Data transmission system and method for enhancing stability of computer network

Abstract

The invention relates to the technical field of data transmission, in particular to a data transmission system and method for enhancing computer network stability. Comprising the following steps of performing flow scheduling and multi-path transmission, setting data encryption and access control, implementing network topology dynamic adjustment, performing data transmission optimization, establishing security audit and log analysis, constructing baseband processing and error control, realizing cross-platform data synchronization and integration, and performing fault recovery and disaster recovery backup. Through a deep reinforcement learning algorithm and a multi-path transmission control protocol, the routing and priority of a data stream are intelligently adjusted, an encryption key which cannot be cracked is generated by using a quantum key distribution protocol and a continuous verification mechanism, and by combining network flow analysis and a machine learning algorithm, subnet division is dynamically adjusted, the size of a broadcast domain is reduced, and the transmission efficiency is improved. Fault diffusion is prevented and overall stability of the network is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of data transmission, and in particular to a data transmission system and method for enhancing the stability of a computer network. Background Art

[0002] Computer network refers to a computer system that connects multiple computers and their external devices with independent functions in different geographical locations through communication lines, and realizes resource sharing and information transmission under the management and coordination of network operating systems, network management software and network communication protocols. Its development has gone through a process from simple to complex, from low speed to high speed, and from local to global, which has greatly promoted the construction and development of the information society. With the continuous advancement of technology, computer networks have gradually spread to various fields such as business, education, and government, becoming an indispensable part of modern society. Today, computer networks have developed into a huge system including local area networks (LANs), metropolitan area networks (MANs), wide area networks (WANs) and the Internet.

[0003] Although computer networks have made great achievements, there are still problems of network congestion and delay in traditional data transmission. Due to the uneven distribution of network traffic and bursty data transmission, network congestion is easy to occur, which in turn causes data transmission delays and packet loss, affecting network performance. Traditional data transmission methods often lack effective encryption and authentication mechanisms, making them vulnerable to hacker attacks and data theft, threatening network security. Traditional network topology structures are often fixed and difficult to adapt to dynamic changes in network traffic, resulting in limited network scalability and performance. At the same time, fault recovery and disaster tolerance capabilities are weak: traditional networks often lack effective recovery and backup mechanisms when facing failures or catastrophic events, resulting in data loss and service interruptions.

[0004] In summary, it is necessary to propose a data transmission system and method for enhancing the stability of computer networks to solve the above problems. Summary of the invention

[0005] The object of the present invention is to provide a data transmission system and method for enhancing the stability of a computer network, so as to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A data transmission system for enhancing the stability of a computer network, comprising a traffic management module, a data encryption authentication module, a network topology adjustment module, a data transmission module, an audit log analysis module, a baseband processing error control module, a cross-platform data synchronization integration module, and a fault recovery and disaster recovery backup module;

[0008] The traffic management module is used for traffic scheduling and multi-path transmission;

[0009] The data encryption authentication module is used for key distribution and access control;

[0010] The network topology adjustment module is used for subnet division and fault prediction;

[0011] The data transmission module is used for read-write optimization and data decompression;

[0012] The audit log analysis module is used for security auditing and log analysis;

[0013] The baseband processing error control module is used for FPGA baseband processing and providing a modulation and coding scheme;

[0014] The cross-platform data synchronization integration module is used to provide a heterogeneous system data bridge and real-time push;

[0015] The fault recovery and disaster recovery backup module is used for fault recovery and disaster recovery backup.

[0016] Preferably, the traffic management module further includes a traffic scheduling unit and a multi-path transmission unit;

[0017] The traffic scheduling unit uses deep reinforcement learning (DRL) to dynamically adjust the routing and priority of data flows according to the real-time network load conditions, and is used to automatically monitor network congestion, predict future traffic trends, and adjust the distribution of data flows accordingly to minimize delays and packet loss rates.

[0018] The multipath transmission unit implements the Multipath Transmission Control Protocol (MPTCP), allowing multiple paths to simultaneously transmit the same data stream, and is used to automatically switch to other paths when a single connection fails or performance degrades, thereby enhancing the reliability and stability of transmission.

[0019] Preferably, the data encryption authentication module further includes a key distribution unit and an access control unit;

[0020] The key distribution unit is based on the quantum key distribution (QKD) protocol and is used to generate unbreakable encryption keys to protect confidentiality during data transmission and provide unprecedented security.

[0021] The access control unit implements continuous verification and the principle of least privilege, and is used to strictly verify each network access request to ensure that only authorized devices and users can access network resources, thereby reducing potential security threats.

[0022] Preferably, the network topology adjustment module further includes a subnet division unit and a fault prediction unit;

[0023] The subnet division unit combines network traffic analysis and machine learning algorithms to automatically and dynamically adjust subnet division according to network traffic distribution, reduce broadcast domain size, and improve network scalability and performance.

[0024] The fault prediction unit uses time series analysis and anomaly detection to predict network device failures in advance, automatically isolate faulty devices, prevent faults from spreading, and ensure overall network stability.

[0025] Preferably, the data transmission module further includes a read-write optimization unit and a data decompression unit;

[0026] The read / write optimization unit optimizes the I / O operation of the file system and adopts multi-threading or asynchronous I / O technology to increase data read / write speed and reduce transmission delay.

[0027] The data decompression unit uses LZ4 or ZSTD high-efficiency compression algorithm to reduce the size of transmitted data, reduce network bandwidth occupancy, and improve transmission efficiency.

[0028] Preferably, the audit log analysis module further includes a security audit unit and a log analysis unit;

[0029] The security audit unit monitors network traffic and user behavior in real time based on a behavioral analysis algorithm, identifies potential security threats, and records detailed security logs.

[0030] The log analysis unit combines natural language processing and pattern recognition technology to automatically analyze security logs, extract key information, and assist security administrators in quickly locating and handling security incidents.

[0031] Preferably, the baseband processing error control module further includes an FPGA baseband processing unit and a modulation and coding unit;

[0032] The FPGA baseband processing unit implements convolutional code encoding and Viterbi decoding, and is used to optimize baseband processing of data transmission at the hardware level, thereby improving the reliability and efficiency of data transmission.

[0033] The modulation and coding unit dynamically adjusts the modulation and coding scheme according to the channel quality, so as to adopt a more robust modulation and coding scheme when the channel condition is poor, thereby ensuring the stability of data transmission.

[0034] Preferably, the cross-platform data synchronization integration module further includes a heterogeneous system data bridge and a real-time push unit;

[0035] The heterogeneous system data bridge is used to support multiple data format conversions and interface adaptations, realize data synchronization integration among different systems, and ensure information consistency.

[0036] The real-time push unit uses WebSocket or MQTT protocol to provide real-time data update push service, reduce data delay and improve user experience.

[0037] Preferably, the fault recovery and disaster recovery backup module further comprises a fault recovery unit and a disaster recovery backup unit;

[0038] The fault recovery unit is based on the fault tree analysis technology and is used to automatically start the recovery process when a network failure occurs, so as to quickly restore the network service.

[0039] The disaster recovery backup unit combines the decentralized storage solution of blockchain technology to store data copies in multiple geographical locations to ensure data security and availability, and quickly restore data even when a catastrophic event occurs.

[0040] Based on the above system, the present invention also proposes a data transmission method for enhancing the stability of a computer network, comprising the following steps:

[0041] S1. Perform traffic scheduling and multi-path transmission;

[0042] S2. Set up data encryption and access control;

[0043] S3. Implement dynamic adjustment of network topology;

[0044] S4. Optimize data transmission;

[0045] S5. Establish security audit and log analysis;

[0046] S6. Build baseband processing and error control;

[0047] S7. Realize cross-platform data synchronization and integration;

[0048] S8. Perform fault recovery and disaster recovery backup.

[0049] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention intelligently adjusts the routing and priority of data streams through deep reinforcement learning algorithms and multi-path transmission control protocols, generates uncrackable encryption keys using quantum key distribution protocols and continuous verification mechanisms, dynamically adjusts subnet divisions in combination with network traffic analysis and machine learning algorithms, reduces the size of broadcast domains, prevents the spread of faults, and ensures the overall stability of the network; based on behavioral analysis algorithms and natural language processing technologies, it is capable of monitoring network traffic and user behavior in real time and identifying potential security threats; it improves the reliability and efficiency of data transmission by implementing hardware optimization technologies such as convolutional code encoding and Viterbi decoding; at the same time, it also supports multiple data format conversions and interface adaptations, realizes data synchronization and integration between different systems, and can quickly restore data and services when network failures or catastrophic events occur. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 A topological diagram of a data transmission system for enhancing computer network stability according to the present invention;

[0051] Figure 2 The present invention is a flow chart of a data transmission method for enhancing computer network stability. DETAILED DESCRIPTION

[0052] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0053] Example 1

[0054] See also Figure 1 , the present invention proposes a data transmission system for enhancing the stability of a computer network, the system includes a traffic management module, a data encryption authentication module, a network topology adjustment module, a data transmission module, an audit log analysis module, a baseband processing error control module, a cross-platform data synchronization integration module, and a fault recovery and disaster recovery backup module;

[0055] Among them, it should be noted that this system performs traffic scheduling and multi-path transmission through the traffic management module, this system performs key distribution and access control through the data encryption and authentication module, this system performs subnet division and fault prediction through the network topology adjustment module, this system performs read and write optimization and data decompression through the data transmission module, this system performs security auditing and log analysis through the audit log analysis module, this system performs FPGA baseband processing and provides modulation and coding schemes through the baseband processing error control module, this system provides heterogeneous system data bridge and real-time push through the cross-platform data synchronization integration module, and this system uses the fault recovery and disaster recovery backup module for fault recovery and disaster recovery backup.

[0056] In this embodiment, it should also be noted that the traffic management module of the system also includes a traffic scheduling unit and a multipath transmission unit. The traffic scheduling unit uses deep reinforcement learning (DRL) to dynamically adjust the routing and priority of the data flow according to the real-time load status of the network, and is used to automatically monitor network congestion, predict future traffic trends, and adjust the distribution of data flows accordingly to minimize delays and packet loss rates.

[0057] The multipath transmission unit implements the Multipath Transmission Control Protocol (MPTCP), allowing multiple paths to simultaneously transmit the same data stream, and is used to automatically switch to other paths when a single connection fails or performance degrades, thereby enhancing the reliability and stability of transmission.

[0058] In this embodiment, it should also be noted that the data encryption authentication module of the system also includes a key distribution unit and an access control unit. The key distribution unit is based on the quantum key distribution (QKD) protocol and is used to generate an unbreakable encryption key to protect the confidentiality of data during transmission, providing unprecedented security.

[0059] The access control unit implements continuous verification and the principle of least privilege, and is used to strictly verify each network access request to ensure that only authorized devices and users can access network resources, thereby reducing potential security threats.

[0060] In this embodiment, it should also be noted that the network topology adjustment module of the system also includes a subnet division unit and a fault prediction unit. The subnet division unit combines network traffic analysis and machine learning algorithms to automatically and dynamically adjust the subnet division according to the network traffic distribution, reduce the size of the broadcast domain, and improve the network scalability and performance.

[0061] The fault prediction unit uses time series analysis and anomaly detection to predict network device failures in advance, automatically isolate faulty devices, prevent faults from spreading, and ensure overall network stability.

[0062] In this embodiment, it should also be noted that the data transmission module of the system also includes a read-write optimization unit and a data decompression unit. The read-write optimization unit optimizes the I / O operation of the file system and adopts multi-threading or asynchronous I / O technology to improve data reading and writing speed and reduce transmission delay.

[0063] The data decompression unit uses LZ4 or ZSTD high-efficiency compression algorithm to reduce the size of transmitted data, reduce network bandwidth occupancy, and improve transmission efficiency.

[0064] In this embodiment, it should also be noted that the audit log analysis module of the system also includes a security audit unit and a log analysis unit. The security audit unit monitors network traffic and user behavior in real time based on a behavioral analysis algorithm, identifies potential security threats, and records detailed security logs.

[0065] The log analysis unit combines natural language processing and pattern recognition technology to automatically analyze security logs, extract key information, and assist security administrators in quickly locating and handling security incidents.

[0066] In this embodiment, it should also be noted that the baseband processing error control module of the system also includes an FPGA baseband processing unit and a modulation coding unit. The FPGA baseband processing unit implements convolutional code encoding and Viterbi decoding, which is used to optimize the baseband processing of data transmission at the hardware level and improve the reliability and efficiency of data transmission.

[0067] The modulation and coding unit dynamically adjusts the modulation and coding scheme according to the channel quality, so as to adopt a more robust modulation and coding scheme when the channel condition is poor, thereby ensuring the stability of data transmission.

[0068] In this embodiment, it should also be noted that the cross-platform data synchronization integration module of the system also includes a heterogeneous system data bridge and a real-time push unit. The heterogeneous system data bridge is used to support multiple data format conversions and interface adaptations, realize data synchronization integration between different systems, and ensure information consistency.

[0069] The real-time push unit uses WebSocket or MQTT protocol to provide real-time data update push service, reduce data delay and improve user experience.

[0070] In this embodiment, it should also be noted that the fault recovery and disaster recovery backup module of the system also includes a fault recovery unit and a disaster recovery backup unit. The fault recovery unit is based on fault tree analysis technology and is used to automatically start the recovery process when a network failure occurs to quickly restore network services.

[0071] The disaster recovery backup unit combines the decentralized storage solution of blockchain technology to store data copies in multiple geographical locations to ensure data security and availability, and quickly restore data even when a catastrophic event occurs.

[0072] Example 2

[0073] See also Figure 2 In actual application, based on the above system, the present invention also proposes a data transmission method for enhancing the stability of a computer network, which specifically includes the following steps:

[0074] S1. Perform traffic scheduling and multi-path transmission:

[0075] First, a deep reinforcement learning (DRL) algorithm is used to dynamically adjust the routing and priority of data flows according to the real-time load conditions of the network;

[0076] This step aims to automatically monitor network congestion, predict future traffic trends, and intelligently distribute data flows accordingly to minimize latency and packet loss;

[0077] At the same time, the Multipath Transmission Control Protocol (MPTCP) is implemented to allow data to be transmitted simultaneously through multiple paths;

[0078] When a connection fails or performance degrades, it automatically switches to other paths to enhance transmission reliability and stability;

[0079] S2.Data encryption and access control:

[0080] Next, the quantum key distribution (QKD) protocol is used to generate unbreakable encryption keys to protect the confidentiality of data during transmission, providing a high level of security;

[0081] Implement continuous verification and the principle of least privilege to strictly verify each network access request to ensure that only authorized devices and users can access network resources, thereby reducing potential security threats;

[0082] S3. Dynamic adjustment of network topology:

[0083] Combine network traffic analysis and machine learning algorithms to dynamically adjust subnet divisions based on the distribution of network traffic;

[0084] This step is intended to reduce the size of the broadcast domain and improve the scalability and performance of the network;

[0085] Use time series analysis and anomaly detection technology to predict network device failures and automatically isolate faulty devices to prevent the spread of failures and ensure the overall stability of the network;

[0086] S4. Data transmission optimization:

[0087] Optimize the I / O operation of the file system and use multi-threading or asynchronous I / O technology to increase the data reading and writing speed and reduce transmission delay;

[0088] Use efficient compression algorithms such as LZ4 or ZSTD to reduce the size of transmitted data and reduce network bandwidth usage, thereby improving transmission efficiency;

[0089] S5. Security audit and log analysis:

[0090] Monitor network traffic and user behavior in real time based on behavioral analysis algorithms, identify potential security threats, and record detailed security logs;

[0091] Combine natural language processing and pattern recognition technology to automatically analyze security logs, extract key information, and assist security administrators in quickly locating and handling security incidents;

[0092] S6. Baseband processing and error control:

[0093] Implement convolutional coding and Viterbi decoding at the hardware level to optimize baseband processing of data transmission and improve the reliability and efficiency of data transmission;

[0094] Dynamically adjust the modulation and coding scheme according to the channel quality to ensure that a more robust modulation and coding scheme is used when the channel conditions are poor, thereby ensuring the stability of data transmission;

[0095] S7. Cross-platform data synchronization and integration:

[0096] Supports conversion of multiple data formats and interface adaptation to achieve data synchronization and integration between different systems and ensure information consistency;

[0097] Use WebSocket or MQTT protocol to provide real-time data update push service to reduce data delay and improve user experience;

[0098] S8. Fault recovery and disaster recovery backup:

[0099] Based on fault tree analysis technology, the recovery process is automatically started when a network failure occurs to quickly restore network services;

[0100] A decentralized storage solution that combines blockchain technology to store data copies in multiple geographical locations to ensure data security and availability;

[0101] Even in the event of a catastrophic event, data can be quickly restored.

[0102] In summary, the present invention uses deep reinforcement learning algorithms and multi-path transmission control protocols to intelligently adjust the routing and priority of data streams, utilizes quantum key distribution protocols and continuous verification mechanisms to generate uncrackable encryption keys, combines network traffic analysis and machine learning algorithms to dynamically adjust subnet divisions, reduce broadcast domain sizes, prevent fault spread, and ensure overall network stability. Based on behavior analysis algorithms and natural language processing technology, it can monitor network traffic and user behavior in real time and identify potential security threats. By implementing hardware optimization technologies such as convolutional code encoding and Viterbi decoding, it improves the reliability and efficiency of data transmission. At the same time, it also supports multiple data format conversions and interface adaptations, realizes data synchronization and integration between different systems, and can quickly restore data and services when network failures or catastrophic events occur.

[0103] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A data transmission system for enhancing the stability of a computer network, characterized in that: It includes traffic management module, data encryption and authentication module, network topology adjustment module, data transmission module, audit log analysis module, baseband processing error control module, cross-platform data synchronization integration module, and fault recovery and disaster recovery backup module. The traffic management module is used for traffic scheduling and multi-path transmission; The data encryption authentication module is used for key distribution and access control; The network topology adjustment module is used for subnet division and fault prediction; The data transmission module is used for read-write optimization and data decompression; The audit log analysis module is used for security auditing and log analysis; The baseband processing error control module is used for FPGA baseband processing and providing a modulation and coding scheme; The cross-platform data synchronization integration module is used to provide a heterogeneous system data bridge and real-time push; The fault recovery and disaster recovery backup module is used for fault recovery and disaster recovery backup.

2. A data transmission system for enhancing the stability of a computer network according to claim 1, characterized in that: The traffic management module also includes a traffic scheduling unit and a multi-path transmission unit; The traffic scheduling unit uses deep reinforcement learning (DRL) to dynamically adjust the routing and priority of data flows according to the real-time network load conditions, and is used to automatically monitor network congestion, predict future traffic trends, and adjust the distribution of data flows accordingly to minimize delays and packet loss rates. The multipath transmission unit implements the Multipath Transmission Control Protocol (MPTCP), allowing multiple paths to simultaneously transmit the same data stream, and is used to automatically switch to other paths when a single connection fails or performance degrades, thereby enhancing the reliability and stability of transmission.

3. A data transmission system for enhancing computer network stability according to claim 2, characterized in that: The data encryption authentication module also includes a key distribution unit and an access control unit; The key distribution unit is based on the quantum key distribution (QKD) protocol and is used to generate unbreakable encryption keys to protect confidentiality during data transmission and provide unprecedented security. The access control unit implements continuous verification and the principle of least privilege, and is used to strictly verify each network access request to ensure that only authorized devices and users can access network resources, thereby reducing potential security threats.

4. A data transmission system for enhancing the stability of a computer network according to claim 3, characterized in that: The network topology adjustment module also includes a subnet division unit and a fault prediction unit; The subnet division unit combines network traffic analysis and machine learning algorithms to automatically and dynamically adjust subnet division according to network traffic distribution, reduce broadcast domain size, and improve network scalability and performance. The fault prediction unit uses time series analysis and anomaly detection to predict network device failures in advance, automatically isolate faulty devices, prevent the spread of faults, and ensure overall network stability.

5. A data transmission system for enhancing computer network stability according to claim 4, characterized in that: The data transmission module also includes a read-write optimization unit and a data decompression unit; The read / write optimization unit optimizes the I / O operation of the file system and adopts multi-threading or asynchronous I / O technology to increase data read / write speed and reduce transmission delay. The data decompression unit uses LZ4 or ZSTD high-efficiency compression algorithm to reduce the size of transmitted data, reduce network bandwidth occupancy, and improve transmission efficiency.

6. A data transmission system for enhancing the stability of a computer network according to claim 5, characterized in that: The audit log analysis module also includes a security audit unit and a log analysis unit; The security audit unit monitors network traffic and user behavior in real time based on a behavioral analysis algorithm, identifies potential security threats, and records detailed security logs. The log analysis unit combines natural language processing and pattern recognition technology to automatically analyze security logs, extract key information, and assist security administrators in quickly locating and handling security incidents.

7. A data transmission system for enhancing computer network stability according to claim 6, characterized in that: The baseband processing error control module also includes an FPGA baseband processing unit and a modulation and coding unit; The FPGA baseband processing unit implements convolutional code encoding and Viterbi decoding, and is used to optimize baseband processing of data transmission at the hardware level, thereby improving the reliability and efficiency of data transmission. The modulation and coding unit dynamically adjusts the modulation and coding scheme according to the channel quality, so as to adopt a more robust modulation and coding scheme when the channel condition is poor, thereby ensuring the stability of data transmission.

8. A data transmission system for enhancing computer network stability according to claim 7, characterized in that: The cross-platform data synchronization integration module also includes a heterogeneous system data bridge and a real-time push unit; The heterogeneous system data bridge is used to support multiple data format conversions and interface adaptations, realize data synchronization integration among different systems, and ensure information consistency. The real-time push unit uses WebSocket or MQTT protocol to provide real-time data update push service, reduce data delay and improve user experience.

9. A data transmission system for enhancing computer network stability according to claim 8, characterized in that: The fault recovery and disaster recovery backup module also includes a fault recovery unit and a disaster recovery backup unit; The fault recovery unit is based on the fault tree analysis technology and is used to automatically start the recovery process when a network failure occurs, so as to quickly restore the network service. The disaster recovery backup unit combines the decentralized storage solution of blockchain technology to store data copies in multiple geographical locations to ensure data security and availability, and quickly restore data even when a catastrophic event occurs.

10. A data transmission method for enhancing the stability of a computer network, according to a data transmission system for enhancing the stability of a computer network according to any one of claims 1 to 9, characterized in that , including the following steps: S1. Perform traffic scheduling and multi-path transmission; S2. Set up data encryption and access control; S3. Implement dynamic adjustment of network topology; S4. Optimize data transmission; S5. Establish security audit and log analysis; S6. Build baseband processing and error control; S7. Realize cross-platform data synchronization and integration; S8. Perform fault recovery and disaster recovery backup.

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