Intelligent terminal data interaction optimization method and system based on link state awareness

Abstract

This invention discloses a method and system for optimizing data interaction between intelligent terminals based on link state awareness, relating to the field of wireless communication data transmission technology. The method includes: constructing a directed acyclic graph topology; performing cooperative topology state discovery to generate a real-time link state communication topology; performing hierarchical packetization for transmission quality constraints; performing random linear network coding to obtain multiple linearly independent coded packets; performing distributed congestion-aware scheduling decisions to obtain multiple primary transmission links; performing differential coding and obfuscation transformation to obtain multiple obfuscated coded packets; and concurrently transmitting multiple obfuscated coded packets to a second terminal for Gaussian elimination decoding and reception. This invention solves the technical problems of weak topology adaptability, unreasonable congestion scheduling, and insufficient security protection in existing technologies, achieving efficient and secure data interaction between terminals and improving the real-time performance and transmission security of local area network data transmission.

Description

Technical Field

[0001] This invention relates to the field of wireless communication data transmission technology, and more specifically to a method and system for optimizing data interaction between smart terminals based on link state awareness. Background Technology

[0002] Data interaction between terminals often uses a fixed link transmission mode, lacking dynamic awareness of the real-time status of network links and making it difficult to flexibly recruit suitable relay nodes to build a reliable transmission topology. At the same time, data is not processed in a graded manner according to the service quality requirements of the business, and transmission scheduling is prone to congestion problems. Moreover, conventional transmission methods lack targeted security protection measures, making data vulnerable to eavesdropping and tampering. There are defects such as poor adaptability of data transmission topology between terminals, low transmission efficiency, and insufficient security, which cannot meet the needs of efficient, stable and secure data interaction between terminals in a local area network.

[0003] Existing technologies suffer from technical problems such as weak topology adaptability of data transmission between terminals, unreasonable congestion scheduling, and insufficient security protection. Summary of the Invention

[0004] This application provides a method and system for optimizing data interaction between smart terminals based on link state awareness, which is used to address the technical problems of weak topology adaptability of data transmission between terminals, unreasonable congestion scheduling, and insufficient security protection in the prior art.

[0005] In view of the above problems, this application provides a method and system for optimizing data interaction of smart terminals based on link state awareness.

[0006] The first aspect of this application provides a method for optimizing data interaction between smart terminals based on link state awareness, the method comprising:

[0007] When the first terminal initiates data interaction with the second terminal, the first terminal generates a structured task descriptor based on data transmission requirements, recruits relay nodes in the local area network to construct a directed acyclic graph topology, initiates a cooperative awareness protocol for K candidate relay nodes in the directed acyclic graph topology, performs cooperative topology state discovery to generate a real-time link state communication topology, performs hierarchical packaging of the data to be transmitted with transmission quality constraints to obtain multiple transmission priority data block sequences, performs random linear network coding on the multiple transmission priority data block sequences to obtain multiple linearly independent coded packets, which serve as path scheduling constraints, and performs distributed congestion-aware scheduling decisions on the real-time link state communication topology to obtain multiple primary transmission links, performs differential coding and obfuscation transformation on the multiple linearly independent coded packets based on transmission security policies to obtain multiple obfuscated coded packets, and concurrently transmits the multiple obfuscated coded packets to the second terminal through the multiple primary transmission links for Gaussian elimination decoding and reception.

[0008] A second aspect of this application provides a data interaction optimization system for intelligent terminals based on link state awareness, the system comprising: The system includes a Directed Acyclic Graph (DAG) topology construction module, used when a first terminal initiates data interaction with a second terminal, whereby the first terminal generates a structured task descriptor based on data transmission requirements and recruits relay nodes in the local area network to construct the DAG topology; a communication topology generation module, used to initiate a cooperative awareness protocol among K candidate relay nodes in the DAG topology, perform cooperative topology state discovery, and generate a real-time link state communication topology; a data block sequence acquisition module, used to hierarchically package the data to be transmitted according to transmission quality constraints, obtaining multiple transmission priority data block sequences; a primary transmission link generation module, used to perform random linear network coding on the multiple transmission priority data block sequences, obtaining multiple linearly independent coded packets, which serve as path scheduling constraints, and perform distributed congestion-aware scheduling decisions on the real-time link state communication topology to obtain multiple primary transmission links; an obfuscated coded packet acquisition module, used to perform differential coding obfuscation transformation on the multiple linearly independent coded packets based on transmission security policies, obtaining multiple obfuscated coded packets; and a restoration and reception module, used to concurrently transmit the multiple obfuscated coded packets to the second terminal through the multiple primary transmission links for Gaussian elimination decoding and restoration reception.

[0009] One or more technical solutions provided in this application have at least the following technical effects or advantages: When the first terminal initiates data interaction with the second terminal, a structured task descriptor is generated, and relay nodes are recruited in the local area network to construct a directed acyclic graph (DAG) topology. A cooperative awareness protocol is initiated for K candidate relay nodes in the DAG topology to perform cooperative topology state discovery, generating a real-time link state communication topology. Hierarchical packetization based on transmission quality constraints is performed to obtain multiple transmission priority data block sequences. Random linear network coding is performed to obtain multiple linearly independent coded packets, which serve as path scheduling constraints for distributed congestion-aware scheduling decisions, resulting in multiple primary transmission links. Differential coding and obfuscation transformation is applied to the multiple linearly independent coded packets to obtain multiple obfuscated coded packets. These obfuscated coded packets are concurrently transmitted to the second terminal via the multiple primary transmission links for Gaussian elimination decoding and reception. This achieves efficient and secure data interaction between terminals, improving the real-time performance and transmission security of local area network data transmission. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0011] Figure 1 A schematic diagram of the data interaction optimization method for smart terminals based on link state awareness provided in this application embodiment; Figure 2 This is a schematic diagram of the structure of a smart terminal data interaction optimization system based on link state awareness, provided in an embodiment of this application.

[0012] Figure labeling: Directed acyclic graph topology construction module 10, communication topology generation module 20, data block sequence acquisition module 30, primary transmission link generation module 40, obfuscated encoded packet acquisition module 50, and restoration receiving module 60. Detailed Implementation

[0013] This application provides a method and system for optimizing data interaction between smart terminals based on link state awareness, which addresses the technical problems of weak topology adaptability, unreasonable congestion scheduling, and insufficient security protection in existing technologies.

[0014] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0015] Example 1, as Figure 1 As shown, this application provides a method for optimizing data interaction between smart terminals based on link state awareness, the method comprising: Step S100: When the first terminal initiates data interaction with the second terminal, the first terminal generates a structured task descriptor according to the data transmission requirements and recruits relay nodes in the local area network to construct a directed acyclic graph topology.

[0016] Specifically, when the first terminal initiates data interaction with the second terminal, the first terminal assembles and generates a structured task descriptor containing task incentive budget, basic network coding parameters, security policy identifier, and effective time window based on the data transmission characteristics, service quality requirements, and privacy level in the data transmission requirements. It then broadcasts a preset node hop limit within the local area network based on a preset service discovery protocol to recruit potential relay nodes. The first terminal receives node state vectors containing node identifiers, available resource vectors, and link quality matrices from each responding node. Based on the data interaction objectives and node state vectors, it performs multi-objective optimization evaluation to select K candidate relay nodes. Finally, with the first terminal as the origin, the second terminal as the terminal, and the K candidate relay nodes as the intermediate forwarding layer, a directed acyclic graph topology is constructed.

[0017] Step S200: Initiate the cooperative sensing protocol of K candidate relay nodes in the directed acyclic graph topology, perform cooperative topology state discovery, and generate real-time link state communication topology.

[0018] Specifically, a cooperative sensing protocol for K candidate relay nodes in a directed acyclic graph topology is initiated. The first terminal broadcasts a cooperative sensing initiation command to the K candidate relay nodes, driving each candidate relay node to send probe data packets to neighboring nodes within its one-hop communication radius. It also retrieves K sets of response probe data packets containing source node identifiers, target node identifiers, and preliminary link measurement parameters. Based on this response data, the link state quantization of neighboring relay nodes is completed, and K sets of link quality parameters are obtained. In the directed acyclic graph topology, valid connection relationships are determined by traversing according to a preset link quality threshold, cooperative topology state discovery is performed, and finally, a real-time link state communication topology is generated.

[0019] Step S300: Perform hierarchical packaging of the data to be transmitted according to transmission quality constraints to obtain multiple transmission priority data block sequences.

[0020] Specifically, the data to be transmitted is parsed and sliced ​​to generate multiple basic data units with global sequence identifiers and priority type labels. Based on the priority type labels, the basic data units are classified and merged to form homogeneous data unit sets. Then, the data within each set is reorganized in an orderly manner according to the global sequence identifier. Under the constraints of transmission quality, hierarchical packaging is completed, and finally, multiple transmission priority data block sequences are obtained.

[0021] Step S400: Perform random linear network coding on the multiple transmission priority data block sequences to obtain multiple linearly independent coded packets, which serve as path scheduling constraints. Perform distributed congestion-aware scheduling decisions on the real-time link state communication topology to obtain multiple primary transmission links.

[0022] Specifically, multiple transmission priority data block sequences are randomly linearly network encoded to generate multiple linearly independent encoded packets. Based on the linear independence of the encoded packets, the minimum number of valid encoded packets required for the second terminal to decode is determined, and path scheduling constraints are constructed accordingly. In the real-time link state communication topology, distributed congestion-aware scheduling decisions are executed based on the real-time link state and path scheduling constraints to obtain multiple sets of path allocation schemes. Multi-objective comprehensive utility evaluation is carried out on multiple sets of schemes, and the primary transmission links are located in descending order. At the same time, backup relay links are screened in combination with fault domain isolation, and finally multiple primary transmission links that meet the transmission requirements are obtained.

[0023] Step S500: Based on the transmission security policy, perform differential coding and obfuscation transformation on the multiple linearly independent coded packets to obtain multiple obfuscated coded packets.

[0024] Specifically, according to the preset transmission security strategy, differentiated encoding and obfuscation transformation is performed on the multiple linearly independent encoded packets that have been generated. Security enhancement transformation is performed on different encoded packets through independent obfuscation rules, so that the encoded data has the security characteristics of anti-interception and anti-tampering during transmission, and finally multiple obfuscated encoded packets that can be used for multi-link concurrent transmission are generated.

[0025] Step S600: The multiple obfuscated encoded packets are concurrently transmitted to the second terminal through the multiple primary transmission links for Gaussian elimination decoding and restoration reception.

[0026] Specifically, multiple primary transmission links are used to transmit multiple obfuscated packets concurrently, so that the data is sent to the second terminal efficiently and stably. After receiving all the obfuscated packets, the second terminal uses Gaussian elimination to decode the packets and restore the data, and finally recovers the original data to be transmitted and completes the reception.

[0027] In one possible implementation, step S400 further includes: Step S410: Perform random linear network coding on the first transmission priority data block sequence to construct the first linearly independent coded packet.

[0028] Step S420: Based on the linear independence characteristics of the first linearly independent encoded packet, determine the minimum number of valid encoded packets required for the second terminal to perform decoding, and construct path scheduling constraints based on the minimum number of valid encoded packets.

[0029] Step S430: In the real-time link state communication topology, a distributed congestion-aware scheduling decision is made based on the real-time link state and the path scheduling constraints to obtain P path allocation schemes.

[0030] Step S440: Perform a multi-objective comprehensive utility evaluation on the P path allocation schemes to locate the first primary transmission link in descending order.

[0031] Specifically, random linear network coding is performed on the first transmission priority data block sequence. By randomly selecting coding coefficients within a finite field, multiple basic data units within the sequence are linearly combined to generate a first linearly independent coding packet that satisfies the rank constraint and is linearly independent of each other, ensuring that the receiving end can restore the original data through a sufficient number of coding packets.

[0032] Based on the linear independence characteristic of the first linearly independent encoded packet, the total number of original data slices M is taken as the target rank. According to the random linear network coding full-rank decoding algorithm, the minimum number of effective encoded packets N required for the second terminal to achieve Gaussian elimination decoding is determined as N=M. With N as a mandatory constraint, a path scheduling constraint is constructed, requiring that the set of links selected by the distributed scheduling can guarantee that the number of successfully transmitted linearly independent encoded packets is not less than N. This serves as the basis for path allocation and scheduling decisions.

[0033] In the real-time link state communication topology, the link bandwidth, latency, packet loss rate, congestion level, and remaining forwarding capacity locally perceived by each candidate relay node are used as the real-time link state input. The minimum number of valid encoded packets is a hard constraint that must be met. A distributed congestion-aware scheduling mechanism is adopted, in which each relay node autonomously judges the link congestion status and feeds back the available link information to the upstream. The first terminal combines the global link status and the constraints to perform distributed path calculation, and filters the links with no congestion and high reliability hop by hop, and finally generates P path allocation schemes that meet the transmission guarantee requirements.

[0034] A random forest machine learning algorithm is used to perform multi-objective comprehensive utility evaluation on P path allocation schemes. First, path delay, link bandwidth, packet loss rate, remaining energy, congestion level, and fault domain isolation are used as model input features. Historical transmission data is collected to construct a labeled training sample set to complete model training. The random forest model consists of multiple independent decision trees. During training, different training subsets are generated through bootstrapping. A decision tree is trained on each subset, and the generalization ability is optimized by randomly selecting feature subsets. In the inference phase, the feature vectors of the P path schemes are input into the trained model. The multiple decision trees output utility scores, which are then fused by voting to obtain the final comprehensive score. All path schemes are ranked in descending order of comprehensive score, and the scheme with the highest score is selected as the primary transmission link.

[0035] In one possible implementation, step S100 further includes: Step S110: The first terminal broadcasts the structured task descriptor on the local area network to initiate the recruitment of potential relay nodes and obtain multiple node state vectors of multiple response nodes.

[0036] Step S120: The first terminal performs multi-objective optimization evaluation of the multiple response nodes based on the data interaction target and the multiple node state vectors, and filters the K candidate relay nodes.

[0037] Step S130: Construct the directed acyclic graph topology with the first terminal as the origin, the second terminal as the terminal, and the K candidate relay nodes as the intermediate forwarding layer.

[0038] Specifically, the first terminal broadcasts a structured task descriptor containing transmission task parameters, security constraints, and scheduling requirements within the local area network. After receiving the broadcast information, potential relay nodes in the vicinity collect their own remaining bandwidth, available computing power, remaining energy, link latency, packet loss rate, and other operating status parameters, quantify them into node state vectors, and send them back to the first terminal via single-hop response data packets. The first terminal receives and parses the response data packets, and completes the acquisition and storage of the node state vectors corresponding to multiple response nodes.

[0039] The first terminal performs multi-objective optimization evaluation based on data interaction objectives and multiple node state vectors to screen K candidate relay nodes. First, a multi-objective optimization evaluation function is constructed based on data interaction objectives including path redundancy, end-to-end latency, and total incentive cost, with minimum remaining energy of nodes and minimum link quality set as hard constraints. Then, based on these hard constraints, the available resource vectors and link quality matrices corresponding to the state vectors of each node are traversed to screen the feasible node set that meets the constraints. Next, multiple sets of candidate K node combinations are generated from the feasible node set, and the objective function value vectors corresponding to each combination are calculated through the multi-objective optimization evaluation function. Then, scalar aggregation calculation is performed on each objective function value vector to obtain a comprehensive evaluation value. After sorting the comprehensive evaluation values ​​in ascending order, the optimal K node combination is located, and K candidate relay nodes are extracted from it.

[0040] Using the first terminal as the origin node and the second terminal as the destination node, the selected K candidate relay nodes are used as intermediate forwarding layer nodes. Unidirectional directed connections are established based on the communication reachability between nodes, allowing data to be forwarded only from upstream nodes to downstream nodes. Connections with loops are eliminated. The node hierarchy is divided and directional links are built in sequence to construct a directed acyclic graph topology with no closed loop structure and a unique data transmission direction.

[0041] In one possible implementation, step S120 further includes: Step S121: Construct a multi-objective optimization evaluation function based on the data interaction objective, wherein the data interaction objective includes at least path redundancy, end-to-end latency and total incentive cost, and the multi-objective optimization evaluation function takes the minimum remaining energy of the node and the minimum quality of the link as hard constraints.

[0042] Step S122: Based on the hard constraints, traverse the available resource vectors and link quality matrices of the multiple node state vectors to filter the feasible node set.

[0043] Step S123: Enumerate multiple candidate K-node combinations in the feasible node set, evaluate them using the multi-objective optimization evaluation function, and obtain multiple objective function value vectors.

[0044] Step S124: Perform scalar aggregation calculation on the multiple objective function value vectors to obtain multiple comprehensive evaluation values, then sort them in ascending order to locate the optimal K node combination, so as to extract the K candidate relay nodes.

[0045] Specifically, a multi-objective optimization evaluation function is constructed with path redundancy, end-to-end latency, and total incentive cost as the core data interaction objectives. At the same time, a minimum remaining energy threshold for nodes and a minimum quality threshold for links are set as hard constraints. During the evaluation process, nodes that do not meet the constraints are eliminated first, so that the multi-objective optimization evaluation function can take into account multiple transmission performance indicators while ensuring the basic availability of node resources and link communication quality.

[0046] Based on the two pre-set hard constraints of minimum remaining energy of nodes and minimum link quality, the available resource vectors and link quality matrices corresponding to the state vectors of all responding nodes are traversed one by one. Threshold verification is performed on the remaining energy and corresponding link quality parameters of each node. Unqualified nodes whose parameters do not meet the constraint thresholds are eliminated. The remaining nodes that meet all constraints constitute the feasible node set.

[0047] In the selected feasible node set, multiple candidate node combinations consisting of K nodes are generated by combination enumeration. Each candidate K node combination is substituted into the pre-constructed multi-objective optimization evaluation function to calculate the path redundancy, end-to-end delay, and total incentive cost index values ​​of the corresponding combination, forming the objective function value vector corresponding to each candidate combination.

[0048] The objective function value vector consisting of path redundancy, end-to-end delay, and total incentive cost for each candidate K-node combination is normalized to eliminate differences in the dimensions of each indicator, and then a linear weighted scalar aggregation formula is used. Calculate the comprehensive evaluation value, where U is the comprehensive evaluation value. The preset weights for path redundancy, end-to-end latency, and total incentive cost are respectively, and the sum of the weights is 1. R, T, and C are the normalized index values. Based on the principle that the smaller the comprehensive evaluation value, the better the performance of the node combination, the comprehensive evaluation values ​​of all candidate combinations are sorted in ascending order. The optimal K node combination with the first-ranked value is selected, and finally K candidate relay nodes are extracted from this combination.

[0049] In one possible implementation, step S110 further includes: Step S111: Assemble the structured task descriptor according to the data transmission characteristics, quality of service requirements and privacy level in the data transmission requirements. The structured task descriptor is also configured with task incentive budget, network coding basic parameters, security policy identifier and effective time window.

[0050] Step S112: After broadcasting the structured task descriptor with a preset node hop limit in the local area network based on the preset service discovery protocol, the potential relay nodes in the local area network make resource decision responses based on the task descriptor and their own states, so that the first terminal receives multiple node state vectors of the multiple response nodes, wherein the node state vectors include node identifiers, available resource vectors, and link quality matrices.

[0051] Specifically, the first terminal assembles and constructs a structured task descriptor based on predetermined data transmission requirements, combined with the inherent attributes of the transmitted data (such as the type, size, and frequency of transmission), service quality requirements (such as transmission latency, packet loss rate, and transmission bandwidth), and privacy level (such as the security protection level corresponding to the data sensitivity). Simultaneously, this structured task descriptor is configured with a task incentive budget (the upper limit of resource costs used to incentivize relay nodes to participate in data forwarding), basic network coding parameters (such as data coding method, coding block length, and redundancy coefficient), security policy identifiers (such as encryption and authentication security execution policy numbers corresponding to the data privacy level), and an effective time window (the start and end time range allowed for this transmission task). This forms a standardized structured task descriptor with complete constraint information and task attributes.

[0052] The first terminal broadcasts a structured task descriptor within the local area network based on a pre-agreed service discovery protocol. During the broadcast, a preset node hop limit is set to restrict the maximum node level at which the broadcast data packet can be forwarded, preventing excessive diffusion of task information. After receiving the broadcast information, potential relay nodes within the local area network combine the task constraints in the structured task descriptor with their own real-time operating status to make resource matching decisions, determining whether they have the capability to participate in data forwarding. If the conditions are met, they generate response data packets. The first terminal receives the response data packets from each potential relay node and parses them to obtain multiple node state vectors. Among these, the node identifier is an identity code used to uniquely distinguish different relay nodes, the available resource vector is a set of quantified parameters representing the node's remaining computing power, remaining bandwidth, remaining energy, and other schedulable resources, and the link quality matrix is ​​a two-dimensional matrix data representing the link communication quality between the node and surrounding communication nodes, such as latency, packet loss rate, and signal-to-noise ratio.

[0053] In one possible implementation, step S200 further includes: Step S210: The first terminal broadcasts a cooperative sensing start command to the K candidate relay nodes to drive the K candidate relay nodes to send probe data packets to neighbor nodes within a one-hop communication radius to retrieve K sets of response probe data packets, wherein the response probe data packets include source node identifier, target node identifier and corresponding preliminary link measurement parameters.

[0054] Step S220: Based on the K sets of response probe data packets, perform link state quantization of the neighboring relay nodes to obtain K sets of link quality parameters.

[0055] Step S230: In the directed acyclic graph topology, based on a preset link quality threshold, traverse the K sets of link quality parameters, determine the effective connection relationship between the K candidate relay nodes, and generate the real-time link status communication topology.

[0056] Specifically, the first terminal broadcasts a collaborative sensing start command to the selected K candidate relay nodes, triggering each candidate relay node to initiate a link probing process, causing it to send probe data packets to neighboring nodes within its one-hop communication radius coverage area. After receiving the probe data packets, the neighboring nodes send back corresponding response probe data packets. The first terminal receives and aggregates these responses to obtain K sets of response probe data packets. The response probe data packets contain source node identifiers for identifying the sending node, target node identifiers for the receiving node, and preliminary link measurement parameters characterizing the real-time transmission performance of the link.

[0057] The first terminal extracts preliminary link measurement parameters from the K sets of response probe data packets, and performs standardized quantification on indicators such as link latency, packet loss rate, signal strength, and transmission bandwidth between each candidate relay node and its neighboring nodes. It eliminates the differences in the dimensions of each indicator through normalization operations, and combines preset weighting coefficients to perform fusion calculations on multi-dimensional indicators, thereby completing the comprehensive quantification of the link status of neighboring relay nodes, and finally outputs the K sets of link quality parameters corresponding to each candidate relay node.

[0058] Within the previously constructed directed acyclic graph topology framework, using a pre-defined link quality threshold as the criterion, K sets of link quality parameters are traversed one by one. The actual link quality between each candidate relay node is compared with the threshold value. Valid communication connections with link quality higher than the threshold are retained, while invalid connections with link quality that do not meet the transmission requirements are eliminated. In this way, the effective connection relationship between K candidate relay nodes is screened and determined, and finally, a real-time link status communication topology adapted to the current real-time transmission conditions of the network is generated.

[0059] In one possible implementation, step S300 further includes: Step S310: Parse and slice the data to be transmitted to obtain multiple basic data units, wherein each basic data unit is attached with a global sequence identifier and a priority type label, and the priority type label is used to indicate the quality of service requirements.

[0060] Step S320: Classify and merge the multiple basic data units according to the priority type label to obtain multiple sets of homogeneous data units, and then reassemble them in order within the set according to the global sequence identifier to obtain the multiple transmission priority data block sequences.

[0061] Specifically, the data to be transmitted is parsed to identify the data header fields, data length and business type. Then, the original data stream is continuously segmented and sliced ​​according to a preset fixed byte length, and the complete data to be transmitted is evenly divided into multiple basic data units. At the same time, a global sequence identifier is assigned to each basic data unit to ensure that the transmission order is traceable. In addition, a priority type label is configured for each data unit according to the business scenario, so as to indicate the service quality requirements such as latency, bandwidth and reliability required by the data unit.

[0062] Using priority type labels as classification indexes, all basic data units are traversed, and basic data units with the same label value are grouped into the same group to complete the classification and merging of data with different priorities, forming multiple homogeneous data unit sets. Then, within each homogeneous data unit set, the data is sorted and reorganized in ascending order according to the value of the global sequence identifier, and finally, multiple transmission priority data block sequences corresponding to different service quality levels are generated.

[0063] In one possible implementation, step S400 further includes: Step S450: Using the first primary transmission link as the fault domain analysis benchmark, perform fault domain isolation analysis on P-1 path allocation schemes to obtain P-1 fault domain isolation degrees.

[0064] Step S460: Based on the preset fault domain isolation threshold, traverse the P-1 fault domain isolation degrees to select multiple first backup relay links from the P-1 path allocation schemes.

[0065] Specifically, a baseline fault domain is constructed using the set of relay nodes and communication links occupied by the primary transmission link. The relay nodes and communication links included in each of the P-1 path allocation schemes are extracted one by one. The number of overlapping nodes and links between each alternative path and the primary link are counted. First, the node overlap degree and link overlap degree are calculated. Then, the isolation degree value is obtained by reverse calculation using the fault domain isolation degree = 1 - (node ​​overlap degree × weight + link overlap degree × weight). The more overlapping nodes and links, the higher the overlap degree and the lower the corresponding fault domain isolation degree. This quantifies the fault coupling degree between each alternative path and the primary link. Finally, the P-1 fault domain isolation degrees corresponding to the P-1 path allocation schemes are output.

[0066] The pre-set fault domain isolation threshold is used as the screening criterion. The fault domain isolation degree corresponding to P-1 path allocation schemes is traversed in turn. The isolation degree value of each scheme is compared with the threshold. The path allocation schemes with fault domain isolation degree greater than or equal to the preset threshold are selected. Then, according to the priority order of isolation degree from high to low, multiple schemes that meet the conditions are selected and identified as multiple first backup relay links to ensure that the backup link and the primary link have sufficient fault isolation capability.

[0067] In one possible implementation, step S460 further includes: Step S461: During the concurrent transmission of the first obfuscated coded packet to the second terminal through the first primary transmission link, monitor the real-time performance indicators of the first primary transmission link.

[0068] Step S462: When the real-time performance index of the first primary transmission link is lower than the preset transmission performance constraint, based on the fault domain isolation degree and real-time link quality, adaptive switching of backup path transmission is performed on the plurality of first backup relay links.

[0069] Specifically, during the concurrent transmission of the first obfuscated coded packet to the second terminal via the first primary transmission link, performance acquisition modules deployed at both ends of the link and at relay nodes along the route periodically collect real-time performance indicators such as transmission latency, packet loss rate, effective transmission bandwidth, jitter value, and signal-to-noise ratio of the first primary transmission link. The timestamps of packet transmission and reception and traffic statistics are recorded synchronously. Through local real-time comparison and continuous sampling monitoring, the transmission status of the first primary transmission link is dynamically monitored throughout the entire process.

[0070] When the real-time latency, packet loss rate, effective bandwidth, and other performance indicators of the primary transmission link are lower than the preset transmission performance constraint threshold, a weighted scoring algorithm is used to comprehensively calculate the fault domain isolation and real-time link quality of multiple primary backup relay links. Based on the comprehensive score, the links are sorted from high to low, and the optimal backup link is prioritized for scheduling. Link switching signaling is triggered to complete the seamless adaptive switching of the primary and backup links. The transmission task of the obfuscated coded packet is then completed through the selected primary backup relay link.

[0071] Example 2 is based on the same inventive concept as the link-state-aware intelligent terminal data interaction optimization method in the previous examples, such as... Figure 2 As shown, this application provides a smart terminal data interaction optimization system based on link state awareness. The system and method embodiments in this application are based on the same inventive concept. The system includes: The directed acyclic graph topology construction module 10 is used to generate a structured task descriptor based on data transmission requirements when the first terminal initiates data interaction with the second terminal, and recruit relay nodes in the local area network to construct a directed acyclic graph topology.

[0072] The communication topology generation module 20 is used to initiate the cooperative sensing protocol of K candidate relay nodes in the directed acyclic graph topology, perform cooperative topology state discovery, and generate real-time link state communication topology.

[0073] The data block sequence acquisition module 30 is used to perform hierarchical packaging of the data to be transmitted under transmission quality constraints to obtain multiple transmission priority data block sequences.

[0074] The primary transmission link generation module 40 is used to perform random linear network coding on the multiple transmission priority data block sequences to obtain multiple linearly independent coded packets, which serve as path scheduling constraints. In the real-time link state communication topology, distributed congestion-aware scheduling decisions are made to obtain multiple primary transmission links.

[0075] The obfuscated packet acquisition module 50 is used to perform differential encoding obfuscation transformation on the multiple linearly independent encoded packets based on the transmission security policy to obtain multiple obfuscated encoded packets.

[0076] The restoration receiving module 60 is used to concurrently transmit the multiple obfuscated encoded packets to the second terminal through the multiple primary transmission links for Gaussian elimination decoding and restoration reception.

[0077] Furthermore, the system is also used to implement the following functions: Random linear network coding is performed on the first transmission priority data block sequence to construct a first linearly independent coded packet; based on the linear independence characteristic of the first linearly independent coded packet, the minimum number of valid coded packets required for the second terminal to perform decoding is determined, and path scheduling constraints are constructed based on the minimum number of valid coded packets; in the real-time link state communication topology, distributed congestion-aware scheduling decisions are made based on the real-time link state and the path scheduling constraints to obtain P path allocation schemes; multi-objective comprehensive utility evaluation is performed on the P path allocation schemes to locate the first primary transmission link in descending order.

[0078] Furthermore, the system is also used to implement the following functions: The first terminal broadcasts the structured task descriptor on the local area network to initiate the recruitment of potential relay nodes and obtain multiple node state vectors of multiple response nodes; the first terminal performs multi-objective optimization evaluation of the multiple response nodes based on the data interaction target and the multiple node state vectors, and filters the K candidate relay nodes; the directed acyclic graph topology is constructed with the first terminal as the origin, the second terminal as the terminal, and the K candidate relay nodes as the intermediate forwarding layer.

[0079] Furthermore, the system is also used to implement the following functions: A multi-objective optimization evaluation function is constructed based on the data interaction objectives, wherein the data interaction objectives include at least path redundancy, end-to-end latency, and total incentive cost, and the multi-objective optimization evaluation function uses the minimum remaining energy of nodes and the minimum link quality as hard constraints. Based on the hard constraints, the available resource vectors and link quality matrices of the multiple node state vectors are traversed to filter feasible node sets. Multiple candidate K-node combinations are enumerated in the feasible node set, and the multi-objective optimization evaluation function is used for evaluation to obtain multiple objective function value vectors. Scalar aggregation calculation is performed on the multiple objective function value vectors to obtain multiple comprehensive evaluation values, which are then sorted in ascending order to locate the optimal K-node combination, thereby parsing and extracting the K candidate relay nodes.

[0080] Furthermore, the system is also used to implement the following functions: Based on the data transmission characteristics, service quality requirements, and privacy level in the data transmission requirements, the structured task descriptor is assembled. The structured task descriptor is further configured with a task incentive budget, basic network coding parameters, security policy identifier, and effective time window. After the structured task descriptor with a preset node hop limit is broadcast in the local area network based on a preset service discovery protocol, potential relay nodes in the local area network respond with resource decisions based on the task descriptor and their own states. This enables the first terminal to receive multiple node state vectors from the multiple responding nodes, where each node state vector includes a node identifier, an available resource vector, and a link quality matrix.

[0081] Furthermore, the system is also used to implement the following functions: The first terminal broadcasts a cooperative sensing start command to the K candidate relay nodes to drive the K candidate relay nodes to send probe data packets to neighboring nodes within a one-hop communication radius, thereby retrieving K sets of response probe data packets. Each response probe data packet includes a source node identifier, a target node identifier, and corresponding preliminary link measurement parameters. Based on the K sets of response probe data packets, the link state of the neighboring relay nodes is quantized to obtain K sets of link quality parameters. In the directed acyclic graph topology, based on a preset link quality threshold, the K sets of link quality parameters are traversed to determine the effective connection relationships between the K candidate relay nodes, generating the real-time link state communication topology.

[0082] Furthermore, the system is also used to implement the following functions: The data to be transmitted is parsed and sliced ​​to obtain multiple basic data units, wherein each basic data unit is attached with a global sequence identifier and a priority type label, and the priority type label is used to indicate the quality of service requirements; the multiple basic data units are classified and merged according to the priority type label to obtain multiple sets of homogeneous data units, and then the sets are reassembled in order according to the global sequence identifier to obtain the multiple transmission priority data block sequences.

[0083] Furthermore, the system is also used to implement the following functions: Using the first primary transmission link as the fault domain analysis benchmark, fault domain isolation degree analysis is performed on P-1 path allocation schemes to obtain P-1 fault domain isolation degrees; based on the preset fault domain isolation threshold, the P-1 fault domain isolation degrees are traversed to select multiple first backup relay links from the P-1 path allocation schemes.

[0084] Furthermore, the system is also used to implement the following functions: During the concurrent transmission of the first obfuscated coded packet to the second terminal via the first primary transmission link, the real-time performance indicators of the first primary transmission link are monitored; when the real-time performance indicators of the first primary transmission link are lower than the preset transmission performance constraints, based on the fault domain isolation degree and real-time link quality, adaptive switching of backup path transmission is performed on the multiple first backup relay links.

[0085] It should be noted that the order of the embodiments described above is for descriptive purposes only and does not represent the superiority or inferiority of the embodiments. Specific embodiments of this specification have been described above. Furthermore, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0086] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0087] This specification and accompanying drawings are merely illustrative examples of this application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Therefore, if such modifications and variations fall within the scope of this application and its equivalents, this application intends to include such modifications and variations.

Claims

1. A method for optimizing data interaction between intelligent terminals based on link state awareness, characterized in that, The method includes: When the first terminal initiates data interaction with the second terminal, the first terminal generates a structured task descriptor based on data transmission requirements and recruits relay nodes in the local area network to construct a directed acyclic graph topology. Initiate the cooperative awareness protocol of K candidate relay nodes in the directed acyclic graph topology, perform cooperative topology state discovery, and generate real-time link state communication topology. The data to be transmitted is hierarchically packaged according to transmission quality constraints to obtain multiple transmission priority data block sequences; Random linear network coding is performed on the multiple transmission priority data block sequences to obtain multiple linearly independent coded packets, which serve as path scheduling constraints. Distributed congestion-aware scheduling decisions are then made on the real-time link state communication topology to obtain multiple primary transmission links. Based on the transmission security strategy, the multiple linearly independent coded packets are subjected to differential coding and obfuscation transformation to obtain multiple obfuscated coded packets; The multiple obfuscated encoded packets are transmitted concurrently to the second terminal via the multiple primary transmission links for Gaussian elimination decoding and reception.

2. The intelligent terminal data interaction optimization method based on link state awareness as described in claim 1, characterized in that, Random linear network coding is performed on the multiple transmission priority data block sequences to obtain multiple linearly independent coded packets, which serve as path scheduling constraints. Distributed congestion-aware scheduling decisions are then performed on the real-time link state communication topology to obtain multiple primary transmission links. The method includes: Random linear network coding is performed on the first transmission priority data block sequence to construct the first linearly independent coded packet; Based on the linear independence characteristics of the first linearly independent encoded packet, the minimum number of valid encoded packets required for the second terminal to perform decoding is determined, and path scheduling constraints are constructed based on the minimum number of valid encoded packets. In the real-time link state communication topology, distributed congestion-aware scheduling decisions are made based on the real-time link state and the path scheduling constraints to obtain P path allocation schemes. A multi-objective comprehensive utility evaluation is performed on the P path allocation schemes to determine the first primary transmission link in descending order.

3. The intelligent terminal data interaction optimization method based on link state awareness as described in claim 1, characterized in that, The method further includes: The first terminal broadcasts the structured task descriptor on the local area network to initiate the recruitment of potential relay nodes and obtain multiple node state vectors of multiple response nodes. The first terminal performs multi-objective optimization evaluation of the multiple response nodes based on the data interaction target and the multiple node state vectors, and filters the K candidate relay nodes; The directed acyclic graph topology is constructed with the first terminal as the origin, the second terminal as the terminal, and the K candidate relay nodes as the intermediate forwarding layer.

4. The intelligent terminal data interaction optimization method based on link state awareness as described in claim 3, characterized in that, The first terminal performs multi-objective optimization evaluation of the multiple response nodes based on the data interaction objective and the state vectors of the multiple nodes, and filters the K candidate relay nodes. The method includes: A multi-objective optimization evaluation function is constructed based on the data interaction objective, wherein the data interaction objective includes at least path redundancy, end-to-end latency and total incentive cost, and the multi-objective optimization evaluation function takes the minimum remaining energy of the node and the minimum quality of the link as hard constraints. Based on the hard constraints, the available resource vectors and link quality matrices of the multiple node state vectors are traversed to filter the feasible node set; Multiple candidate K-node combinations are formed by enumerating the feasible node set, and the multi-objective optimization evaluation function is used for evaluation to obtain multiple objective function value vectors. After performing scalar aggregation calculations on the multiple objective function value vectors to obtain multiple comprehensive evaluation values, these values ​​are sorted in ascending order to locate the optimal K-node combination, thereby extracting the K candidate relay nodes.

5. The intelligent terminal data interaction optimization method based on link state awareness as described in claim 3, characterized in that, The first terminal broadcasts the structured task descriptor on the local area network to initiate recruitment of potential relay nodes and obtains multiple node state vectors of multiple responding nodes. The method includes: Based on the data transmission characteristics, quality of service requirements, and privacy level in the data transmission requirements, the structured task descriptor is assembled, wherein the structured task descriptor is further configured with a task incentive budget, basic network coding parameters, security policy identifier, and effective time window; After the structured task descriptor with a preset node hop limit is broadcast in the local area network based on the preset service discovery protocol, the potential relay nodes in the local area network make resource decision responses based on the task descriptor and their own states, so that the first terminal receives multiple node state vectors of the multiple response nodes, wherein the node state vector includes a node identifier, an available resource vector, and a link quality matrix.

6. The intelligent terminal data interaction optimization method based on link state awareness as described in claim 1, characterized in that, Initiating a cooperative awareness protocol for K candidate relay nodes in the directed acyclic graph topology, performing cooperative topology state discovery to generate a real-time link-state communication topology, the method includes: The first terminal broadcasts a cooperative sensing start command to the K candidate relay nodes to drive the K candidate relay nodes to send probe data packets to neighbor nodes within a one-hop communication radius, so as to retrieve K sets of response probe data packets. The response probe data packets include source node identifier, target node identifier and corresponding preliminary link measurement parameters. Based on the K sets of response probe data packets, the link status of the neighboring relay nodes is quantized to obtain K sets of link quality parameters. In the directed acyclic graph topology, the K sets of link quality parameters are traversed based on a preset link quality threshold to determine the effective connection relationship between the K candidate relay nodes, thereby generating the real-time link status communication topology.

7. The intelligent terminal data interaction optimization method based on link state awareness as described in claim 1, characterized in that, The method involves hierarchically packaging data to be transmitted according to transmission quality constraints to obtain multiple sequences of data blocks with transmission priorities. The data to be transmitted is parsed and sliced ​​to obtain multiple basic data units, wherein each basic data unit is attached with a global sequence identifier and a priority type label, and the priority type label is used to indicate the quality of service requirements; The multiple basic data units are classified and merged according to priority type labels to obtain multiple sets of homogeneous data units. Then, the sets are reassembled in order according to global sequence identifiers to obtain multiple transmission priority data block sequences.

8. The intelligent terminal data interaction optimization method based on link state awareness as described in claim 2, characterized in that, The method further includes: Using the first primary transmission link as the fault domain analysis benchmark, fault domain isolation degree analysis is performed on P-1 path allocation schemes to obtain P-1 fault domain isolation degrees. Based on a preset fault domain isolation threshold, the P-1 fault domain isolation degrees are traversed to select multiple first backup relay links from the P-1 path allocation schemes.

9. The intelligent terminal data interaction optimization method based on link state awareness as described in claim 8, characterized in that, Also includes: During the concurrent transmission of the first obfuscated coded packet to the second terminal via the first primary transmission link, the real-time performance indicators of the first primary transmission link are monitored. When the real-time performance index of the first primary transmission link is lower than the preset transmission performance constraint, an adaptive switching backup path transmission is performed on the plurality of first backup relay links based on the fault domain isolation degree and real-time link quality.

10. A smart terminal data interaction optimization system based on link state awareness, characterized in that, The system is used to implement the intelligent terminal data interaction optimization method based on link state awareness as described in any one of claims 1-9, and the system comprises: The directed acyclic graph topology construction module is used to generate a structured task descriptor based on data transmission requirements when the first terminal initiates data interaction with the second terminal, and recruit relay nodes in the local area network to construct a directed acyclic graph topology. The communication topology generation module is used to initiate the cooperative sensing protocol of K candidate relay nodes in the directed acyclic graph topology, perform cooperative topology state discovery, and generate real-time link state communication topology. The data block sequence acquisition module is used to perform hierarchical packaging of the data to be transmitted under transmission quality constraints, and obtain multiple transmission priority data block sequences. The primary transmission link generation module is used to perform random linear network coding on the multiple transmission priority data block sequences to obtain multiple linearly independent coded packets, which serve as path scheduling constraints. In the real-time link state communication topology, distributed congestion-aware scheduling decisions are made to obtain multiple primary transmission links. The obfuscated coded packet acquisition module is used to perform differential encoding obfuscation transformation on the multiple linearly independent coded packets based on the transmission security policy to obtain multiple obfuscated coded packets; The restoration receiving module is used to concurrently transmit the multiple obfuscated encoded packets to the second terminal through the multiple primary transmission links for Gaussian elimination decoding and restoration reception.

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