Blockchain-based methods, devices, and equipment for secure data sharing of electronic flight bags

Abstract

This application relates to the field of information technology and discloses a method, apparatus, and device for secure sharing of electronic flight bag data based on blockchain. The method includes: acquiring the aircraft's trajectory through its positioning and navigation systems; determining the communication link status based on environmental parameters; optimizing the data packet transmission timing using an adaptive algorithm based on the communication link status; determining the allocation weights of multi-channel data streams based on the transmission timing and the communication link status; processing the data packets through a blockchain consensus mechanism; allocating bandwidth resources using a weighted algorithm; dynamically adjusting the data stream distribution path based on environmental parameters; detecting the bit error rate level from the adjusted data stream; repairing the data stream using error correction coding; updating the synchronization rate of aircraft navigation and meteorological data based on the repaired data stream; and determining the completion status of real-time data synchronization based on the aircraft's load status and wind direction. This application improves the flight performance and safety of aircraft.

Description

Technical Field

[0001] This application relates to the field of information technology, and in particular to a method, apparatus and equipment for secure sharing of electronic flight bag data based on blockchain. Background Technology

[0002] Aircraft face significant challenges in real-time data synchronization during high-speed flight. The complex and ever-changing flight environment, with constantly shifting aircraft position, speed, and attitude, coupled with the influence of external factors such as wind speed and turbulence, severely disrupts the stability and reliability of communication links. Ensuring the real-time and accurate synchronization of critical data such as navigation and weather becomes a pressing technical challenge. Traditional data transmission methods struggle to adapt to highly dynamic flight environments, prone to data loss, delays, or errors, directly threatening flight safety. Furthermore, changes in aircraft load status also affect data transmission efficiency. Achieving efficient and reliable data synchronization in a complex and ever-changing flight environment, while balancing transmission efficiency with resource consumption, presents a systemic challenge involving multiple intertwined factors.

[0003] A blockchain-based approach to securely sharing electronic flight bag data offers an effective solution. The immutability and distributed nature of blockchain technology ensure the security and integrity of data during transmission, avoiding data loss, tampering, or delays that occur with traditional methods. Through blockchain technology, critical aircraft data, such as navigation and meteorological data, can be securely shared and synchronized across multiple nodes. Blockchain not only optimizes communication links but also enables smart contracts to automatically adjust data packet transmission timing, facilitate the coordinated use of multiple channels, and dynamically adjust transmission paths, ensuring efficient and reliable data transmission in complex environments.

[0004] Therefore, providing a blockchain-based method and system for secure sharing of electronic flight bag data to ensure efficient and reliable synchronization and sharing of flight data in complex and ever-changing flight environments is an urgent problem to be solved. Summary of the Invention

[0005] This application provides a blockchain-based method, system, and storage medium for secure sharing of electronic flight bag data, which can improve the flight performance and safety of aircraft.

[0006] Firstly, this application provides a blockchain-based method for securely sharing electronic flight bag data, the blockchain-based method for securely sharing electronic flight bag data includes:

[0007] The aircraft's trajectory is obtained through the aircraft's positioning and navigation systems, and the communication link status is determined by combining environmental parameters, including attitude angle data, wind speed components, and wind direction angle.

[0008] Based on the communication link status, an adaptive algorithm is used to optimize the data packet transmission timing. The allocation weight of the multi-channel data stream is determined based on the transmission timing and the communication link status, and the data packets are processed through a blockchain consensus mechanism.

[0009] Bandwidth resources are allocated using a weighted algorithm, and the data stream distribution path is dynamically adjusted in conjunction with the environmental parameters. The bit error rate level is then detected from the adjusted data stream.

[0010] Based on the bit error rate level, the data stream is repaired by error correction coding, and the synchronization rate of aircraft navigation and meteorological data is updated according to the repaired data stream.

[0011] The completion status of real-time data synchronization is determined based on the aircraft's load status and wind direction.

[0012] Furthermore, the process involves acquiring the aircraft's motion trajectory through the aircraft's positioning and navigation systems, and determining the communication link status by combining environmental parameters, including attitude angle data, wind speed components, and wind direction angles. This includes: acquiring the aircraft's position coordinates and flight velocity vector through the Global Positioning System and Inertial Navigation System, combining attitude angle data, wind speed components, and wind direction angles; calculating the aircraft's real-time motion trajectory in three-dimensional space to determine the aircraft's motion status; calculating the communication distance to the ground station based on the aircraft's position coordinates and flight velocity vector, and determining the signal propagation delay and bit error rate level by combining signal strength, noise interference, and turbulence intensity, thereby generating communication link status data.

[0013] Furthermore, the step of optimizing data packet transmission timing using an adaptive algorithm based on the communication link status, determining the allocation weights of multi-channel data streams based on the transmission timing and the communication link status, and processing data packets through a blockchain consensus mechanism includes: extracting the communication link status based on signal propagation delay and bit error rate levels; dynamically optimizing the data packet interval using an adaptive timing adjustment algorithm, and generating a stable transmission timing scheme by combining wind field gradient and timing jitter; forming a stable transmission timing scheme based on the optimized data packet interval and link delay; determining the priority of navigation data update rate and meteorological data synchronization rate based on the data packet interval and link delay in the stable transmission timing scheme, analyzing bandwidth utilization and congestion index, determining the allocation weights of each channel, and recording the allocation process using blockchain technology.

[0014] Furthermore, the step of allocating bandwidth resources through a weighted algorithm, dynamically adjusting the data stream distribution path in conjunction with the environmental parameters, and detecting the bit error rate level from the adjusted data stream includes: allocating bandwidth resources using a weighted round-robin algorithm based on the allocation weight of each channel; calculating the bandwidth allocation ratio of each channel based on the congestion index and wind shear coefficient to generate a bandwidth allocation scheme; dynamically adjusting the distribution of data traffic between the satellite link and the ground station based on the bandwidth allocation ratio of each channel; and determining the optimal path for data transmission based on the signal modulation method, frequency drift value, and temperature gradient.

[0015] Furthermore, the step of repairing the data stream through error correction coding based on the bit error rate level, and updating the synchronization rate of aircraft navigation and meteorological data according to the repaired data stream, includes: obtaining the congestion index and wind field gradient of the current link; if the congestion index exceeds a preset threshold, reducing the data packet transmission frequency; adjusting the data stream in combination with humidity distribution to optimize the transmission path and rate of data packets; if the bit error rate level of the adjusted data stream exceeds a preset threshold, reorganizing the data packets using forward error correction coding, and generating a repaired stable data stream in combination with air pressure changes and turbulence intensity.

[0016] Furthermore, determining the completion status of real-time data synchronization based on aircraft load status and wind direction angle includes: acquiring aircraft load status and wind direction angle, determining the priority of real-time data synchronization requirements; adjusting the data stream distribution path according to the priority to obtain an optimized transmission sequence; allocating bandwidth resources according to the transmission sequence, and determining whether the communication link status meets the synchronization requirements; if the link status meets the requirements, repairing the data stream through error correction coding and updating the navigation data synchronization rate.

[0017] Secondly, this application provides a blockchain-based electronic flight bag data security sharing device, which includes:

[0018] The trajectory and link analysis module is used to acquire the aircraft's motion trajectory through the aircraft's positioning and navigation systems, and determine the communication link status by combining environmental parameters, including: attitude angle data, wind speed components, and wind direction angle.

[0019] The transmission timing and traffic allocation module is used to optimize the data packet transmission timing using an adaptive algorithm based on the communication link status, determine the allocation weight of multi-channel data streams based on the transmission timing and the communication link status, and process data packets through a blockchain consensus mechanism.

[0020] The bandwidth allocation and path adjustment module is used to allocate bandwidth resources through a weighted algorithm, dynamically adjust the data stream distribution path in combination with the environmental parameters, and detect the bit error rate level from the adjusted data stream.

[0021] The data stream repair and synchronization module is used to repair the data stream through error correction coding based on the bit error rate level, and update the synchronization rate of aircraft navigation and meteorological data according to the repaired data stream;

[0022] The real-time synchronization status confirmation module is used to determine the completion status of real-time data synchronization based on the aircraft load status and wind direction angle.

[0023] A third aspect of this application provides a computer device in which the memory stores machine-readable instructions executable by the processor. When the computer device is running, the processor communicates with the memory via a bus, and when the machine-readable instructions are executed by the processor, the steps of the blockchain-based electronic flight bag data secure sharing method described above are performed.

[0024] The technical solutions provided by the embodiments of the present invention may include the following beneficial effects:

[0025] This invention discloses a blockchain-based real-time data synchronization method for aircraft. By acquiring the aircraft's trajectory and environmental parameters, the communication link status is determined. An adaptive algorithm optimizes the data packet transmission timing, and the weighting of multi-channel data streams is determined based on the transmission timing and link status. This method dynamically adjusts the data stream distribution path and determines the synchronization completion status by considering the aircraft's load status and wind direction. Simultaneously, based on blockchain technology, the security and transparency of data transmission are ensured, preventing data tampering and loss. This invention addresses the complex scenario of real-time data synchronization in high-speed aircraft flight environments, comprehensively considering the impact of aircraft position, speed, attitude, and environmental parameters such as wind speed and turbulence on the communication link. Through the immutable records, adaptive timing adjustments, multi-channel weighted allocation, and dynamic path selection provided by blockchain, data transmission optimization, error correction, and secure sharing are achieved. This method effectively improves the synchronization rate and reliability of navigation and meteorological data, providing crucial protection for safe aircraft flight. Attached Figure Description

[0026] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 This is a schematic diagram of one embodiment of the blockchain-based electronic flight bag data secure sharing method in this application.

[0028] Figure 2 This is a flowchart of link state analysis and data flow optimization in the embodiments of this application;

[0029] Figure 3 This is a schematic diagram of one embodiment of the blockchain-based electronic flight bag data security sharing device in this application.

[0030] Figure 4 This is a schematic block diagram of the structure of the blockchain-based electronic flight bag data security sharing device in this embodiment of the invention. Detailed Implementation

[0031] This application provides a blockchain-based method and system for secure data sharing of electronic flight bags. The terms "first," "second," "third," "fourth," etc. (if present) in the specification, claims, and accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. Furthermore, the terms "comprising" or "having" and any variations thereof are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0032] For ease of understanding, the specific process of the embodiments of this application is described below. Please refer to [link / reference]. Figure 1 One embodiment of the blockchain-based electronic flight bag data secure sharing method in this application includes:

[0033] Step S1: Obtain the aircraft's trajectory through the aircraft's positioning and navigation systems, and determine the communication link status by combining environmental parameters, including attitude angle data, wind speed components, and wind direction angle.

[0034] Specifically, the aircraft's trajectory is acquired through its positioning and navigation systems, and the communication link status is determined by combining this data with environmental parameters. The aircraft's trajectory includes position, speed, and attitude information, which reflects its flight status in real time and helps identify changes in the communication link. Environmental parameters such as wind speed, temperature, and humidity affect signal propagation and link stability; therefore, these factors must be considered to comprehensively assess the communication link status. By obtaining the aircraft's precise position through the positioning system and combining it with flight attitude data provided by the navigation system, its trajectory can be accurately calculated, providing a reliable foundation for subsequent data transmission and synchronization. Changes in environmental parameters, such as turbulence and wind speed, also have a significant impact on signal propagation, potentially causing signal attenuation or interruption. Therefore, by collecting environmental parameters, communication strategies can be adjusted in real time to cope with different flight conditions and external interference. Combining real-time flight data and external environmental data allows for the analysis and evaluation of the communication link quality, providing a basis for optimizing data transmission.

[0035] The process of determining the communication link status by integrating the aircraft's motion trajectory and environmental parameters allows for real-time monitoring of link changes and timely adjustments. Signal propagation is affected by various factors, including highly dynamic environmental changes during flight and complex meteorological factors. In this context, ensuring the stability and reliability of the communication link is crucial. By accurately acquiring real-time data on the aircraft's motion status and the surrounding environment, advanced algorithms can predict communication link status change trends, enabling rapid responses during communication and preventing data loss or delays due to link instability.

[0036] Step S2: Based on the communication link status, an adaptive algorithm is used to optimize the data packet transmission timing. The allocation weight of the multi-channel data stream is determined based on the transmission timing and the communication link status, and the data packets are processed through a blockchain consensus mechanism.

[0037] Specifically, an adaptive algorithm is employed to optimize data packet transmission timing. By analyzing link status and transmission timing in real time, the sending interval of data packets is adjusted to ensure the stability and efficiency of the data stream under different network conditions. The adaptive algorithm dynamically adjusts the transmission frequency and interval of data packets based on the real-time link status, thereby minimizing network congestion and signal interference and improving data transmission reliability. Based on transmission timing and link status, the algorithm intelligently evaluates and determines the priority of each data stream, thus rationally allocating bandwidth resources and achieving a balanced distribution of multi-channel data streams. During this process, a blockchain consensus mechanism processes the data packets, ensuring the immutability and transparency of each data packet's transmission process through decentralization, guaranteeing the security of data transmission. This approach not only optimizes data packet transmission efficiency but also enhances the system's resistance to data tampering while ensuring data integrity, thus ensuring the authenticity and reliability of the data.

[0038] Step S3: Allocate bandwidth resources through a weighted algorithm, dynamically adjust the data stream distribution path in combination with the environmental parameters, and detect the bit error rate level from the adjusted data stream.

[0039] Specifically, a weighted algorithm is used to allocate bandwidth resources. Based on the data flow requirements, link quality, and priority of each channel, the bandwidth allocation ratio is dynamically adjusted to ensure that high-priority data flows receive sufficient bandwidth support. The weighted algorithm considers various factors, such as link stability, bandwidth utilization, and environmental parameters like wind speed and air pressure changes, to adjust the bandwidth resource allocation strategy and avoid overloading or wasting resources on certain channels. Simultaneously, combined with environmental parameters, the algorithm can dynamically adjust the data flow distribution path to ensure data is transmitted through the optimal path, addressing the impact of potential link interference or environmental changes on transmission efficiency. After adjusting the data flow path, the system monitors the bit error rate level in real time to assess transmission quality and further optimize data flow allocation and path selection based on the detection results. If the bit error rate is too high, the system will automatically adjust the data flow distribution strategy or reselect the path to ensure reliable data transmission and system stability.

[0040] Step S4: Based on the bit error rate level, repair the data stream through error correction coding, and update the synchronization rate of aircraft navigation and meteorological data according to the repaired data stream.

[0041] Specifically, error correction coding is used to repair the transmitted data stream, identifying and correcting erroneous data packets caused by signal attenuation, interference, or other transmission problems. Through forward error correction coding, redundant information is added to the data packets, allowing the receiver to infer lost or corrupted data based on received data, ensuring data integrity. The repaired data stream is then re-verified, and the synchronization status of the data, especially aircraft navigation and meteorological data, is updated based on the repair progress. During this process, the system reassesses the synchronization rate of navigation and meteorological data based on the accuracy of the corrected data, ensuring that these critical data remain updated in real time and improving data transmission stability while maintaining accuracy. This step reduces data loss or errors caused by transmission instability or environmental interference through the error correction mechanism, thereby providing aircraft with more accurate navigation and meteorological data.

[0042] Step S5: Determine the completion status of real-time data synchronization based on the aircraft load status and wind direction angle.

[0043] Specifically, by combining the aircraft's load status and wind direction, the system assesses the aircraft's data processing capabilities at different flight phases based on real-time monitored load information. Load status includes processor load, storage resource usage, and the computational demands of the current task, affecting resource allocation and processing speed during data synchronization. Simultaneously, changes in wind direction affect the stability of the communication link and data transmission efficiency, especially under high-speed flight or adverse weather conditions. By comprehensively considering these factors, the system can adjust its data synchronization strategy in real time and dynamically optimize the data synchronization process based on the current load status and wind direction. Based on the combined influence of these factors, the system determines whether real-time data synchronization is complete, ensuring safe flight for the aircraft.

[0044] It is understood that the executing entity of this application can be a blockchain-based electronic flight bag data security sharing device, or it can be a terminal or a server; no specific limitation is made here. This application's embodiment uses a server as an example for illustration.

[0045] In one specific embodiment, the process of performing step S1 may specifically include the following steps:

[0046] S11. Obtain the aircraft's position coordinates and flight speed vector through the positioning system and the navigation system;

[0047] S12. Calculate the real-time trajectory of the aircraft in three-dimensional space based on the aircraft's position coordinates, flight speed vector, and environmental parameters to determine the aircraft's motion state;

[0048] S13. Calculate the communication distance with the ground station based on the aircraft's motion state, and obtain the signal propagation delay and bit error rate level by combining signal strength, noise interference and turbulence intensity, and determine the communication link status.

[0049] Specifically, the precise position coordinates and flight velocity vector of the aircraft are obtained through the Global Positioning System (GPS) and Inertial Navigation System (INS). This information provides the foundational data for subsequent flight status analysis. Combined with attitude angle data, the aircraft's spatial orientation can be further accurately described, thereby understanding its relative motion in three-dimensional space. Wind speed components and wind direction angles have a significant impact on aircraft flight. By incorporating these environmental parameters into the analysis, the aircraft's trajectory and its interaction with the external environment can be predicted more accurately. Wind speed and wind direction angles not only affect the aircraft's flight stability but also the quality of communication links. Therefore, when analyzing the aircraft's position and flight speed, these external environmental parameters must be considered simultaneously to obtain a more accurate understanding of its motion state and communication link status.

[0050] After acquiring the aircraft's trajectory, the system calculates its real-time trajectory in three-dimensional space, taking into account changes in the aircraft's current position, speed, and flight direction. Through real-time trajectory calculation, the system can infer the aircraft's dynamic behavior and assess its future motion state. This process involves not only position updates but also consideration of potential deviations and external interference during flight. Real-time trajectory calculation helps the system continuously adjust data synchronization and transmission strategies during flight, ensuring coordination between data transmission and the aircraft's motion state to meet the complex communication requirements of high-speed flight.

[0051] Based on the aircraft's position coordinates and flight velocity vector, the system also needs to calculate the communication distance between the aircraft and the ground station, a crucial factor affecting communication quality and latency. Building upon this, and combining environmental parameters such as signal strength, noise interference, and turbulence intensity, the system can dynamically assess the communication link status. Signal propagation delay and bit error rate (BER) are key indicators for evaluating communication quality. Signal propagation delay depends on the distance between the aircraft and the ground station and the influence of various environmental factors, while the BER is affected by signal interference and turbulence. By comprehensively considering these factors, the system can generate accurate communication link status data, thus providing a basis for data transmission optimization and synchronization.

[0052] By integrating the aircraft's motion status, environmental parameters, and communication link status, the system can adjust flight data transmission strategies in real time. Based on signal propagation delay and bit error rate data, the system can dynamically optimize the data transmission process, adjusting the data stream path, transmission timing, and bandwidth allocation to ensure stable and reliable data transmission during flight. This process not only improves the accuracy of data synchronization but also optimizes the efficiency of communication link utilization, providing safer and more stable flight support for the aircraft.

[0053] Taking a certain type of UAV flight mission as an example, the UAV obtains its precise position coordinates and flight velocity vector through the Global Positioning System (GPS) and Inertial Navigation System (INS). Combined with attitude angle data and real-time wind speed components, the system can accurately depict the UAV's flight trajectory in three-dimensional space. Based on this data, the system calculates the communication distance between the UAV and the ground station in real time, and generates communication link latency and bit error rate data by combining the current signal strength, noise interference, and turbulence intensity. Assuming the UAV is performing a high-altitude reconnaissance mission, facing strong wind speed changes and weather interference during flight, the system can adjust its communication strategy and optimize the communication link in a timely manner by analyzing these environmental parameters. Through real-time monitoring of the communication link status, the system automatically adjusts the data transmission sequence and reduces the data packet interval after detecting an increase in signal latency and bit error rate, ensuring timely transmission of critical information. During this process, the system also adjusts the allocation weight of multi-channel data streams based on the link quality data fed back by the ground station, ensuring priority transmission of important data such as navigation information and meteorological data. When the communication link stabilizes, the system reassesses the flight status, combines load information and real-time synchronization status, and finally determines whether data synchronization has been completed, providing reliable flight data support for subsequent UAV missions.

[0054] In one specific embodiment, the process of performing step S2 may specifically include the following steps:

[0055] S21. Based on the communication link status, an adaptive timing adjustment algorithm is used to optimize the data packet transmission interval, and wind field gradient and timing jitter correction are introduced to generate a stable transmission timing scheme.

[0056] S22. Based on the data packet interval and link delay in the transmission timing scheme, determine the priority of navigation data update rate and meteorological data synchronization rate;

[0057] S23. Calculate the allocation weight of each channel based on the bandwidth utilization rate and link congestion index, and write the allocation weight and allocation result into the blockchain through the blockchain consensus mechanism.

[0058] Specifically, by analyzing signal propagation delay and bit error rate (BER), the system can extract the current state of the communication link. Signal delay and BER are key factors affecting data transmission quality. By monitoring these parameters, the system can determine the stability and reliability of the link. If the delay is too long or the BER exceeds the standard, the system can adjust the transmission strategy to avoid data loss or delay, ensuring reliable data transmission in a highly dynamic environment. Furthermore, an adaptive timing adjustment algorithm is adopted to dynamically optimize the data packet transmission interval based on link status, wind field gradient, and timing jitter. Changes in wind field gradient and timing jitter affect data packet transmission efficiency. By adjusting the timing interval through the algorithm, the system can alleviate network congestion, improve bandwidth utilization, and ensure smooth data transmission. The optimized transmission timing scheme, based on the adjustment of link delay and data packet interval, forms a more stable transmission strategy, effectively avoiding transmission failures or excessive delays caused by link fluctuations or external environmental parameters. By combining this stable scheme, the system can prioritize navigation data update rates and meteorological data synchronization rates based on packet intervals and link latency, ensuring the priority transmission of critical data, especially crucial in flight missions where the timeliness of navigation and meteorological data is paramount. The system adjusts bandwidth resources and data stream allocation according to these priorities to ensure critical data is not delayed due to transmission congestion. Furthermore, by analyzing bandwidth utilization and congestion indices, the system can further adjust the allocation weights of each channel to maximize resource utilization. Blockchain technology records the entire process of bandwidth allocation and data stream processing, ensuring transparency and immutability of the allocation process, preventing improper modification or tampering of data, and ensuring data security and reliability during transmission. Blockchain also provides the system with an effective traceability mechanism, enabling every resource allocation and data stream processing step to be recorded and verified, ensuring the fairness of the entire process.

[0059] For example, under severe weather conditions, such as thunderstorms or strong turbulence, the wind gradient may change at a rate of 20 (m / s) / km, and the turbulence intensity may exceed the moderate level. In such situations, the communication link condition will deteriorate significantly, and the bit error rate may increase from the normal 10... -6 Rise to 10 -3 The adaptive algorithm automatically extends the packet interval from the standard 50 milliseconds to 200 milliseconds, while enabling stronger Reed-Solomon error correction coding, increasing coding redundancy from the standard 25% to 50%, ensuring that critical navigation data can be transmitted reliably.

[0060] Taking a certain type of UAV performing a remote monitoring mission as an example, the system extracts the current state of the communication link by analyzing signal propagation delay and bit error rate. The communication link between the UAV and the ground station is affected by wind speed and turbulent environmental parameters during flight. The system monitors these signal quality indicators in real time to ensure link stability. An adaptive timing adjustment algorithm dynamically optimizes the transmission interval of data packets based on these signal states. Combined with wind field gradients and timing jitter, it automatically adjusts the transmission timing to ensure stable data stream transmission. Through the optimized timing scheme, the system can adjust the interval of data packets according to link delay, reducing the impact of delay fluctuations on data transmission. Based on this, the system prioritizes navigation data and meteorological data, ensuring that real-time navigation data is transmitted first to guarantee flight safety. Simultaneously, the system analyzes bandwidth utilization and network congestion index, adjusting the allocation weight of each communication channel based on these indicators to optimize bandwidth resource usage. During data stream allocation, the system uses blockchain technology to record the specific details of each bandwidth allocation and data stream processing, ensuring transparency and security. Blockchain ensures that all allocation data is immutable and provides a complete audit log, guaranteeing the security and reliability of data transmission and preventing flight mission failures due to malicious tampering or data loss.

[0061] In one specific embodiment, the process of performing step S23 may specifically include the following steps:

[0062] S231. The bandwidth utilization rate and congestion index obtained in real time by the analysis and monitoring tools are used to obtain the data flow demand;

[0063] S232. Based on the bandwidth utilization rate and the congestion index, dynamically calculate the allocation weight of each channel using a weighted algorithm, and optimize the data stream distribution path according to the weight;

[0064] S233. Based on the communication link status, data flow requirements, and environmental parameters, a traffic allocation scheme is generated;

[0065] S234. Based on the blockchain consensus mechanism, the traffic allocation scheme and the allocation weight of each channel are written into the blockchain, and the traffic allocation scheme is automatically executed by the smart contract.

[0066] In the implementation process, a detailed analysis of the current bandwidth utilization and link congestion index is conducted to assess the load status of each communication channel. By analyzing the bandwidth usage and congestion index of the links, the system can clearly understand the transmission pressure and stability of each communication channel, identifying channels that may experience bottlenecks or overloaded links. Based on these analysis results, the system can obtain the current status of each channel, thus providing a basis for subsequent resource allocation and optimization. Based on the analysis results of bandwidth and congestion index, the system dynamically adjusts the allocation weight of each channel. By optimizing the path and bandwidth allocation of data flows, the system can effectively reduce the burden on some channels, directing more data flows to less loaded channels and optimizing resource utilization efficiency. Through this dynamic adjustment, the system can ensure that it maintains high-efficiency transmission capacity even under high data traffic conditions and reduce network congestion caused by resource imbalances.

[0067] The system performs a comprehensive analysis of link status, data flow requirements, and environmental parameters. Environmental parameters such as wind speed and air pressure can affect link stability, while data flow requirements determine the priority and bandwidth needs of different channels. By combining multiple factors, the system can derive a more reasonable traffic allocation scheme, ensuring that different types of data flows receive optimal resource guarantees. During the traffic allocation process, the system continuously adjusts its transmission strategy based on real-time changes in link status and the external environment, ensuring that the transmission of critical data is not affected.

[0068] Based on blockchain technology, the system records detailed information for each channel allocation, ensuring the transparency and immutability of the allocation process. Each adjustment and allocation scheme is automatically recorded by the blockchain, providing a reliable basis for subsequent traceability and auditing. Specifically, the system uses the following resource allocation formula to dynamically optimize data flow: ,in, It is a passage allocated bandwidth It is a passage bandwidth requirements, This is the total available bandwidth. This represents the total number of channels. The formula dynamically adjusts bandwidth allocation based on the bandwidth demand of each channel. Bandwidth allocation needs to consider link congestion and transmission quality, using a link optimization formula to determine the weight of each channel: ,in, It is a passage The allocation weights, It is a passage The delay It is a passage bit error rate, and These are adjustment parameters used to control the impact of latency and bit error rate on bandwidth allocation.

[0069] Through blockchain smart contracts, the system can automatically execute traffic allocation schemes, reducing manual intervention and ensuring efficient and accurate resource allocation. Smart contracts can automatically calculate the bandwidth allocation weight for each channel using algorithms and execute the traffic allocation scheme based on the aforementioned formula, recording the results on the blockchain to ensure the security and transparency of data transmission. Each allocation process and scheme result is executed by the smart contract and stored immutably on the blockchain, guaranteeing that all data transmission records and traffic allocation schemes can be traced and audited at any time, thus ensuring the reliability and fairness of the communication process.

[0070] Taking a commercial drone conducting high-altitude photography missions as an example, the system uses blockchain technology to record detailed information on each channel allocation, ensuring the transparency and immutability of data transmission. During flight, the system first calculates the bandwidth requirements of each communication channel and uses a channel bandwidth allocation formula to determine the bandwidth allocated to each channel. Based on link latency and bit error rate, the system dynamically adjusts the weight of each channel using a link optimization formula, ensuring that bandwidth is allocated reasonably according to real-time network conditions at different flight stages. The signal latency and bit error rate between the drone and the ground station are constantly changing, especially in high-altitude environments and environments with large wind speed variations. The system automatically adjusts the data packet transmission sequence and optimizes the data stream transmission interval to cope with signal attenuation and interference. The system uses blockchain smart contracts to automatically execute the traffic allocation scheme, updating bandwidth allocation and data stream paths based on the calculation results. The smart contract records each adjustment result in the blockchain, ensuring the transparency and immutability of each resource allocation process. Through blockchain technology, every communication and resource allocation scheme of the drone can be traced and audited, thereby improving the security and reliability of data transmission and avoiding flight mission errors caused by human intervention or data tampering. Figure 2 As shown in the figure, this diagram illustrates the process of link state analysis and data flow optimization.

[0071] In one specific embodiment, the process of performing step S3 may specifically include the following steps:

[0072] S31. Based on the allocation weight of each channel, a weighted round-robin algorithm is used to allocate the bandwidth resources;

[0073] S32. Based on the congestion index and wind shear coefficient, calculate the bandwidth allocation ratio of each channel and generate a bandwidth allocation scheme.

[0074] S33. Dynamically adjust the distribution of data traffic between the satellite link and the ground station according to the bandwidth allocation ratio of each channel;

[0075] S34. Determine the optimal data transmission path based on the signal modulation method, frequency drift value, and temperature gradient.

[0076] Specifically, bandwidth resources are allocated using a weighted round-robin algorithm based on the allocation weights of each channel. This algorithm dynamically adjusts bandwidth allocation according to the priority of different channels and the current load status to ensure reasonable resource utilization and traffic balance. The bandwidth allocation ratio for each channel is calculated based on the congestion index and wind shear coefficient. The congestion index reflects the current network load status, while the wind shear coefficient takes into account the impact of weather conditions on communication links. These factors are combined to generate a bandwidth allocation scheme. Guided by the bandwidth allocation scheme, the system can dynamically adjust the bandwidth of each channel according to the actual network conditions and external environmental conditions to meet the real-time and stability requirements of different communication needs.

[0077] Once the bandwidth allocation ratio is determined, the system will dynamically adjust the distribution of data traffic between the satellite link and the ground station based on these ratios. The adjustment of the data flow not only considers bandwidth allocation but also requires real-time monitoring of changes in link status, such as signal strength, link load, and bit error rate, to ensure stable data transmission. When satellite link bandwidth resources are strained, the system will forward some traffic to the ground station, thereby avoiding network congestion and latency, and improving overall communication efficiency.

[0078] The optimal data transmission path is determined based on the signal modulation method, frequency drift value, and temperature gradient. The signal modulation method affects the signal transmission efficiency and anti-interference capability, the frequency drift value is related to the stability of the transmission link, and the temperature gradient affects the signal propagation speed and attenuation characteristics. Taking all these factors into account, the system selects the optimal data transmission path based on real-time monitored environmental conditions and link characteristics, ensuring best performance under different network and weather conditions.

[0079] Taking data traffic management in satellite communication networks as an example, a weighted round-robin algorithm is used to allocate bandwidth to each channel, dynamically adjusting bandwidth resources based on the priority and load of different channels. The bandwidth allocation ratio for each channel is calculated based on real-time congestion indices and wind shear coefficients, generating a bandwidth allocation scheme suitable for the current network status and weather conditions. When the satellite link is overloaded due to weather interference or network congestion, the system will transfer some data traffic to ground stations, thereby alleviating the burden on the satellite link. Optimizing the bandwidth allocation scheme also requires considering factors such as signal modulation methods, frequency drift values, and temperature gradients. After comprehensively evaluating these parameters, the optimal path for data transmission is determined. For example, when the frequency drift is large, the system will choose a path with less signal attenuation for data transmission, ensuring signal stability. The entire system dynamically adjusts the distribution of data traffic according to the bandwidth allocation ratio of each channel, ensuring the efficiency and stability of the communication link. Through this dynamic optimization method, the satellite communication network can achieve optimal data transmission performance under different environmental and load conditions, effectively avoiding communication quality degradation caused by insufficient bandwidth or weather interference.

[0080] In one specific embodiment, the process of performing step S4 may specifically include the following steps:

[0081] S41. Obtain the wind field gradient of the current link, and combine it with the congestion index. If the congestion index exceeds a first preset threshold, reduce the data packet sending frequency.

[0082] S42. Obtain humidity distribution through airborne meteorological sensors, and adjust the data stream based on the humidity distribution to optimize the transmission path and rate of data packets;

[0083] S43. If the adjusted data stream bit error rate exceeds the second preset threshold, forward error correction coding is used to reorganize the data packets, and combined with air pressure changes and turbulence intensity, a repaired stable data stream is generated.

[0084] Specifically, if the congestion index exceeds a preset threshold, the system automatically adjusts the data packet transmission frequency to reduce excessive data transmission and prevent link quality degradation due to excessive network load. By reducing the transmission frequency, the system ensures that the communication link remains stable under high load, avoiding data congestion and excessive packet loss. The system also adjusts the data stream based on humidity distribution to optimize the data packet transmission path and rate. Humidity distribution has a certain impact on signal propagation characteristics; by analyzing the current humidity conditions, the system can select the optimal path for data transmission, improving the reliability and efficiency of data transmission and reducing transmission delays and signal attenuation caused by environmental factors. The system checks the bit error rate (BER) level of the adjusted data stream. If the BER exceeds a preset threshold, the system uses forward error correction coding (FEC) to reorganize the data packets. FEC improves the fault tolerance of data packets, ensuring automatic repair even if some data loss occurs during transmission, guaranteeing data integrity and correctness.

[0085] During this process, the system also incorporates external factors such as air pressure changes and turbulence intensity to further adjust the transmission strategy, generating a repaired and stable data stream to ensure that the data can successfully reach the receiving end. Through these refined adjustments, the system can dynamically optimize the data stream in complex environments, maximizing the stability and transmission efficiency of the communication link and reducing the risk of data transmission failure or performance degradation due to environmental changes.

[0086] Taking satellite communication systems as an example, when the link congestion index reaches a set threshold, the system automatically reduces the data packet transmission frequency to alleviate the link burden and avoid excessive network congestion. At this time, humidity distribution is used to optimize the data stream transmission path. The system selects the optimal transmission path based on humidity changes in different areas, thereby improving data transmission efficiency and stability. If the error rate is found to be too high in the adjusted data stream, the system will initiate a forward error correction coding mechanism to reorganize the data packets, ensuring that even if some data is lost or damaged, data integrity can still be restored through error correction. Simultaneously, the system will further optimize the data stream by considering environmental factors such as air pressure changes and turbulence intensity, ensuring stable data transmission even under adverse weather conditions. These dynamic adjustment processes ensure the reliability and stability of the communication link under different environments and network conditions, avoiding communication quality degradation caused by congestion, humidity, or changes in weather conditions.

[0087] In one specific embodiment, the process of performing step S5 may specifically include the following steps:

[0088] S51. Based on the aircraft load status and the wind direction angle, determine the priority of real-time data synchronization requirements;

[0089] S52. Adjust the data stream distribution path based on the priority of the real-time data synchronization requirements to obtain an optimized transmission sequence;

[0090] S53. Allocate bandwidth resources according to the transmission sequence, determine whether the communication link status meets the synchronization requirements, and if so, repair the data stream through error correction coding and update the navigation data synchronization rate.

[0091] Specifically, during implementation, the system acquires the aircraft's load status and wind direction to determine the priority of real-time data synchronization needs. Based on the aircraft's current load status, the system determines which data needs to be synchronized first, such as critical navigation information and meteorological data. Changes in wind direction may affect the aircraft's flight attitude, thus impacting synchronization requirements. The system adjusts the data stream distribution path based on this priority information to ensure that high-priority data streams are transmitted first. By adjusting the transmission path, the system optimizes the data stream transmission sequence, improves transmission efficiency, and prevents low-priority data from consuming excessive bandwidth resources.

[0092] Based on the optimized transmission sequence, the system allocates bandwidth resources to ensure that each data stream is reasonably allocated even with limited bandwidth. After allocating bandwidth resources, the system determines whether the current communication link status meets the synchronization requirements. If the link status is good, the bit error rate is low, and the bandwidth is sufficient, the system repairs the data stream through error correction coding, further ensuring that data is not lost or damaged during transmission. Based on the repaired data stream, the system updates the synchronization rate of navigation data, ensuring real-time synchronization of all critical data and guaranteeing that the aircraft's navigation and meteorological information is always up-to-date. This series of steps, through dynamic adjustment and optimization, ensures efficient data synchronization and communication stability under various environmental and load conditions.

[0093] The above describes the blockchain-based electronic flight bag data security sharing method in the embodiments of this application. The following describes the blockchain-based electronic flight bag data security sharing device in the embodiments of this application. Please refer to [link / reference]. Figure 3 One embodiment of the blockchain-based electronic flight bag data security sharing device in this application includes:

[0094] Module 201 is used to acquire the aircraft's motion trajectory through the aircraft's positioning and navigation systems, and determine the communication link status by combining environmental parameters, including: attitude angle data, wind speed components and wind direction angle;

[0095] Module 202 is used to optimize the data packet transmission timing using an adaptive algorithm based on the communication link status, determine the allocation weight of the multi-channel data stream based on the transmission timing and the communication link status, and process the data packets through a blockchain consensus mechanism.

[0096] Module 203 is used to allocate bandwidth resources through a weighted algorithm, dynamically adjust the data stream distribution path in combination with the environmental parameters, and detect the bit error rate level from the adjusted data stream.

[0097] Module 204 is used to repair the data stream through error correction coding based on the bit error rate level, and update the synchronization rate of aircraft navigation and meteorological data according to the repaired data stream;

[0098] Module 205 is used to determine the completion status of real-time data synchronization based on the aircraft load status and wind direction angle.

[0099] Through the collaborative efforts of the aforementioned components, the system effectively achieves secure data sharing for electronic flight bags based on blockchain. Module 201 acquires the aircraft's trajectory and assesses the current communication link status in conjunction with environmental parameters. This environmental data significantly impacts the stability of the communication link, providing a foundation for subsequent data transmission and optimization. Module 202, based on the acquired communication link status, employs an adaptive algorithm to optimize the timing of data packet transmission. By precisely calculating the transmission timing and link status, it determines the data stream allocation weights for different channels, thereby optimizing bandwidth utilization efficiency and ensuring data security and integrity through a blockchain consensus mechanism. Module 203 uses a weighted algorithm to allocate bandwidth resources and dynamically adjusts the data stream distribution path in conjunction with environmental parameters. If the link status changes, the system automatically readjusts the data stream path to ensure efficient data transmission. Furthermore, Module 203 monitors the bit error rate to promptly identify and correct transmission problems, ensuring data stream stability. Module 204, during this process, repairs the data stream through forward error correction coding, ensuring complete data transmission even under high bit error rates. The repaired data stream will be used to update the synchronization rate of the aircraft's navigation and meteorological data, ensuring that the aircraft always receives the latest and most accurate flight and weather information. Module 205 determines the completion status of real-time data synchronization based on the aircraft's load status and wind direction. When the system load is heavy, critical data is synchronized first to ensure flight safety and real-time decision-making. Through the collaboration of these modules, the system can ensure the safe, efficient, and stable transmission and sharing of flight data, improving the operational efficiency and safety of the aircraft.

[0100] above Figure 3 The blockchain-based electronic flight bag data security sharing device in this embodiment of the invention will be described in detail from the perspective of modular functional entities. The blockchain-based electronic flight bag data security sharing device in this embodiment of the invention will be described in detail from the perspective of hardware processing.

[0101] Reference Figure 4This invention also provides a blockchain-based electronic flight bag data security sharing device, which can be a server, and its internal structure can be as follows: Figure 4 As shown, the blockchain-based electronic flight bag data security sharing device includes a processor, memory, display screen, input device, network interface, and database connected via a system bus. The processor, designed as a computer, provides computing and control capabilities. The memory of the blockchain-based electronic flight bag data security sharing device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database of the blockchain-based electronic flight bag data security sharing device stores the data corresponding to this embodiment. The network interface of the blockchain-based electronic flight bag data security sharing device is used for communication with external terminals via network connection. When the computer program is executed by the processor, it implements the above-described method.

[0102] Those skilled in the art will understand that Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present invention and does not constitute a limitation on the blockchain-based electronic flight bag data security sharing device to which the present invention is applied.

[0103] The present invention also provides a computer-readable storage medium, which can be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium, wherein the computer-readable storage medium stores instructions that, when the instructions are executed on a computer, cause the computer to perform the steps of the blockchain-based electronic flight bag data secure sharing method.

[0104] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0105] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0106] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A blockchain-based method for securely sharing electronic flight bag data, characterized in that: The method includes: S1. Obtain the aircraft's trajectory through the aircraft's positioning and navigation systems, and determine the communication link status by combining environmental parameters, including: attitude angle data, wind speed components, and wind direction angle. S2. Based on the communication link status, an adaptive algorithm is used to optimize the data packet transmission timing, the allocation weight of the multi-channel data stream is determined based on the transmission timing and the communication link status, and the data packets are processed through a blockchain consensus mechanism. S3. Allocate bandwidth resources through a weighted algorithm, dynamically adjust the data stream distribution path in combination with the environmental parameters, and detect the bit error rate level from the adjusted data stream; S4. Based on the bit error rate level, repair the data stream through error correction coding, and update the synchronization rate of aircraft navigation and meteorological data according to the repaired data stream; S5. Determine the completion status of real-time data synchronization based on the aircraft load status and the wind direction angle; S2 includes: S21, optimizing the data packet transmission interval using an adaptive timing adjustment algorithm based on the communication link status, and introducing wind field gradient and timing jitter correction to generate a stable transmission timing scheme; S22, determining the priority of navigation data update rate and meteorological data synchronization rate based on the data packet interval and link delay in the transmission timing scheme; S23, calculating the allocation weight of each channel based on bandwidth utilization and link congestion index, and writing the allocation weight and allocation result into the blockchain through a blockchain consensus mechanism; S3 includes: S31, allocating bandwidth resources using a weighted round-robin algorithm based on the allocation weight of each channel; S32, calculating the bandwidth allocation ratio of each channel based on the congestion index and wind shear coefficient, and generating a bandwidth allocation scheme; S33, dynamically adjusting the distribution of data traffic between the satellite link and the ground station according to the bandwidth allocation ratio of each channel; and S34, determining the optimal path for data transmission based on the signal modulation method, frequency drift value, and temperature gradient. S5 includes: S51, determining the priority of real-time data synchronization requirements based on the aircraft load status and the wind direction angle; S52, adjusting the data stream distribution path based on the priority of real-time data synchronization requirements to obtain an optimized transmission sequence; S53, allocating bandwidth resources according to the transmission sequence, determining whether the communication link status meets the synchronization requirements, and if so, repairing the data stream through error correction coding and updating the navigation data synchronization rate.

2. The blockchain-based electronic flight bag data secure sharing method according to claim 1, characterized in that, S1 includes: S11. Obtain the aircraft's position coordinates and flight speed vector through the positioning system and the navigation system; S12. Calculate the real-time trajectory of the aircraft in three-dimensional space based on the aircraft's position coordinates, flight speed vector, and environmental parameters to determine the aircraft's motion state; S13. Calculate the communication distance with the ground station based on the aircraft's motion state, and obtain the signal propagation delay and bit error rate level by combining signal strength, noise interference and turbulence intensity, and determine the communication link status.

3. The blockchain-based electronic flight bag data secure sharing method according to claim 1, characterized in that, S23 includes: S231. The bandwidth utilization rate and congestion index obtained in real time by the analysis and monitoring tools are used to obtain the data flow demand; S232. Based on the bandwidth utilization rate and the congestion index, dynamically calculate the allocation weight of each channel using a weighted algorithm, and optimize the data stream distribution path according to the weight; S233. Based on the communication link status, data flow requirements, and environmental parameters, a traffic allocation scheme is generated; S234. Based on the blockchain consensus mechanism, the traffic allocation scheme and the allocation weight of each channel are written into the blockchain, and the traffic allocation scheme is automatically executed by the smart contract.

4. The blockchain-based electronic flight bag data secure sharing method according to claim 1, characterized in that, S4 includes: S41. Obtain the wind field gradient of the current link, and combine it with the congestion index. If the congestion index exceeds a first preset threshold, reduce the data packet sending frequency. S42. Obtain humidity distribution through airborne meteorological sensors, and adjust the data stream based on the humidity distribution to optimize the transmission path and rate of data packets; S43. If the adjusted data stream bit error rate exceeds the second preset threshold, forward error correction coding is used to reorganize the data packets, and combined with air pressure changes and turbulence intensity, a repaired stable data stream is generated.

5. A device for securely sharing blockchain-based electronic flight bag data, used to implement the blockchain-based electronic flight bag data secure sharing method as described in any one of claims 1 to 4, characterized in that, The device for secure sharing of blockchain-based electronic flight bag data includes: The trajectory and link analysis module is used to acquire the aircraft's motion trajectory through the aircraft's positioning and navigation systems, and determine the communication link status by combining environmental parameters, including: attitude angle data, wind speed components, and wind direction angle. The transmission timing and traffic allocation module is used to optimize the data packet transmission timing using an adaptive algorithm based on the communication link status, determine the allocation weight of multi-channel data streams based on the transmission timing and the communication link status, and process data packets through a blockchain consensus mechanism. The bandwidth allocation and path adjustment module is used to allocate bandwidth resources through a weighted algorithm, dynamically adjust the data stream distribution path in combination with the environmental parameters, and detect the bit error rate level from the adjusted data stream. The data stream repair and synchronization module is used to repair the data stream through error correction coding based on the bit error rate level, and update the synchronization rate of aircraft navigation and meteorological data according to the repaired data stream; The real-time synchronization status confirmation module is used to determine the completion status of real-time data synchronization based on the aircraft load status and wind direction angle.

6. A data security sharing device for blockchain-based electronic flight bags, characterized in that, The device for secure sharing of blockchain-based electronic flight bag data includes: a memory and at least one processor, wherein the memory stores instructions; The at least one processor invokes the instructions in the memory to cause the blockchain-based electronic flight bag data secure sharing device to perform the blockchain-based electronic flight bag data secure sharing method as described in any one of claims 1 to 4.

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