Computer wireless network operation monitoring system and method

Abstract

The present invention discloses a computer wireless network operation supervision system and method, which relates to the field of network security technology. The system includes collecting network status data; constructing a QUBO model and generating a network spectrum allocation policy matrix through a quantum annealing machine; parsing the network spectrum allocation policy matrix to generate a network base station radio frequency parameter instruction set and a network terminal access policy table, and adjusting the network flow table rules through an SDN controller; comparing the expected configuration network parameters with the new network status data to locate the root cause of network anomalies; screening out redundant links in the network, optimizing the topology using an ant colony optimization algorithm and updating the spectrum allocation policy matrix, isolating faulty nodes, and reconstructing topological connections. The present invention improves computer wireless network operation supervision through a quantum annealing machine. In terms of spectrum resource allocation, the quantum annealing machine optimizes frequency allocation and transmit power by constructing a QUBO model.

Description

Technical Field

[0001] The present invention relates to the technical field of network security, and in particular to a computer wireless network operation supervision system and method. Background Art

[0002] In the field of computer wireless network operation supervision, advances in computer technology have improved the intelligence level of network performance management. With the promotion of 5G and Wi-Fi 6 technologies, the diversified deployment and high-density characteristics of network equipment have placed higher requirements on the efficient allocation of spectrum resources. In existing literature, dynamic spectrum management based on software-defined networks (SDN) has achieved real-time monitoring of network operation status. For example, it optimizes channel allocation through interference relationship graphs to reduce co-channel interference. In addition, the application of quantum computing is gradually emerging. Using quantum annealing machines to solve the QUBO model can accelerate the calculation of complex spectrum optimization problems, providing a new path for improving channel quality and traffic allocation efficiency.

[0003] However, existing technologies still have shortcomings in practical applications, especially in highly dynamic, multi-interference wireless network environments. First, traditional network status collection mostly relies on a single type of probe, lacking differentiated designs for base stations, access points and terminal devices, resulting in insufficient data collection accuracy and real-time performance, making it difficult to fully reflect the network operation status. Secondly, although spectrum allocation optimization has introduced quantum computing, its adaptive adjustment capability for network topology is limited, especially in terms of fault node isolation and redundant link utilization. There is a lack of solutions, which limits the network performance optimization effect. In addition, existing methods have a slow response speed in the closed-loop management of anomaly detection and repair, and cannot effectively deal with sudden interference or equipment failures. Summary of the Invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a computer wireless network operation supervision method to solve the problem of limited network performance optimization effect.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides a method for supervising the operation of a computer wireless network, which includes collecting network status data, the network status data including spectrum occupancy, channel quality, topological connection, traffic load and network equipment energy consumption, and encrypting and transmitting it to a central server; constructing a QUBO model, and generating a network spectrum allocation policy matrix through a quantum annealing machine; parsing the network spectrum allocation policy matrix, generating a network base station radio frequency parameter instruction set and a network terminal access policy table, and adjusting the network flow table rules through an SDN controller; re-collecting network status data, comparing the expected configuration network parameters with the new network status data, verifying whether the network operation status meets expectations and detecting network anomalies, locating the root cause of the network anomalies, and generating an anomaly analysis report; screening out redundant links in the network, using an ant colony optimization algorithm to optimize the topology structure and update the spectrum allocation policy matrix, isolating faulty nodes and reconstructing topological connections.

[0008] As a preferred solution of the computer wireless network operation supervision method of the present invention, wherein: the QUBO model is constructed and the network spectrum allocation strategy matrix is ​​generated by quantum annealing. The specific steps are:

[0009] Construct a network interference relationship graph based on topological connectivity, spectrum status, and channel quality;

[0010] Set optimization goals and constraints for the network interference relationship graph;

[0011] Based on the optimization objectives and constraints, a QUBO model is constructed;

[0012] Upload the QUBO model to the quantum annealer through the API interface, set the solution parameters of the quantum annealer, and obtain the optimal solution;

[0013] The quantum annealer solves the frequency allocation and transmission power of network devices based on the optimization objectives and constraints in the QUBO model;

[0014] Use constraints to check frequency allocation and transmit power. If the constraints are violated, adjust the weight of the interference relationship graph and recalculate;

[0015] The frequency allocation and transmit power that have been verified to be compliant are integrated into a spectrum allocation strategy matrix.

[0016] As a preferred solution of the computer wireless network operation supervision method of the present invention, wherein: said parsing of the network spectrum allocation strategy matrix refers to extracting the configuration network parameters of the network devices through the central server;

[0017] The network flow table rules are generated based on traffic load, combined with allocated frequency bands, transmit power, and effective time windows.

[0018] As a preferred solution of the computer wireless network operation supervision method described in the present invention, the root cause of the positioning network abnormality is determined by weight analysis, dynamically correlating the interference intensity, poor channel quality and network abnormality duration in the network interference relationship diagram, and sorting priorities.

[0019] As a preferred solution of the computer wireless network operation supervision method described in the present invention, the method of screening out redundant links in the network refers to identifying all network connection paths from the topological connection, extracting pre-configured backup connections not used by the main link, forming a redundant link candidate list, and combining the abnormality analysis report to indicate the network fault device and the root cause, and screening out redundant links to replace the failed main link.

[0020] As a preferred solution of the computer wireless network operation supervision method described in the present invention, the use of the ant colony optimization algorithm to optimize the topology structure and update the spectrum allocation strategy matrix refers to using the ant colony optimization algorithm to generate network performance indicators as fitness functions based on network status data, search for the optimal topology structure, repair abnormal networks, and update the spectrum allocation strategy matrix.

[0021] As a preferred solution of the computer wireless network operation supervision method described in the present invention, wherein: the isolating faulty nodes and reconstructing the topological connections refers to reconfiguring network parameters and topological connections according to the updated spectrum allocation strategy matrix, marking faulty network devices and adjusting the topological connections, and isolating network faulty nodes.

[0022] In a second aspect, the present invention provides a computer wireless network operation supervision system, comprising: an acquisition module for collecting network status data, wherein the network status data includes spectrum occupancy, channel quality, topological connection, traffic load and network equipment energy consumption, and encrypting and transmitting the data to a central server; a generation module for constructing a QUBO model, and generating a network spectrum allocation policy matrix through a quantum annealing machine; an adjustment module for parsing the network spectrum allocation policy matrix, generating a network base station radio frequency parameter instruction set and a network terminal access policy table, and adjusting the network flow table rules through an SDN controller; an anomaly module for re-collecting network status data, comparing the expected configuration network parameters with the new network status data, verifying whether the network operation status meets expectations and detecting network anomalies, locating the root cause of the network anomaly, and generating an anomaly analysis report; an update module for screening out redundant links in the network, optimizing the topology structure using an ant colony optimization algorithm and updating the spectrum allocation policy matrix, isolating faulty nodes and reconstructing topological connections.

[0023] In a third aspect, the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, any step of the computer wireless network operation supervision method as described in the first aspect of the present invention is implemented.

[0024] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements any step of the computer wireless network operation supervision method as described in the first aspect of the present invention.

[0025] The beneficial effects of the present invention are as follows: the present invention improves the operation supervision of computer wireless networks through a quantum annealing machine. In terms of spectrum resource allocation, the quantum annealing machine optimizes frequency allocation and transmission power by constructing a QUBO model solution. Compared with the traditional simulated annealing algorithm with a calculation time of several seconds, it achieves near real-time dynamic adjustment, meeting the rapid response requirements in high-density network environments. The quantum annealing machine accurately quantifies the interference intensity of the same frequency and adjacent frequencies, achieving global interference minimization and channel quality index maximization. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0027] Figure 1 This is a flow chart of the computer wireless network operation supervision method in Example 1.

[0028] Figure 2 Flowchart for constructing and solving the QUBO model in Example 1.

[0029] Figure 3 This is a schematic diagram of policy analysis and network adjustment in Example 1.

[0030] Figure 4 This is a flowchart of exception handling and topology optimization in Example 1. DETAILED DESCRIPTION

[0031] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0032] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0033] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive of other embodiments.

[0034] Example 1, reference Figures 1 to 4 , which is the first embodiment of the present invention, provides a computer wireless network operation supervision method, comprising the following steps:

[0035] S1. Collect network status data and encrypt and transmit it to the central server.

[0036] Furthermore, dedicated data collection probes are deployed in network base stations, wireless access points (APs), and network terminal devices;

[0037] The network base station deploys hardware-level probes, which support high-frequency RF signal scanning (such as 5GHz and 6GHz);

[0038] Deploy software probes for wireless access points (APs) and network terminal devices, which are integrated into the network device firmware;

[0039] When the collection probe is started, it registers with the central server to obtain a unique identifier and collection parameters (such as frequency and encryption key);

[0040] Set the fixed collection frequency to 10 times per second, and instantly increase it to 50 times per second in the event of an emergency;

[0041] Collect network status data through acquisition probes, including spectrum status, channel quality, topology connection, traffic load, and network device energy consumption;

[0042] The spectrum status includes the signal strength (unit: dBm) and noise interference value (unit: dBm) of the 2.4GHz, 5GHz, and 6GHz frequency bands;

[0043] Channel quality includes signal-to-noise ratio (unit: dB), bit error rate (unit: 10 -6 ), channel quality index (0-100);

[0044] Topological connections include device ID, IP address, physical location coordinates, and adjacency table;

[0045] Traffic load includes peak upstream and downstream traffic (unit: Mbps) and average packet queue delay (unit: ms);

[0046] Network equipment energy consumption includes wireless network card power consumption (unit: mW) and terminal battery remaining power (percentage);

[0047] The clocks of all collection probes are aligned through a time synchronization protocol to ensure the time accuracy of the collected network status data is down to the microsecond level.

[0048] Integrate the collected network status data into a unified JSON format and encapsulate it through hash values ​​to generate a global network status data packet;

[0049] The hash value is calculated using SHA-256;

[0050] Use the TLS encryption protocol to establish an end-to-end secure channel and transmit global network status data packets to the central server.

[0051] S2. Build the QUBO model and use the quantum annealing machine to quickly solve and generate the network spectrum allocation strategy matrix.

[0052] Furthermore, the central server receives the global network status data packet and verifies the hash value of the global network status data packet to ensure integrity and no tampering;

[0053] Construct a network interference relationship graph based on topological connectivity, spectrum status, and channel quality;

[0054] The central server parses the global network status data packet and calculates the distance (in meters) between network devices based on the physical location coordinates in the topological connection;

[0055] Combined with the spectrum status, identify the use of co-frequency or adjacent frequency channels and quantify the interference intensity (reduction of signal-to-noise ratio, unit: dB);

[0056] Using the channel quality index as the weight of the auxiliary interference relationship graph, a weighted interference relationship graph is generated, where the nodes are network base stations, wireless access points, and network terminal devices, and the edges represent the degree of interference;

[0057] The expression of the interference relationship graph weight is:

[0058]

[0059] Among them, W is the interference relationship graph weight, which represents the interference degree of a certain connection (edge) in the network, ranging from 0 to 1, where 0 represents no interference, indicating the best network connection state, and 1 represents maximum interference, indicating that the network connection is severely affected. CQI is the channel quality index (0-100), which is a commonly used indicator in wireless communications, usually measured by network equipment, reflecting the reliability and transmission capacity of the channel quality. 0 represents the worst channel quality, and 100 represents the best channel quality. ΔSNR is the signal-to-noise ratio reduction value caused by interference (unit: dB). max The maximum expected signal-to-noise ratio reduction, expressed in dB, is a reference threshold set based on specific operations, indicating the maximum level of interference that may occur. The reference threshold can be set to 20 dB (indoor Wi-Fi) or 30 dB (outdoor cellular networks), depending on the actual scenario.

[0060] If ΔSNR>ΔSNR max , resulting in W>1, then W is limited to 1 to ensure the rationality of the weight of the interference relationship graph;

[0061] Set optimization goals and constraints for the network interference relationship graph;

[0062] The optimization goal is:

[0063] Minimize interference and reduce the total weight of the interference relationship graph to improve channel quality;

[0064] Maximize spectrum utilization and improve the average value of channel quality index within the frequency band;

[0065] The constraints are:

[0066] Use acquisition probes to set the supported frequency band range for network device hardware;

[0067] Set the network transmit power limit as a configurable network parameter (the default values ​​are ≤30dBm for network base stations, ≤20dBm for wireless access points, and ≤10dBm for network terminal devices).

[0068] Set energy consumption limits for network terminals (power consumption should not exceed 10% of the current power of the network device);

[0069] Based on the optimization objectives and constraints, a QUBO (quadratic unconstrained binary optimization) model is constructed;

[0070] Upload the QUBO model to the quantum annealer through the API interface;

[0071] The quantum exchanger solves the optimal spectrum allocation scheme for network devices based on the optimization objectives and constraints in the QUBO model, such as obtaining the optimal frequency allocation and transmit power to optimize network performance.

[0072] Set the quantum annealing machine's solution parameters: the number of samples is 1000, and the annealing time is 20 microseconds to ensure a balance between accuracy and efficiency;

[0073] After receiving the QUBO model, the quantum annealer calculates the frequency allocation and transmit power of each network device within 100ms based on the optimization objectives and constraints, and returns the results to the central server. If it times out, it switches to the backup traditional simulated annealing algorithm;

[0074] Use constraints to check frequency allocation and transmit power. If a constraint is violated (e.g., power exceeds the limit), adjust the weight of the interference relationship graph and recalculate it. This is repeated up to three times to ensure that the constraints are met while also approaching the optimization goal.

[0075] Integrate the verified compliant frequency allocation and transmit power into a spectrum allocation strategy matrix;

[0076] A verified hash value is added to the spectrum allocation strategy matrix, and it is encapsulated and stored in the central server through the TLS encryption protocol.

[0077] S3. Analyze the network spectrum allocation strategy matrix, generate the network base station radio frequency parameter instruction set and the network terminal access strategy table, and adjust the network flow table rules through the SDN controller.

[0078] Furthermore, after receiving the spectrum allocation policy matrix, the central server verifies the hash value of the spectrum allocation policy matrix to ensure that the data has not been tampered with or damaged during transmission. If the verification fails, an error log is recorded and the spectrum allocation policy matrix is ​​regenerated.

[0079] The central server parses the spectrum allocation strategy matrix and extracts the configuration network parameters of each network device; the configuration network parameters are the allocated frequency band, transmit power, and effective time window;

[0080] Classify the configured network parameters by network device type (network base station, wireless access point, network terminal device) and generate a device configuration list;

[0081] Generates a set of radio frequency parameter instructions, including center frequency, bandwidth, and transmit power, based on the allocated frequency bands and transmit power of network base stations in the spectrum allocation strategy matrix.

[0082] The center frequency is calculated based on the frequency band allocation, the bandwidth is set according to the frequency band standard (default value), and the transmit power directly uses the value in the spectrum allocation strategy matrix;

[0083] Generate a network terminal access policy table based on the allocation data of wireless access points and network terminal devices in the spectrum allocation policy matrix;

[0084] The network terminal access policy table includes priority, list of allowed access frequency bands and transmit power limit;

[0085] Priorities are set based on traffic load and channel quality index. For example, high-load network devices have a priority of 1, and low-load network devices have a priority of 3. The list of frequency bands allowed for access is the list of available frequency bands. The transmit power limit directly references the value in the spectrum allocation strategy matrix.

[0086] Use the NETCONF protocol to push radio parameter instruction sets to network base stations through a secure channel;

[0087] Verify the online status of the network base station before pushing. If it is offline, record it in the central server operation log and mark it as waiting for retry;

[0088] After the push, the network base station receives the configuration and confirms the response. If it fails, it rolls back to the last stable configuration. The last stable configuration is the set of RF parameter instructions that the network base station has successfully applied and is running normally before the current configuration is pushed.

[0089] Use the CoAP protocol to send the network terminal access policy table to the wireless access point and network terminal device through the DTLS encrypted channel;

[0090] For wireless access points, update the access control list in the wireless access point firmware to restrict network terminal devices from accessing designated frequency bands;

[0091] For network terminals, the software probe receives the network terminal access policy table and adjusts the wireless network card parameters, including frequency and power, and sets a timeout of 5 seconds. If no confirmation is received, it will retry up to 3 times;

[0092] Generate network flow table rules based on traffic load and combined with the allocated frequency band, transmit power, and effective time window in the configured network parameters;

[0093] Network flow table rules include matching conditions and action instructions; matching conditions include source IP address, destination IP address, traffic type, priority, and time window; action instructions include forwarding path and queue allocation;

[0094] The SDN controller issues and adjusts network flow table rules to optimize traffic distribution between network devices and adjust network flow table rules;

[0095] Dynamically adjust network flow table rules based on the effective time window of the spectrum allocation policy matrix to allocate low-latency paths for video streams or real-time applications;

[0096] Optimize traffic distribution between network base stations and wireless access points based on the allocated frequency bands and traffic loads in the spectrum allocation strategy matrix;

[0097] Record the configurations issued by the spectrum allocation strategy matrix and generate network parameter adjustment logs;

[0098] The network parameter adjustment log includes the effective time, target device list and operation verification code;

[0099] The effective time is the specific timestamp of successful configuration (accurate to milliseconds); the target device list is all affected network devices and their new network parameters; the operation check code is the generated hash value;

[0100] If the configuration fails to be delivered, for example, the network base station rejects the configured network parameters or the network terminal device does not respond, the network parameter adjustment log is rolled back to the last stable configuration;

[0101] The previous stable configuration refers to the configuration network parameters that have been successfully applied and operated normally by the network device before the current push, and is stored locally by the central server;

[0102] The reason for the delivery failure is recorded in the central server operation log, such as power exceeding the hardware limit, triggering recalculation and allocation.

[0103] S4. Re-collect network status data, compare the expected configuration network parameters with the new network status data, verify whether the network operation status meets expectations and detect network anomalies, locate the root cause of the network anomaly, and generate an anomaly analysis report.

[0104] Furthermore, network status data is recollected to verify whether the network operation status after the configuration is delivered meets expectations and detect any anomalies;

[0105] After the spectrum allocation strategy matrix takes effect, all acquisition probes maintain a basic acquisition frequency of 10 times per second. If the spectrum allocation strategy matrix adjustment causes a change in network status (such as a decrease in the channel quality index by more than 20%), the acquisition frequency will be automatically increased to 50 times per second.

[0106] A new policy validity identifier is added to the re-collected network status data to mark whether the currently collected network status data is within the validity time window of the spectrum allocation policy matrix;

[0107] The central server compares the expected configuration network parameters in the network parameter adjustment log with the re-collected network status data to detect whether there are any abnormalities in the network;

[0108] The expected configuration network parameters are the state that the network device should reach in the network parameter adjustment log;

[0109] Abnormal conditions include spectrum abnormalities, power abnormalities, channel quality abnormalities, and traffic abnormalities;

[0110] Spectrum anomaly means that the actual frequency band or center frequency does not match the configured network parameters;

[0111] Power anomaly means the actual transmit power exceeds the configured network parameters or hardware upper limit (network base station ≤ 30dBm, wireless access point ≤ 20dBm, network terminal device ≤ 10dBm);

[0112] Abnormal channel quality means the signal-to-noise ratio is lower than the expected value (calculated based on the channel quality index);

[0113] Traffic anomaly refers to the peak value of upstream and downstream traffic or the average packet queue delay exceeding the normal range (compared with the old network status data, the normal range threshold of traffic is set to ±20%. If it exceeds the normal range threshold, it is determined to be abnormal traffic);

[0114] Analyze the root causes of network anomalies (including interference root causes, configuration root causes, and network device root causes) based on the network interference relationship diagram and network anomaly detection results;

[0115] If the spectrum or channel quality is abnormal, check the use of the same-frequency or adjacent-frequency channels, calculate the interference intensity (reduce the signal-to-noise ratio), and locate the interference source device;

[0116] If power or traffic is abnormal, verify whether the configured network parameters in the network parameter adjustment log exceed the hardware capabilities of the network device or do not match the traffic load;

[0117] If the anomaly is concentrated on a specific network device, consider the topology and network device energy consumption to determine whether it is a hardware failure or excessive energy consumption.

[0118] The root cause of network anomalies is located through weight analysis. The expression is:

[0119]

[0120] Where R is the root cause weight, that is, the root cause with the highest weight is found from multiple root causes, W is the interference relationship graph weight, CQI is the channel quality index, and ΔT is the anomaly duration (unit: seconds);

[0121] Integrate anomaly detection results and root causes into an anomaly analysis report (including a list of abnormal devices, root cause description, timestamp, and checksum);

[0122] The timestamp is for the exception analysis report, indicating the time when the exception analysis report was generated;

[0123] The check code is for the exception analysis report, verifying the integrity of the entire content of the exception analysis report;

[0124] Generate anomaly handling suggestions based on the root cause of the anomaly detection results;

[0125] If the root cause is interference, adjust the allocated frequency bands in the spectrum allocation strategy matrix to trigger recalculation;

[0126] If the root cause is configuration, correct the configured network parameters in the network parameter adjustment log to trigger re-issuance;

[0127] If the root cause is network equipment, notify the user to check the hardware status or replace the network equipment;

[0128] Attach the exception handling suggestions to the exception analysis report and record them in the central server operation log.

[0129] S5. Filter out redundant links in the network, use the ant colony optimization algorithm to optimize the topology structure and update the spectrum allocation strategy matrix, isolate the faulty nodes and reconstruct the topology connection.

[0130] Furthermore, the current topological connection (including network device ID, connection relationship, and channel allocation) is extracted from the network status data;

[0131] Obtain a list of abnormal devices, root causes (interference, configuration, device failure), and interference intensity data from the anomaly analysis report;

[0132] Identify all network connection paths from the topology provided by network status data, extract pre-configured backup connections not used by the primary link (such as multiple wireless access points for terminals or redundant backhaul links for network base stations), and form a list of redundant link candidates. Then, based on the network fault devices and fault causes (such as a failure or interference on the primary link T1-AP1) indicated in the anomaly analysis report, select redundant links (such as T1-AP2) that are suitable for replacing the failed primary link, ensuring that the redundant links bypass the primary link failure or reduce interference.

[0133] Using the ant colony optimization algorithm, network performance indicators (channel quality index, traffic delay, network equipment energy consumption) are generated based on network status data as fitness functions to search for the best network topology to fix anomalies and optimize network performance.

[0134] Among them, network performance indicators belong to the subset of network status data;

[0135] The input parameters of the ant colony optimization algorithm are defined as the interference relationship graph weight, anomaly duration and current spectrum allocation strategy matrix, which serve as the initial topology and optimization basis.

[0136] Construct a topology graph based on the input parameters (nodes are network devices, edges are network connection relationships, and attributes are network frequency bands and network power);

[0137] The ant colony optimization algorithm selects a topology scheme based on pheromones and heuristic factors (determined by the weight of the interference relationship graph and the duration of anomalies), and evaluates each topology scheme using the network performance index as the fitness function;

[0138] Update pheromones, output the optimized best topology, and redistribute device connection relationships, network frequency bands, and power parameters;

[0139] Pheromones are the memory mechanism in the ant colony optimization algorithm. During network topology reconstruction, they mark the quality of each topological connection and guide the algorithm through updates (evaporation + deposition) to find a topology with high CQI, low latency, and optimal energy consumption.

[0140] Update the spectrum allocation strategy matrix (adjust network frequency band, center frequency, and bandwidth) based on the results of the ant colony optimization algorithm;

[0141] Correct the configured network parameters of the abnormal device (e.g., reduce network power to reduce network interference) and use them as the reconstructed configured network parameters;

[0142] If a network device failure occurs, mark the network device that needs to be replaced and temporarily adjust the topology connection to bypass the network fault node;

[0143] The reconstructed configuration network parameters and topology connections are sent to the target network devices (network base stations, wireless access points, and network terminal devices) through the TLS encryption protocol.

[0144] After the delivery is completed, the operation timestamp and verification code are recorded in the central server operation log;

[0145] All collection probes re-collect network status data at a basic frequency of 10 times per second;

[0146] The central server compares the re-collected network status data with the expected configured network parameters to check whether the anomaly has been eliminated;

[0147] If the anomaly still exists, adjust the control parameters of the ant colony optimization algorithm (such as increasing the number of iterations or changing the weight threshold) and rerun the topology reconstruction process;

[0148] Compare the optimized topology connection with the initial topology connection and update the network topology database;

[0149] Generate a topology reconstruction report, including the topology diagrams before and after reconstruction, anomaly repair results, and performance improvement indicators (such as the percentage of improved channel quality index and the degree of delay reduction);

[0150] A hash value is added to the topology reconstruction report, which is then archived to the central server database via the TLS encryption protocol and recorded in the central server operation log.

[0151] This embodiment also provides a computer wireless network operation supervision system, including: a collection module for collecting network status data, the network status data including spectrum occupancy, channel quality, topological connection, traffic load and network equipment energy consumption, and encrypting and transmitting it to a central server; a generation module for constructing a QUBO model and generating a network spectrum allocation policy matrix through a quantum annealing machine; an adjustment module for parsing the network spectrum allocation policy matrix, generating a network base station radio frequency parameter instruction set and a network terminal access policy table, and adjusting the network flow table rules through an SDN controller; an anomaly module for re-collecting network status data, comparing the expected configuration network parameters with the new network status data, verifying whether the network operation status meets expectations and detecting network anomalies, locating the root cause of the network anomaly, and generating an anomaly analysis report; an update module for screening out redundant links in the network, optimizing the topology structure using an ant colony optimization algorithm and updating the spectrum allocation policy matrix, isolating faulty nodes and reconstructing topological connections.

[0152] This embodiment also provides a computer device suitable for the computer wireless network operation supervision method, including: a memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions to implement the computer wireless network operation supervision method proposed in the above embodiment.

[0153] The computer device may be a terminal, comprising a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device comprises a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner may be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a button, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse.

[0154] This embodiment also provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for supervising the operation of a computer wireless network as proposed in the above embodiment; the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0155] In summary, the present invention improves the operation supervision of computer wireless networks through a quantum annealer. In terms of spectrum resource allocation, the quantum annealer optimizes frequency allocation and transmit power by constructing a QUBO model solution. Compared with the traditional simulated annealing algorithm with a calculation time of several seconds, it achieves near real-time dynamic adjustment, meeting the rapid response requirements in high-density network environments. The quantum annealer accurately quantifies the interference intensity of the same frequency and adjacent frequencies, achieving global interference minimization and channel quality index maximization.

[0156] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for supervising wireless network operation, characterized in that: include, Collecting network status data, including spectrum occupancy, channel quality, topology connectivity, traffic load, and network device energy consumption, and transmitting the encrypted data to a central server; Construct the QUBO model and generate the network spectrum allocation strategy matrix through quantum annealing. Parse the network spectrum allocation policy matrix and extract the configuration network parameters for each network device. Generate a set of radio frequency parameter instructions based on the allocated frequency bands and transmit powers of the network base stations in the network spectrum allocation policy matrix. Generate a network terminal access policy table based on the allocation data of wireless access points and network terminals in the network spectrum allocation policy matrix. Use the NETCONF protocol to push the set of radio frequency parameter instructions to the network base stations over a secure channel. The network terminal access policy table is sent to wireless access points and network terminals using the CoAP protocol over a DTLS encrypted channel. Network flow table rules are generated based on traffic load and in combination with the allocated frequency band, transmit power, and effective time window in the configured network parameters. Network flow table rules are sent and adjusted via the SDN controller. Configurations sent by the network spectrum allocation policy matrix are recorded and a network parameter adjustment log is generated. The network devices include network base stations, network terminals, and network access points. Recollect network status data, compare the expected configuration network parameters in the network parameter adjustment log with the new network status data, verify whether the network operation status meets expectations, detect network anomalies, locate the root cause of the network anomaly, and generate an anomaly analysis report; Based on the anomaly analysis report, redundant links in the network are screened out, and the ant colony optimization algorithm is used to optimize the topology structure and update the network spectrum allocation strategy matrix, isolate the faulty nodes and reconstruct the topology connection.

2. The wireless network operation supervision method according to claim 1, wherein: The QUBO model is constructed and the network spectrum allocation strategy matrix is ​​generated by quantum annealing. The specific steps are: Construct a network interference relationship graph based on topological connectivity, spectrum status, and channel quality; Set optimization goals and constraints for the network interference relationship graph; Based on the optimization objectives and constraints, a QUBO model is constructed; Upload the QUBO model to the quantum annealer through the API interface, set the solution parameters of the quantum annealer, and obtain the optimal solution; The quantum annealer solves the frequency allocation and transmission power of network devices based on the optimization objectives and constraints in the QUBO model; Use constraints to check frequency allocation and transmit power. If the constraints are violated, adjust the weight of the interference relationship graph and recalculate; Integrate the verified compliant frequency allocation and transmit power into a network spectrum allocation strategy matrix.

3. The wireless network operation supervision method according to claim 1, wherein: The parsing of the network spectrum allocation strategy matrix refers to extracting the configuration network parameters of the network devices through the central server; The network flow table rules are generated based on traffic load, combined with allocated frequency band, transmit power and effective time window.

4. The wireless network operation supervision method according to claim 1, wherein: The root cause of the network anomaly is determined by weight analysis, dynamically correlating the interference intensity, poor channel quality and network anomaly duration in the network interference relationship diagram, and sorting priorities.

5. The wireless network operation supervision method according to claim 1, wherein: Screening out redundant links in the network refers to identifying all network connection paths from the topological connection, extracting pre-configured backup connections that are not used by the main link, forming a redundant link candidate list, and combining the abnormality analysis report to indicate the network fault device and the root cause, and screening out redundant links to replace the failed main link.

6. The wireless network operation supervision method according to claim 1, wherein: The use of the ant colony optimization algorithm to optimize the topology structure and update the network spectrum allocation strategy matrix refers to using the ant colony optimization algorithm to generate network performance indicators as fitness functions based on network status data, search for the optimal topology structure, repair abnormal networks, and update the network spectrum allocation strategy matrix.

7. The wireless network operation supervision method according to claim 1, wherein: Isolating the faulty node and reconstructing the topology connection refers to reconfiguring the network parameters and topology connection according to the updated network spectrum allocation strategy matrix, marking the faulty network device and adjusting the topology connection, and isolating the network faulty node.

8. A wireless network operation supervision system, configured to execute the wireless network operation supervision method according to any one of claims 1 to 7, characterized in that: include, A collection module is used to collect network status data, including spectrum occupancy, channel quality, topology connection, traffic load, and network device energy consumption, and transmit the encrypted data to a central server; The generation module is used to build the QUBO model and generate the network spectrum allocation strategy matrix through quantum annealing. The adjustment module is used to parse the network spectrum allocation policy matrix and extract the configuration network parameters of each network device. It generates a radio frequency parameter instruction set based on the allocated frequency band and transmit power of the network base station in the network spectrum allocation policy matrix. It also generates a network terminal access policy table based on the allocation data of wireless access points and network terminals in the network spectrum allocation policy matrix. It uses the NETCONF protocol to push the radio frequency parameter instruction set to the network base station through a secure channel. The network terminal access policy table is sent to wireless access points and network terminals using the CoAP protocol over a DTLS encrypted channel. Network flow table rules are generated based on traffic load and in combination with the allocated frequency band, transmit power, and effective time window in the configured network parameters. Network flow table rules are sent and adjusted via the SDN controller. Configurations sent by the network spectrum allocation policy matrix are recorded and a network parameter adjustment log is generated. The network devices include network base stations, network terminals, and network access points. The anomaly module is used to recollect network status data, compare the expected configuration network parameters in the network parameter adjustment log with the new network status data, verify whether the network operation status meets expectations, detect network anomalies, locate the root cause of network anomalies, and generate anomaly analysis reports; The update module is used to screen out redundant links in the network based on the anomaly analysis report, optimize the topology structure using the ant colony optimization algorithm and update the network spectrum allocation strategy matrix, isolate the faulty nodes and reconstruct the topology connection.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the wireless network operation supervision method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the wireless network operation supervision method according to any one of claims 1 to 7 are implemented.

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