Communication method and device, electronic equipment and storage medium

Abstract

The invention provides a communication method and device, electronic equipment and a storage medium. The method comprises the following steps: sending a verification data packet to an aggregation node by taking a communication rate as a first baud rate; and monitoring confirmation information returned by the aggregation node, if the confirmation information is not received in a preset first time period, reducing the current communication rate step by step, resending the verification data packet, and repeatedly executing the operations of reducing the communication rate and resending the verification data packet until the confirmation information is successfully received in the preset first time period, the communication rate at the moment is used as a second baud rate; and transmitting the to-be-transmitted data to the sink node by adopting the second baud rate. According to the invention, a satellite communication technology is utilized to realize high-speed data transmission with seamless coverage in a global range, so that the delay time of data transmission is greatly shortened; a communication adaptive strategy is introduced in the data transmission process, and the reliability and real-time performance of data transmission can be effectively improved by adaptively adjusting the communication rate and adaptively allocating the channel capacity.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication, and particularly to a communication method, device, electronic device, and storage medium. Background Art

[0002] Traditional methods for transmitting shipborne voyage records mainly include three types: wired transmission schemes, coverage network transmission schemes for inland rivers and coastal waters, and Beidou short message transmission schemes for the open sea. Wired transmission schemes have problems of cost and signal attenuation. For the coverage network (Wi-Fi, LTE, etc.) transmission schemes for inland rivers and coastal waters and the Beidou short message transmission schemes for the open sea, there are still problems in data transmission. Wireless networks are vulnerable to interference when the signal is unstable or in coverage blind spots. Although the Beidou system has accurate navigation, it is still insufficient in terms of data transmission bandwidth and rate, and it is difficult to meet the requirements of voyage records for real-time and large-capacity data. Especially in ocean voyages or extreme weather conditions, this limitation is particularly prominent, affecting the reliability and real-time performance of data transmission. Therefore, traditional transmission schemes all expose problems such as slow speed, limited storage capacity, and insufficient data security in data transmission, and it is difficult to meet the stringent requirements of modern ship operation and management. Summary of the Invention

[0003] Embodiments of the present application provide a communication method, device, electronic device, and storage medium for realizing reliable and real-time transmission of data in ocean voyages or extreme weather conditions.

[0004] Other features and advantages of the present application will become apparent through the following detailed description, or be learned in part through the practice of the present application.

[0005] According to a first aspect of an embodiment of the present application, a communication method is provided, including: sending a check data packet to a convergence node at a communication rate of a first baud rate, where the convergence node is a data reception destination; monitoring the acknowledgment information returned by the convergence node within a preset first time period. If the acknowledgment information is not received within the preset first time period, gradually reduce the current communication rate and resend the check data packet, and repeat the operations of reducing the communication rate and resending the check data packet until the acknowledgment information is successfully received within the preset first time period, and use the communication rate at this time as the second baud rate; transmit the data to be transmitted to the convergence node using the second baud rate.

[0006] In an embodiment of the present application, the first baud rate is the highest baud rate of the system, and the second baud rate is less than or equal to the first baud rate and greater than or equal to the lowest baud rate of the system.

[0007] In an embodiment of the present application, the length of the preset first time period is dynamically adjusted according to the current communication rate.

[0008] In one embodiment of the present application, it further includes that after a preset second time period, the second baud rate is re-determined and used as the new communication rate.

[0009] In one embodiment of the present application, it further includes transmitting the data to be transmitted to the aggregation node by means of adaptively allocating channel capacity. The adaptive allocation of channel capacity specifically includes: estimating the minimum channel traffic; configuring the traffic transmission channel with the minimum channel traffic as a constraint condition under a given communication capacity; estimating the traffic of each channel and completing the capacity allocation of each channel.

[0010] In one embodiment of the present application, a directed graph model is constructed based on the network structure, and the channel communication traffic is simulated as a queue with intersections to complete the estimation of the minimum channel traffic.

[0011] In one embodiment of the present application, the estimating the traffic of each channel and completing the capacity allocation of each channel specifically includes: generating random data to form an initial solution space, where the random data represents the buffer length of each channel; setting an objective function based on the estimated traffic of each channel and the configured traffic transmission channel; iteratively optimizing the solution space based on the objective function to determine the optimal solution; and performing channel capacity allocation according to the optimal solution.

[0012] In one embodiment of the present application, the estimating the traffic of each channel and completing the capacity allocation of each channel further includes: dynamically adjusting the allocation strategy of the channel capacity according to the real-time monitoring results and feedback of the channel.

[0013] In one embodiment of the present application, before transmitting the data, it further includes: classifying the data to be transmitted into category A, category B, and category C from high to low according to the importance of the data; for the category A data to be transmitted, using the lossless compression method; for the category B data to be transmitted, dynamically switching between the lossless compression method and the lossy compression method according to the overall compression rate; and for the category C data to be transmitted, using the lossy compression method.

[0014] In one embodiment of the present application, the data is segmented and linearly fitted by time period, and only the endpoints of the fitted line segments are retained to complete the compression of the data.

[0015] In one embodiment of the present application, before transmitting the data, it further includes generating a random number to participate in the elliptic curve point, and encrypting the data to be transmitted based on the encryption method of elliptic curve cryptography.

[0016] According to the second aspect of the embodiments of the present application, a communication device is provided, including: a data acquisition module for acquiring the data to be transmitted; a control processing module for sending a check data packet to the aggregation node and monitoring the confirmation information fed back by the aggregation node to complete the adjustment of the current communication rate; the aggregation node being the data receiving destination; and a communication module for transmitting the data to be transmitted to the aggregation node at the adjusted communication rate.

[0017] In another embodiment of the present application, the control processing module is further configured to estimate the minimum channel traffic, configure a traffic transmission channel with the minimum channel traffic as a constraint condition, estimate the traffic of each channel, and complete the capacity allocation of each channel.

[0018] According to a third aspect of the embodiments of the present application, there is provided an electronic device, including a memory and a processor, and a computer program capable of being loaded and executed by the processor and corresponding to the communication method described in the first aspect is stored on the memory.

[0019] According to a fourth aspect of the embodiments of the present application, there is provided a computer-readable storage medium, on which computer program instructions are stored, and the program instructions are used to implement the process corresponding to the communication method described in the first aspect when executed by a processor.

[0020] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The drawings here are incorporated into the specification and form a part of this specification, showing embodiments consistent with the present application, and are used together with the specification to explain the principles of the present application. Obviously, the drawings in the following description are only some embodiments of the present application, and those of ordinary skill in the art can obtain other drawings based on these drawings without creative efforts.

[0022] Figure 1 It is a schematic diagram of the communication method according to the embodiment of the present application.

[0023] Figure 2 It is a schematic diagram of adaptively adjusting the communication rate according to the embodiment of the present application.

[0024] Figure 3 It is a schematic diagram of the routing node queue model according to the embodiment of the present application.

[0025] Figure 4 It is a schematic diagram of lightweight according to the embodiment of the present application.

[0026] Figure 5 It is a schematic diagram of data classification according to the embodiment of the present application.

[0027] Figure 6 It is a schematic diagram of the communication device according to the embodiment of the present application.

[0028] Figure 7 It is a schematic diagram of data storage according to the embodiment of the present application.

[0029] Figure 8 It is a schematic diagram of the electronic device according to the embodiment of the present application.

[0030] Figure 9 It is a schematic structural diagram of a computer system suitable for implementing the embodiments of the present application.

[0031] Reference numerals:

[0032] 100 - Communication device, 101 - Control processing module, 102 - Communication module, 103 - Data acquisition module, 104 - Data storage module, 105 - Power module, 106 - Satellite communication antenna, 107 - Audio module, 108 - Audio device, 109 - Communication interface, 110 - WIFI antenna, 111 - Bluetooth antenna, 112 - Beidou antenna, 113 - Human - machine interaction module, 114 - Additional expansion module, 115 - Voyage data recorder;

[0033] 200 - Electronic device, 201 - Memory, 202 - Processor;

[0034] 300 - Computer system, 301 - CPU, 302 - ROM, 303 - RAM, 304 - Bus, 305 - I / O interface, 306 - Input section, 307 - Output section, 308 - Storage section, 309 - Communication section, 310 - Driver, 311 - Removable medium. Detailed implementation manners

[0035] To make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application. Without conflict, the embodiments in the present application and the features in the embodiments can be combined with each other arbitrarily. And although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order from that here.

[0036] The terms "first" and "second" in the specification and claims of the present application and the above - mentioned accompanying drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the term "including" and any variations thereof are intended to cover non - exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally further includes steps or units not listed, or optionally further includes other steps or units inherent to these processes, methods, products or devices.

[0037] The existing three transmission schemes, namely the wired transmission scheme, the coverage network transmission scheme for inland rivers and coastal waters, and the Beidou short message transmission scheme for the open sea, all have certain defects in the three aspects of communication capacity allocation, data compression, and data encryption, as follows:

[0038] (1) In terms of communication capacity allocation: Traditional schemes often allocate resources based on static communication requirements and channel states, lacking the ability of dynamic adjustment. Although this method is simple, it cannot make full use of the dynamic changes of the channel, resulting in low resource utilization. Some schemes can monitor the channel state, but the real-time and accuracy of the monitoring are limited, making it difficult to comprehensively reflect the dynamic changes of the channel, which restricts the effective management and optimization of channel resources by the system. The evaluation method of communication capacity is relatively simple, often only considering the current communication situation and ignoring the potential scalability and dynamic changes of the channel state. This causes the system to be difficult to make timely responses and adjustments when facing sudden traffic or channel state changes.

[0039] (2) In terms of data encryption: The existing data encryption schemes mainly include symmetric encryption and asymmetric encryption. Symmetric encryption is known for its high efficiency and fast encryption speed. However, key distribution and management are the main challenges faced by symmetric encryption. Asymmetric encryption solves the problem of key distribution, but the encryption and decryption speeds are relatively slow and not suitable for the transmission of large amounts of data.

[0040] (3) In terms of data compression: The strategies of traditional data compression mainly focus on removing redundant information in the data while retaining the differential features of the data. In terms of compression strategies and efficiency, existing technologies usually adopt a unified compression strategy without considering the importance and type differences of the data. This may lead to the same treatment of critical data and non-critical data, increasing both the storage and transmission burdens and potentially sacrificing the integrity of critical data.

[0041] Due to the limitations of wireless networks and Beidou communication, the global seamless coverage, high bandwidth, and low latency characteristics of satellite communication systems can provide a more reliable and efficient solution for voyage record transmission.

[0042] Due to the fact that the current satellite communication system needs to handle a huge amount of data traffic, there are deficiencies in global optimization, which easily leads to problems such as channel congestion and resource waste. Moreover, the lack of refined traffic control and optimization strategies will also cause the system to be difficult to quickly respond and make effective adjustments in complex traffic scenarios. At the same time, the satellite communication environment is complex and changeable, covering multiple factors such as atmospheric interference and satellite orbit changes, which poses a severe challenge to the adaptive adjustment ability of the system. The existing communication system may be difficult to adjust the communication rate and channel state accurately in real time to adapt to these dynamic changes, and its scalability may also be limited, making it difficult to meet the expected continuous growth of future communication requirements. Therefore, based on this, the embodiments of the present application propose a communication method applied to terminal nodes. The terminal nodes transmit data to a convergence node, and the convergence node is the data reception destination. Taking the data to be transmitted as navigation data as an example for illustration, the convergence node is a land data center. This communication method mainly realizes data transmission under ocean navigation or extreme weather conditions based on a satellite network, ensuring the real-time and reliable data transmission. This communication method controls the data transmission through an adaptive strategy to ensure the reliability and real-time of data transmission. Specifically, the communication adaptive strategy includes adaptively adjusting the communication rate and adaptively allocating the channel capacity, and can be executed alternatively or in combination.

[0043] In an embodiment of the present application, a communication method for adaptively adjusting the communication rate is provided. When adjusting the communication rate, this method makes the communication rate as high as possible at the baud rate that can enable normal communication to improve transmission real-time. Please refer to Figure 1 、 Figure 2 , and the specific process is as follows:

[0044] First, by default, use the first baud rate as the starting communication rate, and send a check data packet containing a CRC check code to the convergence node through the satellite network. This CRC check code is used to ensure the integrity of the data packet. In the embodiments of the present application, the first baud rate represents the highest baud rate of the current system.

[0045] Then, monitor the acknowledgment information returned by the sink node within a preset first time period. If the acknowledgment information is not received within the preset first time period, gradually decrease the current communication rate and resend the verification data packet. Repeat the operations of decreasing the communication rate and resending the verification data packet until the acknowledgment information is successfully received within the preset first time period, and use the communication rate at this time as the second baud rate. Specifically, first determine the preset first time period, and judge whether the acknowledgment information (ACK, Acknowledge character) from the sink node is received within the preset first time period. If the acknowledgment information is received within the preset first time period, verify it and confirm that the communication is successful, indicating a normal communication state, and the current communication rate is the second baud rate without adjustment. If the ACK acknowledgment information is not received within the preset first time period or an error occurs during the reception process, it means that the current communication rate is too high; at this time, the communication rate needs to be adjusted down to the baud rate, and the verification data packet is reconfigured and sent. Repeat the process of rate adjustment and verification data packet sending until the acknowledgment information returned by the sink node is successfully received within the preset first time period, and the communication rate at this time is the second baud rate. Additionally, if the data packet still cannot be received after adjusting the communication rate to the lowest communication rate of the system, it is considered that the effective communication range of the sink node has been exceeded, and the corresponding processing logic is triggered, such as sending an alarm message or attempting to re - establish a connection. In this embodiment, the highest baud rate of the system = the first baud rate ≥ the second baud rate ≥ the lowest baud rate of the system.

[0046] Finally, transmit the data to be transmitted to the sink node using the second baud rate, and the data transmission can be completed.

[0047] It should be added that the length of the preset first time period is determined according to the expected time for data packet transmission calculated based on the current communication rate, and will change dynamically with the adjustment of the communication rate.

[0048] To ensure the stability and efficiency of communication, trigger the operation of adaptively adjusting the communication rate after a preset second time period, that is, in each operation, re - determine the second baud rate and use it as the new communication rate. Through the adaptive communication rate adjustment strategy, the communication rate in the current communication environment can be automatically matched. The length of the preset second time period can be adjusted according to the communication environment. This communication method uses a geostationary orbit satellite or a low - orbit satellite as a relay station to transmit data between the satellite and the ground station or user terminal through electromagnetic waves, with high anti - interference ability and stability, and can ensure the reliable transmission of data. This transmission method also has the characteristic of global seamless coverage, is not restricted by terrain, climate, and geographical location, and is especially suitable for data transmission in extreme harsh environments such as ocean voyages or polar regions, and can meet most data transmission requirements, including high - definition videos, big data files, etc.

[0049] In a communication network, reasonable allocation of communication capacity is the key to ensuring the efficient operation of the network. To achieve this goal, based on the communication capacity, the adaptive adjustment of the communication channel state and the scalable characteristics of the channel are considered. In another embodiment of the present application, it is proposed to use the method of adaptively allocating channel capacity to transmit the data to be transmitted to the aggregation node. By introducing a directed graph model and combining queuing theory, the communication capacity is accurately evaluated, and a capacity allocation scheme is formulated based on this, which can minimize the average data transmission delay. The specific process is as follows:

[0050] Step 1: Determine the basic information and constraints.

[0051] First, it is necessary to determine the basic information such as the existing network structure, routing algorithm, and communication traffic between nodes. Set the constraints and the total resource amount (i.e., channel capacity). In this embodiment, the minimum traffic in each communication channel is used as the constraint condition to ensure the maximization of the number of communication channels and avoid congestion.

[0052] Step 2: Estimate the minimum channel traffic.

[0053] To estimate the minimum traffic of the bandwidth electronic communication channel, the embodiment of the present application introduces a directed graph model, simulates the channel communication traffic as a queue with intersections, solves the problem of finding the time-division switching queue through the directed graph, reduces the waiting time, so that the traffic can quickly pass through the channel, and realizes the minimum traffic estimation. Specifically, set the directed graph as G=(V,E), where V is the set of all network nodes; E is the set of communication links between adjacent nodes. The link set can be expressed in the following form:

[0054]

[0055] In the formula, h=(u,v) represents the link; u and v represent two different nodes; H(u) represents the total number of known link sets on node u; H i (u) and H0(u) represent the output and input link sets on node u respectively.

[0056] By monitoring the state changes of the communication channel in real time and combining the simulation results of the directed graph model, estimate the minimum traffic of each channel. In this embodiment, under the given communication capacity, the minimum channel traffic is used as the constraint condition to configure the traffic transmission channel for the subsequent steps, that is, to maximize the number of communication channels.

[0057] By introducing a directed graph model, the simulation accuracy of channel communication traffic and the dynamic evaluation ability of communication capacity are significantly improved. Compared with traditional technologies that are only limited to the static analysis of the current communication situation, it fully considers the dynamic changes of the channel state and provides a more solid and reliable data basis. During the transmission process, it real-time tracks the state changes of the communication channel, and according to the simulation results of the directed graph model, flexibly adjusts the evaluation of communication capacity and resource allocation strategies, which can effectively prevent channel congestion and promote the efficient and balanced flow of network communication traffic.

[0058] Step 3: Estimation of the traffic of each channel.

[0059] Nodes can communicate using multiple channels simultaneously. Therefore, it is necessary to reasonably estimate the traffic of each channel according to the network structure, node communication capacity, and the real-time monitored channel state. At the same time, the probability variance G corresponding to the input channel is used to evaluate the full-load situation of the input channel buffer. The calculation formula of the probability variance G corresponding to the input channel is as follows:

[0060]

[0061] In the formula: h x,y,d represents the probability that the input communication buffer is full; represents the total number of data packets in the channel; R represents the total number of node channels. By accurately calculating the probability variance G of the input channel, a corresponding objective function can be set subsequently to optimize the usage efficiency of the communication channel and more reasonably achieve channel capacity allocation.

[0062] Step 4: Set the objective function to optimize communication performance.

[0063] In actual communication, a node includes independent input channels in multiple directions, and each channel has its specific data packet arrival rate and service rate. Please refer to Figure 3 , in the embodiment of the present application, by applying queuing theory, a queue model is constructed based on the multiple input channels of the routing node. Using this model, the average waiting time and queue length of data packets in each channel can be calculated, so as to real-time monitor and evaluate the load situation of the channel. At the same time, an objective function can also be set based on the constructed queue model to complete the optimization of communication performance. Taking the objective function of optimizing the usage efficiency f x,y,E as an example, it is set as follows:

[0064]

[0065] In the formula: f x,y,E represents the usage efficiency of the target communication range; r x,y,E represents the total length of the communication channel; β x,y,ERepresents the communication rate of data packets in the communication channel. Based on this objective function, adjusting factors such as the total length of the communication channel and the communication rate of data packets can complete the optimization of the corresponding communication performance.

[0066] Please continue to refer to Figure 3 , combined with relevant theoretical analysis, it can be known that the data transmitted from direction E can be forwarded to multiple different directions respectively, and there are corresponding node services. Among them, the queue waiting time mainly utilizes the service rate provided by the downstream buffer Obtained by giving the calculation formula of the service rate:

[0067]

[0068] Among them, α x,y,E Represents the probability of successful data transmission in the communication channel, κ x,y,E Represents the routing function, β x,y,E Represents the transmission rate of data packets in the communication channel.

[0069] Considering from the perspective of the channel (x, y, E), the waiting time W of the data packet in the queue can be obtained x,y-1,E , and the specific calculation formula is:

[0070]

[0071] Among them, The data packet processing rate (data packets per second) from the communication channel (x, y, E) to (x, y - 1, E), κ x,y,E Represents the routing function; β x,y,E Represents the transmission rate of data packets in the communication channel.

[0072] By considering the queue waiting time and the waiting time of the data packet in the queue, the data transmission delay is minimized, and the optimal configuration of the communication channel capacity is achieved. It should be added that in other embodiments, the objective function can be set according to the performance parameters to be concerned about.

[0073] Step 5, construct the solution space and iterative calculation.

[0074] ① Set the initial data and the initial solution space. This data includes the buffer lengths of each communication channel, which are organized in three-dimensional data form, and this data is randomly generated to simulate the uncertainty in the actual communication environment.

[0075] ② After initialization, according to the current communication status and requirements, construct a new solution space. This solution space contains possible communication channel capacity allocation schemes.

[0076] ③ Calculate the increment between the new solution and the current solution to optimize communication performance. If the increment is less than 0, it indicates that the new solution optimizes the current communication performance to some extent. Therefore, the new solution is taken as the current solution. If the increment is not less than 0, the new solution is accepted with a certain probability to avoid being trapped in a local optimal solution.

[0077] ④ Determine whether the algorithm meets the termination condition. Assuming it does, directly output the optimal solution, that is, the optimal communication channel capacity allocation scheme; otherwise, return to step ② to continue exploring the new solution space and update the current solution until a solution that meets the conditions is found.

[0078] Step 6: Determine the capacity allocation scheme.

[0079] Based on the relevant parameters obtained in the previous steps (such as the minimum channel flow, channel flow estimation, optimization results of the objective function, etc.), iteratively determine the final communication channel capacity allocation scheme to ensure the efficient and balanced distribution of network communication traffic.

[0080] Step 7: Dynamic adjustment and continuous optimization.

[0081] During the actual operation process, continuously monitor the state changes of the communication channels. According to the real-time monitoring results and feedback, dynamically adjust the evaluation and allocation strategies of communication capacity, and through continuous optimization, improve the stability and efficiency of the entire communication system.

[0082] Compared with the problems that the existing technology may face, such as high data transmission delay and low channel utilization rate, this application provides a more efficient and practical solution. By setting configurable constraint conditions and objective functions, and using randomly generated initial data to simulate the uncertainty of the actual communication environment, the applicability and flexibility of the system are significantly enhanced. Its flexible parameter settings and algorithm design enable the system to easily cope with different communication requirements and network environment changes, and achieve adaptive adjustment.

[0083] By applying the communication method of adaptively adjusting the communication rate and adaptively adjusting the channel capacity, the applicability and flexibility of the communication system are significantly enhanced, enabling it to easily cope with different communication requirements and network environment changes, showing significant advantages compared with the existing technology. It is applicable to scenarios such as Internet access, ocean communication, and emergency communication globally, with high flexibility and scalability. It can meet the high-speed and stable data transmission requirements of ships during ocean voyages.

[0084] Please refer to Figure 4, in the communication method proposed by the embodiments of the present application, before transmitting data, lightweight processing is also performed on the data to be transmitted. Different from the unified compression strategy of traditional solutions, in the lightweight processing process of the embodiments of the present application, the data to be transmitted is classified according to its importance, and then different compression methods are adopted for different categories of data. The compression methods mainly include lossless compression and lossy compression.

[0085] Please refer to Figure 5 To clarify the data categories of lossy and lossless compression in the hybrid compression strategy and ensure the accuracy of data transmission, the embodiments of the present application classify the data to be transmitted into Class A, Class B, and Class C from high to low. Taking navigation data as an example:

[0086] Class A includes: real-time navigation ship status safety data, including basic navigation data, alarms and warning information, radar and AIS information, bridge recordings, and wireless communications, etc. For Class A data, these data directly reflect the real-time status of the ship and are crucial for ensuring navigation safety. Errors in them will affect the navigation safety of the ship, and lossless compression must be performed during the compression process.

[0087] Class B includes: ship navigation environment data and ship engine room environment data. For Class B data, the compression method is dynamically switched according to the overall compression ratio. That is, during the compression process, if the overall compression ratio of the data does not meet the requirements, lossy compression can be used for compression; if the compression ratio requirement is met, lossless compression is better than lossy compression.

[0088] Class C includes: Electronic Chart Display and Information System (ECDIS) screen images and other sensor data. For Class C data, the required accuracy is not high, but the approximate range of the data needs to be understood, and lossy compression is used for such data.

[0089] During the actual navigation data transmission process, for navigation data every certain period of time (for example, 30 seconds), the data within this period can be regarded as linearly changing. Therefore, the embodiments of the present application adopt a compression method based on piecewise linear fitting to achieve data compression. By linearly fitting the data and only retaining the endpoints of the fitted line segments, the data compression is completed, reducing the amount of transmitted data. And, the compression and decompression operation complexity based on piecewise linear fitting is low, which can ensure less resource consumption during the data compression process. The specific compression method is as follows:

[0090] Let the fitted line be: where is the parameter approximation value. To obtain the best a and b so that the fitted line best conforms to the actual situation, calculate its mean squared error (MSE):

[0091]

[0092] Among them, t i represents the time series when the parameter value is y i and represents the parameters a * , b * of the best-fit straight line for this segment of data. The calculation formulas are as follows:

[0093]

[0094] a * , b * are the values of a and b when the mean square error reaches the minimum value, that is, the derivatives of MSE(a, b) with respect to a and b are zero. Obtained from as follows:

[0095]

[0096] That is:

[0097]

[0098] Solving for a * , b * yields the values:

[0099]

[0100] Where:

[0101] Through multiple experiments, the fitted straight line of the data within the same transmission period is During the transmission process, the fitted data at t = 1 and t = 30 are selected to represent the parameters for the entire time period.

[0102] In the embodiments of the present application, according to the importance degree of navigation data, it is divided into Class A, Class B, and Class C, and lossy and lossless compression strategies are adopted accordingly. This classified compression strategy is more refined and efficient, which can effectively reduce the storage and transmission burden of non-critical data while ensuring the security of key data. In particular, by adopting the compression method of piecewise linear fitting, the data compression efficiency is significantly improved. This method utilizes the linear change characteristics of navigation data within a short period of time (such as within 30 seconds). After linear fitting of the data, only the endpoints of the fitted line segments are retained, thus greatly reducing the number of data points to be transmitted. In addition, in terms of data integrity and accuracy, in the prior art, data loss or damage may occur during the compression process due to improper algorithm selection or unreasonable parameter settings, thus affecting data integrity. At the same time, lossy compression methods may also lead to a decrease in data accuracy, affecting subsequent data analysis and applications. However, in this embodiment, through classified compression and the adoption of lossless compression methods, the integrity and accuracy of Class A data (real-time navigation ship status safety data) are ensured. In addition, the piecewise linear fitting compression method achieves higher compression efficiency on the premise of ensuring data accuracy. Because navigation data has the characteristics of linear change within a short period of time, the main change trends and characteristic points of the data can be retained through linear fitting, thus ensuring the accuracy of the data during the compression process. In terms of security and adaptability, in the prior art, data may be illegally obtained or tampered with due to data leakage or security vulnerabilities during the transmission process during the compression process. At the same time, the compression algorithm and parameter settings are usually relatively fixed and difficult to adapt to the data requirements of different types and importance levels. However, in this embodiment, through classified compression and reducing the total amount of data transmission, the risk of data leakage is reduced, and the lossless compression method ensures the integrity and accuracy of key data, which is helpful for subsequent data verification and security checks.

[0103] The lightweight method proposed in the embodiments of the present application can also flexibly cope with different types of navigation record data and different compression requirements. This strong adaptability makes this method have a wider application prospect in the satellite communication environment.

[0104] To further ensure the security of transmitted data, before transmitting data, the embodiments of the present application also include encrypting the data to be transmitted. Specifically, this encryption process is implemented based on the encryption method of elliptic curve cryptography; during the encryption process, a random number is generated to participate in the calculation of elliptic curve points, which improves randomness and the difficulty of cracking. The encryption method based on elliptic curve cryptography (ECC) can significantly reduce the key length on the premise of ensuring the same security level. Compared with traditional encryption technologies such as RSA, the ECC algorithm can achieve similar security strength with a smaller key size, thus effectively reducing the occupation of storage space and the burden of transmission bandwidth. The following takes the example of node A sending a data M with a length of len to node B to specifically illustrate the encryption process, where the public and private key pairs of A are (P A , d A ), and those of B are (P B , d B ), P A and P B are public keys, and d A and d B are private keys. Public keys are used for encryption and signature verification, and private keys are used for decryption and signature.

[0105] ① Use a random number generator to generate a random number k ∈ [1, n - 1], where n is the order of the elliptic curve base point G. By integrating the random number generator with the elliptic curve point calculation, this not only improves the randomness of the encryption algorithm but also increases the complexity of cracking.

[0106] ② Calculate the elliptic curve point C1 = [k]G = (x1, y1), where both G and C1 are on the elliptic curve.

[0107] ③ Calculate the key string t = KDF(x2||y2, len) for symmetrically encrypting the plaintext data M, h ∈ [1, n - 1], and h is the cofactor of n. If S is not the point at infinity, then proceed to step ④, otherwise report an error and exit.

[0108] ④ Calculate [k]P B = (x2, y2).

[0109] ⑤ Calculate t = KDF(x2||y2, len), where KDF is a key derivation function. If t is all zeros, return to the first step. The calculation result of t is a bit string of length len. Using the key derivation function (KDF) to generate a key string of the same length as the plaintext based on the elliptic curve point coordinates not only ensures the randomness and unpredictability of the key but also can flexibly adapt to the encryption requirements of plaintexts of different lengths. Compared with the traditional fixed-length key generation method, the use of KDF improves the flexibility and adaptability of the encryption system. Through multiple error checking mechanisms, such as verifying the validity of the elliptic curve point and the non-zero nature of the key string generated by KDF, the accuracy and reliability of the encryption and decryption processes are ensured. These checking mechanisms effectively avoid encryption failures or decryption errors caused by calculation errors or data corruption, improving the stability and reliability of the entire encryption system.

[0110] ⑥ Calculate the encrypted data That is, the encrypted data obtained by performing an exclusive OR operation (⊕) on the plaintext M and the key t.

[0111] ⑦ Calculate the data integrity verification code C3 = Hash(x2||M||y2), where Hash is the SM3 cryptographic hash function. Introducing the SM3 cryptographic hash function to generate the data integrity verification code in the encryption process can verify whether the data has been tampered with or damaged during transmission, thus ensuring the authenticity and integrity of the data. Compared with existing data integrity verification methods, the SM3 cryptographic hash function has higher security and efficiency.

[0112] ⑧ Output the ciphertext C = C1||C2||C3.

[0113] In this encryption process, a hybrid encryption strategy is adopted, that is, first use asymmetric encryption to securely transmit the symmetric encryption key, and then use symmetric encryption to efficiently transmit the actual data. This strategy not only solves the security problem of key distribution but also ensures the efficiency of data transmission. Compared with traditional key distribution methods, the hybrid encryption strategy reduces the risk of key leakage and interception, ensuring the overall security of data transmission.

[0114] At the same time, the embodiment of this application also gives the decryption process of the ciphertext C = C1||C2||C3 by node B:

[0115] ① Convert C1 and check whether it is a point on the elliptic curve. If not, report an error and exit.

[0116] ② Calculate S = [h]G. If S is not the infinite point, then enter step (3); otherwise, report an error and exit.

[0117] ③ Calculate [d B C1 = (x2, y2).

[0118] ④ Calculate t = KDF(x2 || y2, len). If all t values are zero, report an error and exit.

[0119] ⑤ Calculate M′ is a candidate value of the plaintext M obtained through the decryption process and needs to be confirmed for its correctness through data integrity verification.

[0120] ⑥ Calculate u = Hash(x2 || M′ || y2). If u ≠ C3, report an error and exit. u is a candidate value of the data integrity verification code and is used to compare with C3 to verify the correctness of M'.

[0121] ⑦ Output the plaintext M′.

[0122] The encryption method and the corresponding decryption method proposed in the embodiments of the present application have the advantages of shorter key length, faster operation speed, and smaller storage space under the same security level. They can provide more efficient and secure data encryption and decryption services in satellite communication, effectively protecting sensitive information such as navigation records from being illegally obtained or tampered with.

[0123] Please refer to Figure 6 , the embodiments of the present application also provide a communication device 100, which mainly includes a data acquisition module 103, a control processing module 101, and a communication module 102. Among them, the data acquisition module 103 is used to acquire data to be transmitted; the control processing module 101 is used to send a check data packet to the aggregation node and adjust the current communication rate according to the confirmation information feedback by the aggregation node; the aggregation node is the data receiving destination; the communication module 102 is used to transmit the data to be transmitted to the aggregation node at the adjusted communication rate. In practical applications, the data acquisition module 103 is mainly connected to the voyage data recorder 115, and the voyage data recorder 115 is mainly used to record ship navigation data and status, including information such as the ship's navigation track, speed, position, rudder angle, and hull inclination. The communication module 102 can stably communicate with the satellite to realize the remote transmission of navigation data.

[0124] In one embodiment, the control processing module 101 of the communication device is further used to estimate the minimum channel traffic and configure the traffic transmission channel with the minimum channel traffic as a constraint condition, estimate the traffic of each channel, and complete the capacity allocation of each channel.

[0125] In one embodiment, the control processing 101 of the communication device further includes lightweight and encryption processing of the data to be transmitted.

[0126] When the communication module 102 is used to transmit navigation data, considering the reception and transmission effects of the signals of the communication device, it is selected to install the communication device on the top deck of the ship or other higher positions to reduce signal occlusion and interference. The voyage recorder records the ship's navigation data in real time during the voyage and packs and encapsulates it in a predetermined format and sends it to the connected communication device. The data after the communication device unpacks and decrypts it will be stored in the database of the ground station or remote server for subsequent analysis and query.

[0127] For the data caching and recovery function designed for the case of network disconnection, it is necessary to locally save the offline data. In one embodiment, the communication device 100 further includes a data storage module 104 for storing navigation data and cached data. The data storage module 104 should be a non-volatile memory with a high-speed communication interface, sufficient storage space, and miniaturization, and fully utilize the storage capacity through a file management system, preferably implemented using an SD card. Please refer to Figure 7 , which shows the process of the communication device implementing storage. The control processing module 101 divides the writing process into a data block write operation and a data stop operation. In the write operation, first send the CMD24 command to make the SD card enter the transmission state and wait for the return response. After obtaining the response, judge whether the current SD card transmission line is busy, and then start writing the data block. In the stop operation, the SD card verifies the CRC bit of the data block and returns a verification response to the control processing module 101; when it is determined that the data block format is correct, the control processing module 101 sends the CMD12 command to stop the data transmission, that is, the data writing is completed. In order to facilitate data management, make the offline data stored orderly in the form of files in the SD card, and at the same time introduce the FATFS file system in the communication device to achieve fast data reading and efficient capacity utilization.

[0128] In addition, the communication device 100 further includes a basic module or an expansion module to ensure normal operation. For example: the power module 105 provides electrical energy to ensure that all components of the satellite Internet communication device can obtain stable power supply to work properly; the satellite communication antenna 106 is used to receive and send satellite signals; the audio module 107 is used to process audio signals, play sounds, record sounds, and communicate with the audio device 108; the communication interface 109 is responsible for the communication device to connect to other external devices to achieve various functions; the WIFI antenna 110 is used for wireless local area network (WLAN) communication, which is responsible for receiving and sending wireless signals; the Bluetooth antenna 111 is responsible for short-distance wireless communication and data transmission between the communication device and other Bluetooth devices; the Beidou antenna 112 is used to receive the signals sent by Beidou satellites to determine information such as the position of the device; the human-computer interaction module 113 is responsible for realizing the interaction operation between people and the communication device; the additional expansion module 114 allows users to add additional functional modules or devices according to needs to expand the performance and functions of the communication device.

[0129] The communication device proposed in this embodiment utilizes satellite communication technology to achieve seamless global coverage, including remote sea areas, providing a stable and reliable communication connection for ships, enabling high-speed data transmission, greatly shortening the data transmission delay time, and supporting real-time updates of voyage records. At the same time, the device supports encrypted data transmission to ensure the security and integrity of voyage records during transmission. In addition, the communication device also has excellent device compatibility and flexibility, can be connected to a variety of on-board voyage record devices, and can be adjusted and optimized according to the specific needs of the ship and the navigation environment, thereby improving the adaptability and reliability of the device and ensuring that voyage records can be transmitted accurately and efficiently.

[0130] Referring to Figure 8 As shown, an electronic device 200 according to an embodiment of the present application includes: a memory 201 and a processor 202, and a computer program corresponding to the foregoing communication method is stored on the memory 201 and can be loaded and executed by the processor 202.

[0131] Figure 9 The structural diagram of a computer system of an electronic device suitable for implementing the embodiments of the present application is shown.

[0132] It should be noted that Figure 9 The computer system 300 of the electronic device shown is only an example and should not impose any limitations on the functions and usage scope of the embodiments of the present application.

[0133] As Figure 9 shown, the computer system 300 includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 302 or the program loaded from the storage section 308 into the random access memory (RAM) 303, such as executing the method described in the foregoing embodiment. In the RAM 303, various programs and data required for system operation are also stored. The CPU 301, ROM 302, and RAM 303 are connected to each other through a bus 304. The input / output (I / O) interface 305 is also connected to the bus 304.

[0134] The following components are connected to the I / O interface 305: an input section 306 including a keyboard, a mouse, etc.; an output section 307 including such as a cathode ray tube (CRT), a liquid crystal display (LCD), etc. and a speaker, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as required. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is mounted on the drive 310 as required so that a computer program read therefrom is installed into the storage section 308 as required.

[0135] Specifically, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product that includes a computer program carried on a computer-readable medium, and the computer program includes program codes for performing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 309, and / or installed from the removable medium 311. When the computer program is executed by a central processing unit (CPU) 301, various functions defined in the system of the present application are executed.

[0136] It should be noted that the computer-readable medium shown in the embodiments of the present application can be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of a computer-readable storage medium can include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium can be any tangible medium that contains or stores a program, and this program can be used by or in conjunction with an instruction execution system, apparatus, or device. In the present application, a computer-readable signal medium can include a data signal propagated in a baseband or as part of a carrier wave, in which computer-readable program code is carried. Such a propagated data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, and this computer-readable medium can send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on a computer-readable medium can be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0137] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present application. Among them, each block in the flowchart or block diagram can represent a module, a program segment, or a part of code, and the above module, program segment, or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than marked in the accompanying drawings. For example, two consecutive blocks shown can actually be executed substantially in parallel, and they can sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram or flowchart, and the combination of blocks in the block diagram or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0138] The units involved in the embodiments described in this application can be implemented in software or in hardware, and the described units can also be provided in a processor. Among them, the names of these units do not, in some cases, constitute a limitation on the unit itself.

[0139] As another aspect, the present application also provides a computer program product or a computer program. The computer program product or the computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the communication method described in the foregoing embodiments.

[0140] As another aspect, the present application also provides a computer-readable medium. The computer-readable medium can be included in the electronic device described in the foregoing embodiments; it can also exist alone without being assembled into the electronic device. The foregoing computer-readable medium carries one or more programs. When the one or more programs are executed by an electronic device, the electronic device implements the communication method described in the foregoing embodiments.

[0141] It should be noted that although several modules or units of a device for action execution are mentioned in the foregoing detailed description, such a division is not mandatory. In fact, according to the embodiments of the present application, the features and functions of the two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0142] Through the description of the above embodiments, those skilled in the art can easily understand that the example embodiments described herein can be implemented by software or by a combination of software and necessary hardware. Therefore, the technical solutions according to the embodiments of the present application can be embodied in the form of a software product. The software product can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiments of the present application.

[0143] For those of ordinary skill in the art, the specific meanings of the above terms can be understood according to specific circumstances; the accompanying drawings in the embodiments are used to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. Generally, the components of the embodiments of the present invention described and illustrated here can be arranged and designed in various different configurations.

[0144] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. A communication method, characterized in that: include: Sending a verification data packet to a sink node at a communication rate of a first baud rate, the sink node being a data receiving destination; Monitoring confirmation information returned by the aggregation node within a preset first time period, if no confirmation information is received within the preset first time period, gradually reducing the current communication rate and resending the verification data packet, repeatedly performing the communication rate reduction and verification data packet resending operations until the confirmation information is successfully received within the preset first time period, and using the communication rate at this time as the second baud rate; The data to be transmitted is transmitted to the sink node using the second baud rate.

2. The communication method according to claim 1, characterized in that: The first baud rate is the highest baud rate of the system, and the second baud rate is less than or equal to the first baud rate and greater than or equal to the lowest baud rate of the system.

3. The communication method according to claim 2, characterized in that: The length of the preset first time period is dynamically adjusted according to the current communication rate.

4. The communication method according to any one of claims 1 to 3, characterized in that: Also includes: After the preset second time period has passed, the second baud rate is re-determined and used as a new communication rate.

5. The communication method according to claim 1, characterized in that: The method further includes: transmitting the data to be transmitted to the aggregation node by adaptively allocating channel capacity, wherein the adaptively allocating channel capacity specifically includes: Estimate the minimum flow rate of the channel; Under a given communication capacity, the traffic transmission channel is configured with the minimum channel flow as the constraint condition; Estimate the traffic of each channel and complete the capacity allocation of each channel.

6. The communication method according to claim 5, characterized in that: A directed graph model is constructed based on the network structure, and the channel communication traffic is simulated as a queue with intersections to complete the channel minimum flow estimation.

7. The communication method according to claim 5, characterized in that: The estimating the flow of each channel and completing the capacity allocation of each channel specifically includes: Generate random data to form an initial solution space, wherein the random data represents the buffer length of each channel; Setting an objective function based on the estimated traffic of each channel and the configured traffic transmission channel; Iteratively optimize the solution space based on the objective function to determine the optimal solution; Channel capacity is allocated according to the optimal solution.

8. The communication method according to claim 7, characterized in that: The estimating the flow of each channel and completing the capacity allocation of each channel also includes: dynamically adjusting the allocation strategy of the channel capacity according to the real-time monitoring results and feedback of the channel.

9. The communication method according to claim 1 or 5, characterized in that: Before transferring data, it also includes: According to the importance of the data, the data to be transmitted is divided into Class A, Class B and Class C from high to low; For the data of type A to be transmitted, lossless compression is adopted; For the B-type data to be transmitted, the lossless compression mode and the lossy compression mode are dynamically switched according to the overall compression ratio; For the C type of data to be transmitted, a lossy compression method is used.

10. The communication method according to claim 9, characterized in that: The data is segmented into linear fits according to time periods, and only the endpoints of the fitted line segments are retained to complete the data compression.

11. The communication method according to claim 1 or 5, characterized in that: Before transmitting data, it also includes generating random numbers to participate in elliptic curve points, and encrypting the transmitted data based on the encryption method of elliptic curve cryptography.

12. A communication device, characterized in that: include: A data acquisition module, used to acquire data to be transmitted; A control processing module, used to send a verification data packet to a sink node and monitor the confirmation information fed back by the sink node to complete the adjustment of the current communication rate; the sink node is a data receiving destination; The communication module is used to transmit the data to be transmitted to the aggregation node using the adjusted communication rate.

13. The communication device according to claim 12, characterized in that: The control processing module is also used to estimate the minimum flow of the channel, configure the flow transmission channel based on the minimum flow of the channel as a constraint condition, estimate the flow of each channel and complete the capacity allocation of each channel.

14. An electronic device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program corresponding to the communication method according to any one of claims 1 to 11 that can be loaded by the processor and executed.

15. A computer-readable storage medium having computer program instructions stored thereon, characterized in that: When the program instructions are executed by a processor, they are used to implement a process corresponding to the communication method according to any one of claims 1 to 11.

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