Computer wireless network operation supervision system and method

Abstract

The invention discloses a computer wireless network operation supervision system and method, and relates to the technical field of network security, and the method comprises the steps: collecting network state data; constructing a QUBO model, and solving and generating a network spectrum allocation strategy matrix through a quantum annealing machine; analyzing the network spectrum allocation strategy matrix, generating a network base station radio frequency parameter instruction set and a network terminal access strategy table, and adjusting a network flow table rule through an SDN controller; comparing the expected configuration network parameters with the new network state data, and positioning the root cause of the network abnormal condition; and redundant links in the network are screened out, an ant colony optimization algorithm is adopted to optimize a topological structure, a spectrum allocation strategy matrix is updated, fault nodes are isolated, and topological connection is reconstructed. According to the method, computer wireless network operation supervision is improved through the quantum annealing machine, and in the aspect of spectrum resource allocation, the quantum annealing machine solves by constructing a QUBO model, so that optimization of frequency allocation and transmitting power is realized.

Description

Technical Field

[0001] The present invention relates to the field of network security technology, 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, the progress of computer technology has improved the intelligent level of network performance management. With the popularization of 5G and Wi-Fi 6 technologies, the diverse deployment and high-density characteristics of network devices have put forward higher requirements for the efficient allocation of spectrum resources. In the existing literature, dynamic spectrum management based on software-defined network (SDN) has realized the real-time monitoring of network operation status. For example, the channel allocation is optimized through the interference relationship graph to reduce co-channel interference. In addition, the application of quantum computing has gradually emerged. Using a quantum annealing machine 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, the existing technologies still have deficiencies in practical applications, especially in high-dynamic and multi-interference wireless network environments. Firstly, traditional network state 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, and it is difficult to comprehensively reflect the network operation status. Secondly, although quantum computing has been introduced in spectrum allocation optimization, its ability to adaptively adjust the network topology is limited. Especially in terms of fault node isolation and redundant link utilization, there is a lack of solutions, resulting in limited network performance optimization effects. In addition, the existing methods have a slow response speed in the closed-loop management of anomaly detection and repair, and cannot effectively cope with sudden interference or device 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] 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, where the network status data includes spectrum occupancy rate, channel quality, topological connection, traffic load, and network device energy consumption, and encrypting and transmitting it to a central server; constructing a QUBO model, and solving it through a quantum annealer to generate a network spectrum allocation strategy matrix; parsing the network spectrum allocation strategy matrix to generate a network base station radio frequency parameter instruction set and a network terminal access strategy table, and adjusting the network flow table rules through an SDN controller; re-collecting network status data, comparing the expected configured network parameters with the new network status data, verifying whether the network operation status meets the expectations and detecting network anomalies, locating the root cause of the network anomalies, generating an anomaly analysis report; screening out redundant links in the network, optimizing the topological structure using the ant colony optimization algorithm and updating the spectrum allocation strategy matrix, isolating faulty nodes and reconstructing the topological connection.

[0008] As a preferred solution of the method for supervising the operation of a computer wireless network according to the present invention, wherein: the steps of constructing a QUBO model and solving it through a quantum annealer to generate a network spectrum allocation strategy matrix are specifically as follows:

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

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

[0011] Construct a QUBO model based on the optimization objectives and constraints;

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

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

[0014] Use the constraints to verify the frequency allocation and transmission power. If the constraints are violated, adjust the weights of the interference relationship graph and recalculate;

[0015] Integrate the verified compliant frequency allocation and transmission power into a spectrum allocation strategy matrix.

[0016] As a preferred solution of the method for supervising the operation of a computer wireless network according to the present invention, wherein: parsing the network spectrum allocation strategy matrix means extracting the configured network parameters of network devices through a central server;

[0017] The network flow table rules are generated based on the traffic load, combined with the allocated frequency band, transmission power, and effective time window.

[0018] As a preferred solution of the computer wireless network operation supervision method described in the present invention, wherein: the root cause of the located network anomaly is determined by weight analysis, dynamically associating the interference intensity, the inferior situation of the channel quality and the network anomaly duration in the network interference relationship diagram, and sorting the priority.

[0019] As a preferred solution of the computer wireless network operation supervision method described in the present invention, wherein: screening out the redundant links in the network means identifying all network connection paths from the topological connection, extracting the pre-configured standby connections not used by the main link, forming a redundant link candidate list, and combining the anomaly analysis report to indicate the network fault devices and the root cause, and screening out the 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, wherein: using the ant colony optimization algorithm to optimize the topological structure and update the spectrum allocation policy matrix means generating network performance indicators as the fitness function based on the network state data through the ant colony optimization algorithm, searching for the optimal topological structure, repairing the abnormal network, and updating the spectrum allocation policy matrix.

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

[0022] In a second aspect, the present invention provides a computer wireless network operation supervision system, including an acquisition module for acquiring network state data, where the network state data includes spectrum occupancy rate, channel quality, topological connection, traffic load, and network device energy consumption, and encrypting and transmitting it to the central server; a generation module for constructing a QUBO model and solving it through a quantum annealing machine to generate a network spectrum allocation policy matrix; an adjustment module for analyzing 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-acquiring network state data, comparing the expected configured network parameters with the new network state data, verifying whether the network operation state meets the expectations and detecting network anomalies, locating the root cause of the network anomalies, and generating an anomaly analysis report; an update module for screening out the redundant links in the network, using the ant colony optimization algorithm to optimize the topological structure and update the spectrum allocation policy matrix, and isolating the fault nodes and reconstructing the topological connection.

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

[0025] The beneficial effects of the present invention are as follows: The present invention improves the supervision of computer wireless network operation through a quantum annealing machine. In terms of spectrum resource allocation, the quantum annealing machine constructs a QUBO model to solve, realizing the optimization of frequency allocation and transmission power. Compared with the several-second calculation time of the traditional simulated annealing algorithm, it realizes almost real-time dynamic adjustment, meeting the rapid response requirements in a high-density network environment. The quantum annealing machine accurately quantifies the interference intensity of co-frequency and adjacent frequencies, realizing 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 drawings required for the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0027] Figure 1 It is a flowchart of the computer wireless network operation supervision method in Embodiment 1.

[0028] Figure 2 It is a flowchart of the construction and solution of the QUBO model in Embodiment 1.

[0029] Figure 3 It is a schematic diagram of policy parsing and network adjustment in Embodiment 1.

[0030] Figure 4 It is a flowchart of exception handling and topology optimization in Embodiment 1. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0031] In order to make the above objects, features, and advantages of the present invention more obvious and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings of the specification.

[0032] In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. However, the present invention may be practiced in other ways than those specifically described herein, and those skilled in the art can make similar extensions without departing from the spirit of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed below.

[0033] Secondly, as used herein, an "embodiment" or "embodiments" refer to specific features, structures, or characteristics that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it an individual or alternative embodiment that is mutually exclusive with other embodiments.

[0034] Embodiment 1, referring to Figures 1 to 4 , which is the first embodiment of the present invention. This embodiment provides a method for monitoring the operation of a computer wireless network, including the following steps:

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

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

[0037] Among them, hardware-level probes are deployed in network base stations, which support high-frequency radio frequency signal scanning (such as 5 GHz, 6 GHz);

[0038] Software probes are deployed in wireless access points (APs) and network terminal devices, which are integrated into the network device firmware;

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

[0040] Set the fixed collection frequency to 10 times per second, and instantaneously increase it to 50 times per second during emergencies;

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

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

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

[0044] The topology connection includes device ID, IP address, physical location coordinates, and adjacency relationship table;

[0045] The traffic load includes the uplink and downlink traffic peaks (unit: Mbps) and the average packet queue delay (unit: ms);

[0046] The energy consumption of network devices includes the power consumption of wireless network cards (unit: mW) and the remaining battery power of terminals (percentage);

[0047] The clocks of all collection probes are aligned through the time synchronization protocol to ensure that the time accuracy of the collected network status data reaches the microsecond level;

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

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

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

[0051] S2. Construct a QUBO model and use a quantum annealer to solve it at high speed to generate a network spectrum allocation strategy matrix.

[0052] Furthermore, the central server receives the global network status data packet, 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 connections, spectrum status, and channel quality;

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

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

[0056] Use the channel quality index as the weight of the auxiliary interference relationship graph to generate a weighted interference relationship graph, 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 for the weight of the interference relationship graph is:

[0058]

[0059] Among them, W is the weight of the interference relationship graph, representing the interference degree of a certain connection (edge) in the network, with a range of 0 - 1. 0 means no interference, representing the best network connection state, and 1 means the 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 communication and is usually measured by network devices, reflecting the reliability and transmission ability 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), and ΔSNR max is the maximum expected signal - to - noise ratio reduction value, with the unit of dB. It is a reference threshold set according to specific operations, representing the maximum possible interference degree. The reference threshold can be set to 20 dB (indoor Wi - Fi) or 30 dB (outdoor cellular network), and it needs to be determined according to the actual scenario;

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

[0061] Set the optimization objective and constraint conditions for the network interference relationship graph;

[0062] The optimization objective is:

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

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

[0065] The constraint conditions are:

[0066] By collecting probes, set the supported frequency band range for the network device hardware;

[0067] Set the upper limit of the network transmission power as a configurable network parameter (the default values are network base station ≤ 30 dBm, wireless access point ≤ 20 dBm, network terminal device ≤ 10 dBm);

[0068] Set the network terminal energy consumption limit (the power consumption does not exceed 10% of the current power of the network device);

[0069] Based on the optimization objective and constraint conditions, construct a QUBO (Quadratic Unconstrained Binary Optimization) model;

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

[0071] Among them, the quantum annealing machine solves to obtain the best spectrum allocation scheme for the network device according to the optimization objective and constraint conditions in the QUBO model, such as obtaining the optimal frequency allocation and transmission power to optimize the network performance;

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

[0073] After receiving the QUBO model, the quantum annealing machine determines, according to the optimization objective and constraint conditions, to calculate the frequency allocation and transmission power of each network device within 100 ms and return the results to the central server. If it times out, it switches to the standby traditional simulated annealing algorithm;

[0074] Use the constraint conditions to verify the frequency allocation and transmission power. If the constraint conditions are violated (such as power overlimit), adjust the weights of the interference relationship graph and recalculate. Iterate at most 3 times. On the premise of meeting the constraints, it can also approach the optimization objective;

[0075] Integrate the frequency allocation and transmission power that pass the verification into a spectrum allocation strategy matrix;

[0076] Add the verified hash value to the spectrum allocation strategy matrix and encapsulate it. Through the TLS encryption protocol, store the spectrum allocation strategy matrix in the central server.

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

[0078] Furthermore, after receiving the spectrum allocation strategy matrix, the central server verifies the hash value of the spectrum allocation strategy matrix to ensure that the data has not been tampered with or damaged during the transmission process. If the verification fails, record the error log and return to regenerate the spectrum allocation strategy matrix;

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

[0080] Classify the configured network parameters according to the network device types (network base stations, wireless access points, network terminal devices) to generate a device configuration list;

[0081] Generate a radio frequency parameter instruction set according to the allocated frequency band and transmission power of the network base station in the spectrum allocation strategy matrix, including the center frequency point, bandwidth, and transmission power;

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

[0083] Generate a network terminal access strategy table according to the allocation data of the wireless access points and network terminal devices in the spectrum allocation strategy matrix;

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

[0085] The priority is set according to traffic load and channel quality index. For example, the priority of a high-load network device is 1, and the priority of a low-load network device is 3; the allowed access frequency band list is the listed available frequency bands; the transmit power limit directly references the value in the spectrum allocation policy matrix;

[0086] Use the NETCONF protocol to push the radio frequency parameter instruction set to the network base station 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 pending retry;

[0088] After pushing, receive the configuration of the network base station and confirm the response. If it fails, roll back to the previous stable configuration; among them, the previous stable configuration is the radio frequency parameter instruction set that has been successfully applied and is running normally by the network base station 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 a DTLS encrypted channel;

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

[0091] For the network terminal, the software probe receives the network terminal access policy table and adjusts the wireless network card parameters, including frequency and power, sets the timeout to 5 seconds, and retries if no confirmation is received, up to 3 times;

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

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

[0094] Send and adjust the network flow table rules through the SDN controller to optimize the traffic distribution between network devices and adjust the network flow table rules;

[0095] Dynamically adjust the 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] According to the allocated frequency band and traffic load in the spectrum allocation policy matrix, optimize the traffic distribution between the network base station and the wireless access point;

[0097] Record the configuration of the spectrum allocation policy matrix issued, and generate a network parameter adjustment log;

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

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

[0100] If the configuration issuance fails, for example, the network base station rejects the configured network parameters or the network terminal device does not respond, then roll back to the previous stable configuration according to the network parameter adjustment log;

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

[0102] Record the reason for the issuance failure in the central server operation log, such as power exceeding the hardware limit, and trigger recalculation and allocation.

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

[0104] Furthermore, re-collect network status data, verify whether the network operation status after the configuration issuance meets the expectations, and detect whether there are any anomalies;

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

[0106] Add a policy effectiveness identifier to the re-collected network status data to mark whether the currently collected network status data is within the effective time window of the spectrum allocation policy matrix;

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

[0108] Among them, the expected configured network parameters are the states that the network devices should reach in the network parameter adjustment log;

[0109] Anomalies include spectrum anomalies, power anomalies, channel quality anomalies, and traffic anomalies;

[0110] Among them, spectrum anomaly means that the actual frequency band or center frequency point does not match the configured network parameters;

[0111] Power anomaly means that the actual transmission power exceeds the configured network parameters or the hardware upper limit (for network base stations ≤ 30 dBm, wireless access points ≤ 20 dBm, network terminal devices ≤ 10 dBm);

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

[0113] Traffic anomaly means that the peak value of uplink and downlink traffic or the average packet queue delay exceeds the normal range (compared with the old network status data, the traffic normal range threshold is set at ±20%, and if it exceeds the normal range threshold, it is determined as abnormal traffic);

[0114] Based on the network interference relationship graph and the network anomaly detection results, analyze the root causes of network anomalies (including interference root causes, configuration root causes, and network device root causes);

[0115] If there is a spectrum anomaly or a channel quality anomaly, check the usage of co-frequency or adjacent-frequency channels, calculate the interference intensity (reduce the signal-to-noise ratio value), and locate the interfering source device;

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

[0117] If the anomalies are concentrated in specific network devices, combine the topological connections and the energy consumption of the network devices to determine whether it is a hardware failure or an energy consumption overrun;

[0118] Locate the root cause of the network anomaly situation through weight analysis. The expression is:

[0119]

[0120] Among them, R is the root cause weight, that is, the one 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: second);

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

[0122] Among them, the timestamp is for the anomaly analysis report, indicating the time when the anomaly analysis report is generated;

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

[0124] Locate the anomaly detection results according to the root cause and generate anomaly handling suggestions;

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

[0126] If it is the root cause of configuration, correct the configured network parameters in the network parameter adjustment log to trigger redelivery;

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

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

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

[0130] Furthermore, extract the current topology connection (including network device ID, connection relationship, channel allocation) from the network status data;

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

[0132] Identify all network connection paths from the topology connection provided by the network status data, extract the pre-configured standby connections not used by the main link (such as the multi-wireless access point option of the terminal or the redundant backhaul link of the network base station) to form a redundant link candidate list; then combine the network faulty devices and fault causes (such as the failure of the main link T1-AP1 or interference) indicated by the exception analysis report to screen out the redundant links (such as T1-AP2) suitable for replacing the failed main link to ensure that the redundant link bypasses the main link failure or reduces interference;

[0133] Adopt the ant colony optimization algorithm to generate network performance metrics (channel quality index, traffic delay, network device energy consumption) based on the network status data as the fitness function, search for the optimal network topology structure to repair the exception and optimize the network performance;

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

[0135] Define the input parameters of the ant colony optimization algorithm as the interference relationship graph weight, exception duration and current spectrum allocation strategy matrix as the initial topology and optimization basis;

[0136] Construct a topology graph based on the input parameters (including 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 weights of the interference relationship graph and the abnormal duration), and evaluates each topology scheme with the network performance index as the fitness function;

[0138] Update the pheromones, output the optimized best topology structure, and reallocate the device connection relationship, network frequency band, and power parameters;

[0139] Among them, pheromones are the memory mechanism in the ant colony optimization algorithm. In network topology reconstruction, they mark the advantages and disadvantages of each topology connection, and guide the algorithm to find a topology structure with high CQI, low latency, and excellent energy consumption through updating (evaporation + deposition);

[0140] According to the results of the ant colony optimization algorithm, update the spectrum allocation strategy matrix (adjust the network frequency band, center frequency point, and bandwidth);

[0141] Modify the configuration network parameters of abnormal devices (such as reducing the network power to reduce network interference) as the configuration network parameters after reconstruction;

[0142] If a network device failure is involved, mark the network device to be replaced and temporarily adjust the topology connection to bypass the network failure node;

[0143] Through the TLS encryption protocol, send the reconstructed configuration network parameters and topology connection to the target network devices (network base stations, wireless access points, network terminal devices);

[0144] After the sending is completed, record the operation timestamp and check code in the central server running log;

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

[0146] The central server compares the re-acquired network status data with the expected configuration network parameters to check whether the anomalies are eliminated;

[0147] If the anomalies still exist, adjust the control parameters of the ant colony optimization algorithm (such as increasing the number of iterations or changing the weight threshold), and re-run 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, the abnormal repair results, and the performance improvement indicators (such as the percentage of improvement in the channel quality index and the reduction amplitude of latency);

[0150] Add a hash value to the topology reconstruction report, archive it in the central server database through the TLS encryption protocol, and record it in the central server running log.

[0151] This embodiment also provides a computer wireless network operation supervision system, including: a collection module, which is used to collect network status data, where the network status data includes spectrum occupancy rate, channel quality, topology connection, traffic load, and network device energy consumption, and encrypts and transmits it to the central server; a generation module, which is used to construct a QUBO model and solve it through a quantum annealer to generate a network spectrum allocation strategy matrix; an adjustment module, which is used to analyze the network spectrum allocation strategy matrix, generate a network base station radio frequency parameter instruction set and a network terminal access strategy table, and adjust the network flow table rules through the SDN controller; an exception module, which is used to re-collect network status data, compare the expected configured network parameters with the new network status data, verify whether the network operation status meets the expectations and detect network anomalies, locate the root cause of the network anomalies, and generate an anomaly analysis report; an update module, which is used to screen out redundant links in the network, optimize the topology structure using the ant colony optimization algorithm and update the spectrum allocation strategy matrix, isolate faulty nodes and reconstruct the topology connection.

[0152] This embodiment also provides a computer device, which is applicable to the situation of 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] This computer device can be a terminal. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes 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 can be implemented through WIFI, a carrier network, NFC (Near Field Communication), or other technologies. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a button, a trackball, or a touchpad set on the computer device housing, or an external keyboard, touchpad, or mouse, etc.

[0154] This embodiment also provides a storage medium, on which a computer program is stored. When the program is executed by a processor, it implements the method for supervising the operation of a computer wireless network 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 (Static Random Access Memory, abbreviated as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, abbreviated as EEPROM), erasable programmable read-only memory (Erasable Programmable Read Only Memory, abbreviated as EPROM), programmable read-only memory (Programmable Red-Only Memory, abbreviated as PROM), read-only memory (Read-Only Memory, abbreviated as ROM), magnetic memory, flash memory, magnetic disk or optical disc.

[0155] In summary, the present invention improves the supervision of the operation of a computer wireless network through a quantum annealing machine. In terms of spectrum resource allocation, the quantum annealing machine constructs a QUBO model for solution, realizes the optimization of frequency allocation and transmission power, and compared with the several-second calculation time of the traditional simulated annealing algorithm, it realizes almost real-time dynamic adjustment, meeting the fast response requirements in a high-density network environment. The quantum annealing machine accurately quantifies the interference intensity of co-frequency and adjacent frequencies, and realizes the minimization of global interference and the maximization of the channel quality index.

[0156] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered within the scope of the claims of the present invention.

Claims

1. A computer wireless network operation supervision method, characterized in that: include, Collecting network status data, including spectrum occupancy, channel quality, topological connection, traffic load, and network equipment energy consumption, and encrypting and transmitting the data to a central server; Construct the QUBO model and generate the network spectrum allocation strategy matrix through quantum annealing; Analyze the network spectrum allocation strategy matrix, generate network base station radio frequency parameter instruction set and network terminal access strategy table, and adjust network flow table rules through the SDN controller; Re-collect network status data, compare expected configuration network parameters with new network status data, verify whether the network operation status meets expectations and detect network anomalies, locate the root cause of network anomalies, and generate anomaly analysis reports; The redundant links in the network are screened out, the ant colony optimization algorithm is used to optimize the topology structure and update the spectrum allocation strategy matrix, isolate the faulty nodes and reconstruct the topology connection.

2. The computer wireless network operation supervision method according to claim 1, characterized in that: The QUBO model is constructed to generate a network spectrum allocation strategy matrix by using a quantum annealing machine. The specific steps are: Construct a network interference relationship graph based on topological connections, 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; The frequency allocation and transmit power for verification compliance are integrated into a spectrum allocation strategy matrix.

3. The computer wireless network operation supervision method according to claim 1, characterized in that: 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 the traffic load, combined with the allocated frequency band, transmission power and effective time window.

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

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

6. The computer wireless network operation supervision method according to claim 1, characterized in that: 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 a network performance indicator as a fitness function based on network status data, search for the optimal topology structure, repair abnormal networks, and update the spectrum allocation strategy matrix.

7. The computer wireless network operation supervision method according to claim 1, characterized in that: The isolating the faulty nodes and reconstructing the topological connections refers to reconfiguring the network parameters and the topological connections according to the updated spectrum allocation strategy matrix, marking the faulty network devices and adjusting the topological connections, and isolating the network faulty nodes.

8. A computer wireless network operation supervision system, based on the computer 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, topological connection, traffic load and network equipment energy consumption, and encrypt and transmit it 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 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; The anomaly module is used to 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 network anomalies, and generate anomaly analysis reports; The update module is used to filter out redundant links in the network, optimize the topology structure using the ant colony optimization algorithm and update the spectrum allocation strategy matrix, isolate faulty nodes and reconstruct topological connections.

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 computer 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 the processor, the computer wireless network operation according to any one of claims 1 to 7 is realized. Steps in the regulatory approach.

Images