), PMPs (Portable Media Players), and in-vehicle terminals (e.g., in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. The illustrated cross-domain information distribution terminal for multi-link collaborative networking is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0125] like Figure 3 , Figure 4 As shown, the data sending terminal and / or data receiving terminal may include a processing device 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of cross-domain information distribution terminals in multi-link collaborative networking. The processing device 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to I / O interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. Communication device 1009 allows the cross-domain information distribution terminal for multi-link collaborative networking to exchange data with other devices via wireless or wired communication. Although the figure shows a cross-domain information distribution terminal for multi-link collaborative networking with various systems, it should be understood that it is not required to implement or possess all the systems shown. More or fewer systems can be implemented alternatively.

[0126] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0127] The cross-domain information distribution terminal for multi-link collaborative networking provided in this application, applied to the data sending end and / or the data receiving end, employs the cross-domain information distribution method for multi-link collaborative networking described in the above embodiments. This solves the technical problem of low efficiency in cross-domain information distribution for multi-link collaborative networking in related technologies. Compared with related technologies, the beneficial effects of the cross-domain information distribution terminal for multi-link collaborative networking provided in this application are the same as those of the cross-domain information distribution method for multi-link collaborative networking provided in the above embodiments. Furthermore, other technical features of this cross-domain information distribution terminal for multi-link collaborative networking are the same as those disclosed in the previous embodiment, and will not be repeated here.

[0128] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0129] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0130] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0131] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0132] The above are only some embodiments of this application and do not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A cross-domain information distribution method for multi-link collaborative networking, characterized in that, Applied to the information sending end, the method includes: Based on the computing power level of the information receiving end and the link quality prediction results of each data transmission link, the main transmission path and at least one backup path for cross-domain information are dynamically selected from all the data transmission links. Based on the link quality of the main transmission path, the data to be distributed is fragmented and encoded to obtain multiple data packets to be distributed; wherein, the encoding method includes one of no encoding, erasure coding, and fountain coding; The data packet to be distributed is transmitted to the information receiving end through the main transmission path and the backup path, so that the information receiving end can decode and reassemble the data packet to be distributed; The step of dynamically selecting the primary transmission path and at least one backup path for cross-domain information from all the data transmission links based on the computing power level of the information receiving end and the link quality prediction results of each data transmission link includes: The computing power level of the information receiving end is determined based on its hardware performance indicators and actual decoding capabilities. For each data transmission link, the link state is modeled using a two-state Markov chain model, and the state transition probability and packet loss rate of each data transmission link state are statistically analyzed; wherein the link state includes a good state or a deteriorated state. Based on the state transition probability and the packet loss rate, the link packet loss rate within the prediction time window is determined; wherein, the length of the prediction time window is negatively correlated with the state transition probability; Based on the real-time quality parameters and predicted packet loss rate of the data transmission link, a link quality evaluation function is constructed to determine the real-time link quality score; wherein, the weight of each parameter of the link quality evaluation function is determined based on the computing power level of the information receiving end; Based on the real-time link quality score, the primary transmission path and at least one backup path for cross-domain information are dynamically selected.

2. The cross-domain information distribution method for multi-link collaborative networking as described in claim 1, characterized in that, The step of dynamically selecting the primary transmission path and at least one backup path for cross-domain information based on the real-time link quality score includes: If the link quality score of the backup path with the highest real-time link quality score is higher than that of the primary transmission path for a certain period of time, then the backup path with the highest real-time link quality score will be switched to the primary transmission path.

3. The cross-domain information distribution method for multi-link collaborative networking as described in claim 1, characterized in that, The step of performing fragmentation and encoding processing on the data to be distributed based on the link quality of the main transmission path to obtain multiple data packets to be distributed includes: Determine the packet loss rate of the main transmission path. If the packet loss rate is lower than a first threshold, then use an adaptive side-length fragmentation method to fragment the data to be distributed. If the link packet loss rate is not lower than the first threshold and is lower than the second threshold, the data to be distributed is fragmented and then interleaved and rearranged, and then each rearranged data fragment is encoded based on Reed-Solomon erasure coding. If the packet loss rate is not lower than the second threshold, then the data to be distributed is fragmented and then each data fragment is encoded based on the RaptorQ fountain code.

4. The cross-domain information distribution method for multi-link collaborative networking as described in claim 1, characterized in that, The step of transmitting the data packet to be distributed to the information receiving end through the main transmission path and the backup path includes: After the data packets to be distributed are split according to the link quality prediction results of the main transmission path and the backup path, they are transmitted through different transmission paths. Determine the priority of the data packets to be distributed; The core data packets with high priority are copied, and all the core data packets are sent in parallel to the information receiving end through the main transmission path and the backup transmission path.

5. The cross-domain information distribution method as described in claim 1, characterized in that, The method, applied at the information receiving end, includes: The data packets are sorted according to their sequence numbers. Based on the encoding and fragmentation methods of the data packets, the data packets are decoded and reassembled to obtain complete data. Perform an end-to-end integrity check on the complete data.

6. A cross-domain information distribution system for multi-link collaborative networking, characterized in that, The system includes: The transmission path determination module is used to dynamically select the main transmission path and at least one backup path for cross-domain information from all the data transmission links based on the computing power level of the information receiving end and the link quality prediction results of each data transmission link. The data processing module is used to perform fragmentation and encoding processing on the data to be distributed based on the link quality of the main transmission path to obtain multiple data packets to be distributed; wherein the encoding method includes one of no encoding, erasure coding, and fountain coding; The data sending module is used to transmit the data packet to be distributed to the information receiving end through the main transmission path and the backup path, so that the information receiving end can decode and reassemble the data packet to be distributed; The data receiving module is used to sort data packets according to sequence number identifiers, and perform data packet decoding and reassembly processing based on the data packet encoding and fragmentation methods to obtain complete data. The integrity verification module is used to perform end-to-end integrity verification on the complete data; The transmission path determination module is also used for: The computing power level of the information receiving end is determined based on its hardware performance indicators and actual decoding capabilities. For each data transmission link, a two-state Markov chain model is used to model the link state, and the state transition probability and packet loss rate of each data transmission link state are statistically analyzed; wherein, the link state includes good state and deteriorated state. Based on the state transition probability and the packet loss rate, the link packet loss rate within the prediction time window is determined; wherein, the length of the prediction time window is negatively correlated with the state transition probability; Based on the real-time quality parameters and predicted packet loss rate of the data transmission link, a link quality evaluation function is constructed to determine the real-time link quality score; wherein, the weight of each parameter of the link quality evaluation function is determined based on the computing power level of the information receiving end; Based on the real-time link quality score, the primary transmission path and at least one backup path for the cross-domain information are dynamically selected.

7. The cross-domain information distribution system for multi-link collaborative networking as described in claim 6, characterized in that, If the link quality score of the backup path with the highest real-time link quality score is higher than that of the primary transmission path for a certain period of time, then the backup path will be switched to the primary transmission path.

8. The cross-domain information distribution system for multi-link collaborative networking as described in claim 7, characterized in that, The data processing module is also used for: Determine the packet loss rate of the main transmission path. If the packet loss rate is lower than a first threshold, then use an adaptive side-length fragmentation method to fragment the data to be distributed. If the link packet loss rate is not lower than the first threshold and is lower than the second threshold, the data to be distributed is fragmented and then interleaved and rearranged, and then each rearranged data fragment is encoded based on Reed-Solomon erasure coding. If the link packet loss rate is not lower than the second threshold, then the data to be distributed is fragmented, and each data fragment is encoded based on the RaptorQ fountain code.

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