System and method for adaptive configuration of variability communication parameters in a communication system

Abstract

This application provides an adaptive configuration system and method for variable communication parameters in a communication system. It acquires communication operation data and current communication parameter configuration of a target communication object through the southbound interface of an SDN controller. The communication operation data is used for scenario-based simulation to generate multiple candidate configuration schemes for the target communication object. Trajectory analysis is performed based on the current communication parameter configuration to obtain the parameter variability state. For each candidate configuration scheme, perturbation mapping is applied to the parameter variability state to determine the configuration perturbation potential energy of that candidate configuration scheme. Then, based on the configuration perturbation potential energy corresponding to each candidate configuration scheme, a parameter release strategy is generated. According to the parameter release strategy, the SDN controller issues a communication parameter configuration command to the target communication object and triggers an update of the parameter variability state. This application can adaptively adjust communication parameters to achieve perturbation-controlled configuration, thereby improving communication stability.

Description

Technical Field

[0001] This application relates to the field of communication technology, and more specifically, to a system and method for adaptive configuration of variable communication parameters in a communication system. Background Technology

[0002] As communication networks become increasingly complex and dynamic, traditional static parameter configuration methods are struggling to adapt to real-time changes in channel conditions, network load, and service requirements. To address this, the industry has proposed a series of adaptive communication parameter configuration schemes, such as closed-loop parameter adjustment based on channel state feedback and dynamic parameter distribution under centralized management by a Software Defined Network (SDN) controller. These solutions have improved the network's adaptability to dynamic environments to some extent.

[0003] However, existing communication parameter configuration methods typically rely on static rules, manual experience, or single-time performance metrics. When network conditions change, the system often directly generates configuration adjustment schemes based on current link load, service priority, or alarm information, and then distributes the configuration parameters to the corresponding communication devices. While this approach can achieve parameter adjustment to some extent, it usually only focuses on the immediate performance improvement brought by candidate configuration schemes, lacking comprehensive analysis of the historical change trajectory of communication parameters, the frequency of parameter adjustments, repeated configuration rollbacks, and the impact of coupling disturbances between parameters. Furthermore, in complex communication scenarios, some communication parameters exhibit strong variability and correlation; directly distributing candidate configuration schemes with high expected performance to devices may cause parameter oscillations and link jitter. Therefore, how to adaptively allocate communication parameters to achieve disturbance-controlled configuration, thereby improving communication stability, has become a challenge for the industry. Summary of the Invention

[0004] This application provides a system and method for adaptive configuration of variable communication parameters in a communication system, which can adaptively adjust communication parameters to achieve controlled disturbance configuration, thereby improving communication stability.

[0005] In a first aspect, this application provides a method for adaptive configuration of variable communication parameters in a communication system, comprising the following steps: The communication operation data and current communication parameter configuration of the target communication object are obtained through the southbound interface of the SDN controller. The communication operation data is used to perform scenario-based simulation to generate multiple candidate configuration schemes for the target communication object. Based on the current communication parameter configuration, trajectory analysis is performed to obtain the parameter variability state. For each candidate configuration scheme, the parameter variability state is perturbed and mapped to determine the configuration perturbation potential energy of the candidate configuration scheme. Then, based on the configuration perturbation potential energy corresponding to each candidate configuration scheme, a parameter release strategy is generated. Based on the parameter release strategy, the SDN controller sends communication parameter configuration instructions to the target communication object and triggers parameter variability state updates.

[0006] In some embodiments, obtaining the communication operation data and current communication parameter configuration of the target communication object through the southbound interface of the SDN controller specifically includes: Collect communication status monitoring data and the current configuration table stored locally on the device from the forwarding device, access device or edge gateway corresponding to the target communication object; The communication status monitoring data is preprocessed to generate communication operation data corresponding to the current sliding time window; The current configuration table is associated with the communication operation data to obtain the current communication parameter configuration of the target communication object.

[0007] In some embodiments, performing scenario-based simulations on the communication operation data to generate multiple candidate configuration schemes for the target communication object specifically includes: Based on the communication operation data, identify the business scenario tag of the target communication object; Obtain the parameter template that matches the business scenario tag; By combining link constraints, service priorities, and device-side resource reserves, the parameter template is modified through multi-parameter linkage to generate multiple candidate configuration schemes that meet preset feasibility constraints.

[0008] In some embodiments, trajectory parsing based on the current communication parameter configuration to obtain the parameter variability state specifically includes: Based on the current communication parameter configuration and the historical communication parameter configuration, a parameter change trajectory is constructed, and then core temporal features are extracted from the parameter change trajectory; The core temporal features are scaled to form a parameter variability vector. The parameter reverse adjustment frequency and configuration rollback strength are determined based on the parameter change trajectory sequence, and the device queue congestion level and link fluctuation stability are determined based on the communication operation data. Based on the parameter reverse adjustment frequency, configuration rollback strength, device queue congestion level and link fluctuation stability, generate the state fusion factor corresponding to the current sliding time window; The parameter variability vector is fused using the state fusion factor to obtain a parameter variability state that characterizes the intensity of changes in the time dimension of communication parameters.

[0009] In some embodiments, for each candidate configuration scheme, perturbation mapping processing is performed on the parameter variability state to determine the configuration perturbation potential energy of the candidate configuration scheme, specifically including: For each candidate configuration scheme, a comparison is performed item by item based on the current communication parameter configuration to determine the target communication parameter whose value has changed and the parameter offset corresponding to each target communication parameter; Based on the variability state of the parameters, determine the activity level of each target communication parameter within the current sliding time window; Based on the parameter offset and change activity corresponding to each target communication parameter, the initial disturbance amount corresponding to each target communication parameter is determined; Based on the service carrying status of the target communication object, determine the service disturbance amplification coefficient corresponding to each target communication parameter; The initial disturbance of the target communication parameter is diffused to the associated communication parameters of the target communication parameter to obtain the diffused disturbance of each associated communication parameter. Potential energy is pooled from all initial disturbances, service disturbance amplification coefficients, and diffusion disturbances to obtain the configuration disturbance potential energy corresponding to the candidate configuration scheme.

[0010] In some embodiments, generating a parameter release strategy based on the configuration perturbation potential energy corresponding to each candidate configuration scheme specifically includes: For each candidate configuration scheme, performance evolution is extrapolated based on the communication operation data of the target communication object, business scenario tags, and link resource status to obtain the expected performance gain of the candidate configuration scheme. Based on the parameter offset between the candidate configuration scheme and the current communication parameter configuration, the effective range of the configuration, and the device execution state of the target communication object, the switching disturbance is calculated to obtain the configuration switching cost of the candidate configuration scheme. The configuration disturbance potential, expected performance gain, and configuration switching cost of each candidate configuration scheme are jointly ranked to determine the parameter release strategy with the highest comprehensive evaluation value.

[0011] In some embodiments, according to the parameter release strategy, issuing communication parameter configuration instructions to the target communication object through the SDN controller and triggering parameter variability state updates specifically includes: The optimal parameter release strategy is parsed to generate segmented communication parameter configuration instructions, and the communication parameter configuration instructions are sent to the target communication object through the southbound interface of the SDN controller. After the communication parameter configuration command takes effect, the operation feedback data is collected, and it is determined whether the operation feedback data meets the preset update conditions. If it does not meet the conditions, the configuration rollback is triggered and the corresponding parameter release strategy is reset. Otherwise, the parameter variability status is updated.

[0012] Secondly, this application provides an adaptive configuration system for variable communication parameters in a communication system, used to execute an adaptive configuration method for variable communication parameters in a communication system, including: The data acquisition module is used to acquire the communication operation data and current communication parameter configuration of the target communication object through the southbound interface of the SDN controller; The deduction and analysis module is used to perform scenario-based deduction on the communication operation data, generate multiple candidate configuration schemes for the target communication object, and perform trajectory analysis based on the current communication parameter configuration to obtain the parameter variability state. The strategy generation module is used to perform perturbation mapping processing on the parameter variability state for each candidate configuration scheme, determine the configuration perturbation potential energy of the candidate configuration scheme, and then generate a parameter release strategy based on the configuration perturbation potential energy corresponding to each candidate configuration scheme. The configuration update module is used to send communication parameter configuration instructions to the target communication object through the SDN controller and trigger parameter variability state updates according to the parameter release strategy.

[0013] Thirdly, this application provides a computer device, the computer device including a memory and a processor, the memory storing code, and the processor being configured to acquire the code and execute the above-described adaptive configuration method for variable communication parameters in a communication system.

[0014] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described adaptive configuration method for variable communication parameters in a communication system.

[0015] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects: This application provides a system and method for adaptive configuration of variable communication parameters in a communication system. The system obtains communication operation data and current communication parameter configuration of the target communication object through the southbound interface of the SDN controller. It then performs scenario-based deduction on the communication operation data to generate multiple candidate configuration schemes for the target communication object. Based on the current communication parameter configuration, it performs trajectory analysis to obtain the parameter variability state. For each candidate configuration scheme, it performs perturbation mapping processing on the parameter variability state to determine the configuration perturbation potential energy of the candidate configuration scheme. Based on the configuration perturbation potential energy corresponding to each candidate configuration scheme, it generates a parameter release strategy. According to the parameter release strategy, the SDN controller issues a communication parameter configuration command to the target communication object and triggers a parameter variability state update.

[0016] Therefore, this application demonstrates that, firstly, by classifying business scenarios, the generation of candidate configuration schemes becomes scenario-specific, avoiding response delays during scenario switching; multi-parameter linkage correction ensures the physical feasibility of candidate schemes; generating multiple combinations according to preset step sizes ensures that candidate schemes cover different adjustment ranges; by analyzing the historical change trajectory of each communication parameter, the temporal dimension change characteristics of each communication parameter can be quantified; then, by comparing each item to determine the target communication parameter and its offset, the disturbance assessment can be accurate to the granularity of a single parameter, avoiding the coarse-grained assessment method that treats all parameters equally; and finally, the configuration... The evaluation incorporates disturbance potential energy, expected performance gain, and configuration switching cost, ensuring that the selection of candidate configuration schemes takes into account the three dimensions of benefit, cost, and disturbance. The differentiated release strategy allows high-disturbance configurations to have a longer effective transition period. The step-by-step effective mechanism breaks down high-disturbance configurations into multiple low-disturbance sub-steps, making high-benefit schemes feasible under the premise of controlled disturbance. Finally, the segmented distribution mechanism allows high-disturbance configurations to take effect gradually at a controlled pace. The stable observation period between each instruction segment provides a time window for configuration impact assessment, reducing operational oscillations caused by simultaneous changes in batch parameters and ensuring the stable operation of communication objects.

[0017] In summary, the technical solution adopted in this application can adaptively adjust communication parameters to achieve controlled disturbance configuration, thereby improving communication stability. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only for this embodiment of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1This is an exemplary flowchart of an adaptive configuration method for variable communication parameters in a communication system according to some embodiments of this application; Figure 2 This is a schematic diagram illustrating an application scenario of an adaptive configuration method for variable communication parameters in a communication system, as shown in some embodiments of this application. Figure 3 This is an exemplary flowchart illustrating the determination of the configuration perturbation potential energy of candidate configuration schemes according to some embodiments of this application; Figure 4 This is a schematic diagram of the structure of an adaptive configuration system for variable communication parameters in a communication system according to some embodiments of this application; Figure 5 This is a schematic diagram of the structure of a computer device that implements an adaptive configuration method for variable communication parameters in a communication system, according to some embodiments of this application. Detailed Implementation

[0020] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0021] This application provides an adaptive configuration system and method for variable communication parameters in a communication system. The core of this system is to acquire the communication operation data and current communication parameter configuration of a target communication object through the southbound interface of an SDN controller; perform scenario-based deduction on the communication operation data to generate multiple candidate configuration schemes for the target communication object; perform trajectory analysis based on the current communication parameter configuration to obtain the parameter variability state; for each candidate configuration scheme, perform perturbation mapping processing on the parameter variability state to determine the configuration perturbation potential energy of the candidate configuration scheme; and then generate a parameter release strategy based on the configuration perturbation potential energy corresponding to each candidate configuration scheme; according to the parameter release strategy, the SDN controller issues a communication parameter configuration command to the target communication object and triggers a parameter variability state update. Using this scheme, communication parameters can be adaptively adjusted to achieve perturbation-controlled configuration, thereby improving communication stability.

[0022] To better understand the above technical solutions, a detailed description of the technical solutions will be provided below in conjunction with the accompanying drawings and specific embodiments. (Refer to...) Figure 1 The figure is an exemplary flowchart of an adaptive configuration method for variable communication parameters in a communication system according to some embodiments of this application. The figure mainly includes the following steps: In step S101, the communication operation data and current communication parameter configuration of the target communication object are obtained through the southbound interface of the SDN controller.

[0023] In some embodiments, obtaining the communication operation data and current communication parameter configuration of the target communication object through the southbound interface of the SDN controller can be achieved in the following ways: Collect communication status monitoring data and the current configuration table stored locally on the device from the forwarding device, access device or edge gateway corresponding to the target communication object; The communication status monitoring data is preprocessed to generate communication operation data corresponding to the current sliding time window; The current configuration table is associated with the communication operation data to obtain the current communication parameter configuration of the target communication object.

[0024] In this application, Figure 2 This is a schematic diagram of an application scenario for an adaptive configuration method for variable communication parameters in a communication system according to some embodiments of this application; as shown in the figure: the SDN controller collects communication status monitoring data and the current configuration table output by the forwarding device, access device, and edge gateway corresponding to the target communication object through the southbound interface.

[0025] It should be noted that the southbound interface is a dedicated communication interface for interaction between the SDN controller and forwarding devices, used to issue configuration commands and collect device status information. The interface protocol can be at least one of the OpenFlow, NETCONF, and gRPC protocols. The communication operation data is preprocessed device operation statistics organized according to a fixed sliding window, used to characterize the network operation characteristics of the target communication object within the window period. The current communication parameter configuration is the complete set of parameters currently in effect for the target communication object.

[0026] In specific implementation, firstly, the SDN controller establishes a connection with the forwarding device, access device, or edge gateway corresponding to the target communication object through the southbound interface, and configures interface parameters, including the collection period, interface response timeout threshold, and collection failure retry strategy. The collection period is determined by considering the target communication object's service scenario, network fluctuation frequency, and sliding time window duration. The interface response timeout threshold is determined based on the transmission latency characteristics of the southbound interface protocol and the link transmission distance between the target communication object and the SDN controller. The collection failure retry strategy is determined by considering the interface response timeout threshold and the service's requirements for data integrity, employing a conventional communication retry mechanism of "fixed number of attempts + exponential backoff." The number of retries is set to 2-3, with each retry interval increasing by a factor of 2, for example, an initial interval of 50ms, a second interval of 100ms. If the maximum number of retries is reached and the retry still fails, the data is marked as invalid and subsequently compensated through interpolation. The southbound interface automatically adapts to the corresponding communication protocol based on the target communication object's device type, and then the SDN controller, according to the preset collection period, collects data through the southbound interface. The SDN controller collects communication status monitoring data reported by the southbound interface. This data includes link telemetry data, service queue data, and port status data. Link telemetry data is collected by the device's built-in performance measurement module or out-of-band telemetry mechanism, characterizing the operating status of the corresponding transmission link. Indicators include link bandwidth utilization, link transmission latency, jitter, and packet loss rate. Service queue data is read from the device's queue management module's real-time statistical results, characterizing the queuing status of service packets. Indicators include queue length, queue occupancy rate, and average packet queuing time. Port status data is obtained by reading the device's physical layer and link layer status registers, characterizing the working status of the port corresponding to the target communication object. Indicators include port transmit / receive rate and the number of port error packets. Simultaneously, the SDN controller reads the current configuration table stored in the local configuration database of the forwarding device, access device, or edge gateway corresponding to the target communication object through the southbound interface. This configuration table records all currently effective communication parameter items and their corresponding values ​​for the target communication object under the corresponding device.

[0027] In addition, in specific implementation, the SDN controller performs standardized preprocessing on the collected communication status monitoring data: using the local system clock of the SDN controller as a unified reference, the timestamps of data reported by multiple devices are aligned and calibrated to eliminate cross-device time offset errors; the integrity of all data items and the legality of message format are verified, and invalid data with failed acquisition or incorrect format are removed; out-of-range abnormal values ​​are identified and removed according to the preset physical upper and lower limits of each indicator, and linear interpolation is used to complete numerical compensation for the missing sampling points generated after data removal; after completing all preprocessing, all valid data are normalized according to a fixed duration sliding window, where the window duration ranges from 60s to 300s, and a fixed sliding step size is set synchronously. The normalized data set is the communication operation data of the corresponding window. Finally, using the target communication object identifier and the device unique identifier as the association primary keys, all parameter items in the current configuration table are bound one-to-one with the communication status monitoring data of the corresponding device under the same sliding window. The bound parameters and operating status are integrated to obtain the current communication parameter configuration of the target communication object. Specifically, the parameter items in the current configuration table are mapped one-to-one with the communication status monitoring data. The parameter items in the current configuration table include network layer parameters such as forwarding path and bandwidth control, as well as air interface transmission layer parameters such as modulation and coding scheme and transmit power. The air interface transmission layer parameters correspond to link telemetry data, and the network layer parameters correspond to service queue data and port status data to ensure that each parameter has operating status feedback.

[0028] In step S102, the communication operation data is subjected to scenario-based simulation to generate multiple candidate configuration schemes for the target communication object. Based on the current communication parameter configuration, trajectory analysis is performed to obtain the parameter variability state.

[0029] In some embodiments, the scenario-based simulation of the communication operation data to generate multiple candidate configuration schemes for the target communication object can be performed in the following manner: Based on the communication operation data, identify the business scenario tag of the target communication object; Obtain the parameter template that matches the business scenario tag; By combining link constraints, service priorities, and device-side resource reserves, the parameter template is modified through multi-parameter linkage to generate multiple candidate configuration schemes that meet preset feasibility constraints.

[0030] It should be noted that the business scenario tag is used to characterize the communication requirement type of the current service carried by the target communication object, including any one of low latency service scenario, high throughput service scenario, high reliability service scenario, burst traffic service scenario and multi-service mixed carrying scenario; the parameter template is a combination of baseline communication parameters pre-configured during the system initialization phase and corresponding one-to-one with each business scenario tag; the device-side resource margin specifically refers to the device's available computing resources, available cache resources and available power resources.

[0031] In practice, the SDN controller first inputs communication operation data into a pre-trained scenario classifier. This scenario classifier is a binary and multi-class classification model trained based on the random forest algorithm. The training samples are the feature sets of communication operation data corresponding to each business scenario, including core indicators such as link bandwidth utilization, queue length, and latency. After training, the data is stored in the local model library of the SDN controller. Based on the input communication operation data, the scenario classifier outputs the business scenario label that best matches the target communication object within the current time window through feature matching. The matching threshold is determined comprehensively based on the training and verification results of the scenario classifier, the accuracy requirements of communication scenario recognition, and the feasibility of engineering implementation. It can be set to 85%, that is, when the feature matching degree is ≥85%, it is determined as the corresponding scenario label. Secondly, the SDN controller retrieves a baseline parameter template that matches the service scenario label from the parameter template library. During the system initialization phase, the parameter template library is pre-generated and stored in the local storage module of the SDN controller based on the optimal parameter combination for various service scenarios. Each service scenario corresponds to a unique baseline parameter template, which contains the baseline values ​​and value ranges of each communication parameter in that scenario. For example, in a low-latency service scenario, the baseline value for the modulation and coding scheme is QPSK, and the baseline value for the transmit power is 10dBm.

[0032] In addition, in specific implementation, the SDN controller combines the available bandwidth, maximum latency, and maximum packet loss rate of the current link with the service priority and device-side resource availability to collaboratively correct the parameters in the benchmark parameter template. The specific constraint standards are: available bandwidth ≥ 1.2 times the bandwidth currently occupied by the service; maximum latency ≤ service-required latency; maximum packet loss rate ≤ 0.1%. The service priority is determined based on the latency sensitivity, reliability requirements, and importance of the service carried by the target communication object, combined with the service attribute information in the communication operation data. The service level is divided into 5 levels, with level 1 being the highest priority. For services with higher priority, their communication needs are prioritized during parameter adjustments; the available computing resources, available cache resources, and available power resources in the device-side resource reserves are ≥10%, ≥15%, and ≥20%, respectively. The adjustment process strictly follows these rules: if a parameter is adjusted, related parameters will be adjusted synchronously according to a preset parameter coupling matrix. This parameter coupling matrix is ​​jointly updated by historical configuration feedback results and cross-layer linkage results. The matrix clearly records the linkage adjustment coefficients between each parameter. For example, when the transmit power adjustment range is ±2dBm, the transmission bandwidth is synchronously adjusted by ±5MHz. This linkage adjustment avoids parameter combinations that are not feasible. To generate multiple candidate configuration schemes that meet the requirements, The SDN controller executes the following steps: For adjustable parameters in the baseline parameter template, such as transmit power, transmission bandwidth, and modulation / coding scheme, within the device's supported value range for each parameter, multiple sets of different parameter adjustment values ​​are generated according to a preset adjustment step size. The preset adjustment step size references conventional engineering standards for parameter configuration in the communications field and is pre-set in conjunction with the multi-parameter linkage correction requirements of this scheme. This ensures that the step size setting covers different parameter adjustment ranges, generates sufficient candidate configuration schemes, and avoids an excessive number of candidate schemes due to an excessively small step size, increasing the computational load for subsequent disturbance evaluation, or an incomplete coverage of candidate schemes due to an excessively large step size. For example, transmit power is adjusted according to... The parameters are adjusted in ±2dBm increments, the transmission bandwidth in ±5MHz increments, and the modulation and coding scheme is adjusted in order gradients, for example, from QPSK to 16QAM and then to 64QAM. For each set of parameter adjustment values, the associated parameters are adjusted synchronously in conjunction with the parameter coupling matrix to generate a complete set of parameter combinations. After the parameter collaborative correction is completed, the SDN controller generates multiple sets of parameter combinations with different values, and then performs feasibility screening on all parameter combinations. The screening criteria are: the parameter values ​​are within the range supported by the device, the configuration changes do not violate the link constraints, and the device-side resource margin requirements are met. All parameter combinations that meet the screening criteria are used as multiple candidate configuration schemes for the target communication object.

[0033] It should be noted that mapping the current running status to typical scenario tags by classifying business scenarios can make the generation of candidate configuration schemes scenario-specific, avoiding response delays when general parameter adjustment methods switch scenarios; multi-parameter linkage correction can ensure the physical feasibility of candidate schemes and avoid configuration failure due to infeasible parameter combinations; adjusting parameters according to preset step sizes and generating multiple combinations can ensure that the number of generated candidate configuration schemes is sufficient and covers different parameter adjustment ranges.

[0034] In some embodiments, trajectory parsing based on the current communication parameter configuration to obtain the parameter variability state can be performed in the following manner: Based on the current communication parameter configuration and the historical communication parameter configuration, a parameter change trajectory is constructed, and then core temporal features are extracted from the parameter change trajectory; The core temporal features are scaled to form a parameter variability vector. The parameter reverse adjustment frequency and configuration rollback strength are determined based on the parameter change trajectory sequence, and the device queue congestion level and link fluctuation stability are determined based on the communication operation data. Based on the parameter reverse adjustment frequency, configuration rollback strength, device queue congestion level and link fluctuation stability, generate the state fusion factor corresponding to the current sliding time window; The parameter variability vector is fused using the state fusion factor to obtain a parameter variability state that characterizes the intensity of changes in the time dimension of communication parameters.

[0035] It should be noted that the parameter change trajectory is a sequence of changes in the current communication parameter configuration and the historical communication parameter configuration on the time axis, used to characterize the evolution of the target communication object's communication parameters over time; the core temporal features are used to characterize the time dimension change characteristics of the parameters; the parameter reverse adjustment frequency is used to characterize the number of times the communication parameters undergo directional reversal between adjacent time windows; the configuration rollback intensity is used to characterize the magnitude of the parameter configuration returning to the previous configuration state; and the state fusion factor is used to adjust the weighting coefficients of each dimension in the parameter variability vector to reflect the actual constraints of the current operating state on parameter variability.

[0036] In specific implementation, firstly, the SDN controller reads the current communication parameter configuration and the historical communication parameter configurations of the most recent preset number of historical time windows from the local configuration database, such as the most recent 60 historical time windows. Using time as the horizontal axis and the parameter values ​​as the vertical axis, the parameter configurations of each time window are arranged sequentially according to time, forming a separate parameter change trajectory for each communication parameter, ultimately creating a sequence of parameter change trajectories corresponding to each communication parameter. Further, for each parameter change trajectory sequence corresponding to each communication parameter, the core temporal features of the communication parameter on the time axis are extracted one by one. These core temporal features specifically include the change frequency, change amplitude, and change direction. These core temporal features are extracted separately for each communication parameter, and the core temporal features of different communication parameters are independent of each other. The change frequency is the number of times the parameter changes per unit time, which is consistent with the duration of the sliding time window. The change amplitude is the maximum deviation of the parameter value from its mean, where the parameter mean is the average value of the parameter within the most recent 60 historical time windows. The change direction is divided into three types: parameter value increase, parameter value decrease, and parameter value remain unchanged. Secondly, to avoid the impact of different communication parameters on subsequent fusion processing due to differences in units, value ranges, or sampling periods, the core time series features are scale-consistentized according to preset normalization intervals or standardization rules corresponding to various time series features. The preset normalization interval is 0 to 1, and the standardization rule is to subtract the minimum value from each time series feature value and then divide by the difference between the maximum and minimum values. This process converts core time series features at different scales into feature values ​​at the same numerical scale. After the conversion, a parameter variability vector is formed. This parameter variability vector is a vector generated separately for each communication parameter, used to individually characterize the magnitude, frequency, and stability of the parameter's changes within the current sliding time window.

[0037] Then, the number of times the direction of each communication parameter reversed within the most recent time window is counted to obtain the parameter reverse adjustment frequency for each communication parameter. Parameter direction reversal is specifically defined as the opposite direction of change of the same parameter within adjacent time windows. For example, if the parameter value increases in the previous window and decreases in the next window, it is determined as one direction reversal. The total number of such reversals is counted as the parameter reverse adjustment frequency. The number and magnitude of the reversion of each communication parameter configuration to its previous configuration state are also counted to obtain the configuration rollback strength for each communication parameter. The previous configuration state specifically refers to the parameter configuration that appeared within the most recent 60 historical time windows. The parameter configuration response magnitude is the absolute value of the difference between the current parameter value and the previously configured value. The rollback strength is calculated using the formula "(rollback count × average rollback magnitude) / parameter value range". Here, the average rollback magnitude is the average of the absolute values ​​of the parameter value differences across all rollback operations, and the parameter value range is the range of hardware-supported values ​​for the corresponding communication parameter on the target communication object's device, obtainable from the device manual or device attribute information read from the southbound interface. Based on the queue length and queuing delay in the communication operation data, the device queue congestion level is determined. This congestion level is a measure of the overall operation of the target communication object. The congestion level is not based on a single communication parameter. The specific criteria are as follows: Low congestion occurs when queue length ≤ preset queue length threshold (preset to 60% of device buffer capacity) and queuing delay ≤ preset delay threshold (preset to 50ms); Medium congestion occurs when queue length is between the preset queue length threshold and 80% of device buffer capacity, and queuing delay is between the preset delay threshold and 100ms; High congestion occurs when queue length > 80% of device buffer capacity or queuing delay > 100ms. Low, medium, and high congestion levels are quantified as 0.2, 0.5, and 0.8 respectively. The stability of the link is determined by the changes in latency jitter and packet loss rate in the operational data. This stability is an indicator of the overall operational status of the target communication object, not for a single communication parameter. When the latency jitter fluctuation amplitude is ≤5ms and the packet loss rate change amplitude is ≤0.05%, the stability is high; when the latency jitter fluctuation amplitude is between 5ms and 10ms and the packet loss rate change amplitude is between 0.05% and 0.1%, the stability is medium; when the latency jitter fluctuation amplitude is >10ms or the packet loss rate change amplitude is >0.1%, the stability is low. The high, medium, and low stability are quantified as 0.8, 0.5, and 0.2, respectively.

[0038] In addition, in the specific implementation, for each communication parameter, its corresponding parameter reverse adjustment frequency and configuration rollback strength are weighted and summed with the overall device queue congestion level and link fluctuation stability of the target communication object according to the preset fusion weights to generate the state fusion factor corresponding to each communication parameter within the current sliding time window. The preset fusion weight allocation is as follows: parameter reverse adjustment frequency is 0.2, configuration rollback strength is 0.2, device queue congestion level is 0.3, and link fluctuation stability is 0.3. The normalized value of parameter reverse adjustment frequency is parameter reverse adjustment frequency divided by the maximum possible number of reversals. The maximum possible number of reversals is the sliding time window duration divided by the parameter acquisition period, ensuring that the value of the state fusion factor corresponding to each communication parameter falls within the range of 0 to 1. Finally, for each communication parameter, the eigenvalues ​​of each dimension in the parameter variability vector corresponding to the communication parameter are multiplied by the state fusion factor corresponding to the parameter to obtain the weighted eigenvalues ​​of each dimension. Then, all weighted eigenvalues ​​are summed to obtain the parameter variability state of the communication parameter. The value ranges from 0 to 1. The closer the value is to 1, the greater the intensity of the change in the time dimension of the communication parameter and the more unstable the parameter state. The closer the value is to 0, the smaller the intensity of the change in the time dimension of the communication parameter and the more stable the parameter state.

[0039] It should be noted that by analyzing the historical change trajectory of each communication parameter, the time-dimensional change characteristics of each communication parameter can be quantified. Introducing the reverse adjustment frequency of parameters and the rollback strength of configurations allows each communication parameter to identify its own abnormal adjustment patterns such as frequent oscillations and repeated rollbacks, avoiding the introduction of additional disturbances when a single parameter is in an unstable state. Introducing the device queue congestion level and link fluctuation stability allows the determination of the parameter variability state of each communication parameter, combined with the overall operating status of the target communication object, to distinguish between parameter adjustments caused by device or link instability and parameter adjustments caused by normal scenario switching.

[0040] In step S103, for each candidate configuration scheme, the parameter variability state is perturbed and mapped to determine the configuration perturbation potential energy of the candidate configuration scheme, and then a parameter release strategy is generated based on the configuration perturbation potential energy corresponding to each candidate configuration scheme.

[0041] Preferably, in some embodiments, reference is made to Figure 3 As shown, this figure is an exemplary flowchart illustrating the determination of the configuration perturbation potential energy of a candidate configuration scheme according to some embodiments of this application. In this embodiment, for each candidate configuration scheme, the parameter variability state is perturbed and mapped to determine the configuration perturbation potential energy of the candidate configuration scheme, which can be achieved by the following steps: In step S1031, for each candidate configuration scheme, a comparison is performed item by item based on the current communication parameter configuration to determine the target communication parameter whose value has changed and the parameter offset corresponding to each target communication parameter. In step S1032, the activity level of each target communication parameter within the current sliding time window is determined based on the parameter variability state. In step S1033, the initial disturbance amount corresponding to each target communication parameter is determined based on the parameter offset and change activity corresponding to each target communication parameter. In step S1034, the service disturbance amplification coefficient corresponding to each target communication parameter is determined according to the service bearer status of the target communication object; In step S1035, the initial disturbance amount corresponding to the target communication parameter is diffused to the associated communication parameters of the target communication parameter to obtain the diffused disturbance amount corresponding to each associated communication parameter. In step S1036, the potential energy of all initial disturbances, service disturbance amplification coefficients and diffusion disturbances is pooled to obtain the configuration disturbance potential energy corresponding to the candidate configuration scheme.

[0042] It should be noted that the parameter offset is used to characterize the degree of change of the target communication parameter value relative to the current configuration in the candidate configuration scheme; the change activity is used to characterize the frequency of changes of the target communication parameter within the current sliding time window, and its value is consistent with the value of the parameter variability state; the initial disturbance is used to characterize the initial disturbance intensity introduced by the value change of a single target communication parameter; the service disturbance amplification coefficient is used to characterize the amplification effect of parameter change on service performance under the current service carrying state of the target communication object; the associated communication parameter refers to the communication parameter that has a configuration linkage relationship or operational influence relationship with the target communication parameter, and the configuration linkage relationship or operational influence relationship can be determined by a preset parameter coupling relationship table; the diffusion disturbance is used to characterize the disturbance intensity after the initial disturbance of the target communication parameter is transmitted to the associated communication parameter through the coupling relationship; the configuration disturbance potential energy is used to characterize the overall impact on system stability when the candidate configuration scheme is switched relative to the current configuration.

[0043] In practice, firstly, for each candidate configuration scheme, the values ​​of each communication parameter in the scheme are compared item by item with the corresponding parameter values ​​in the current communication parameter configuration. The comparison covers all parameter items in the current communication parameter configuration. Parameters whose values ​​have changed are marked as target communication parameters. The difference between the value of each target communication parameter in the candidate scheme and the current value is calculated as the parameter offset of the target communication parameter. For numerical communication parameters, such as transmit power and transmission bandwidth, the parameter offset is the normalized difference between the target value and the current value, ensuring that the parameter offset value falls within the range of -1 to 1. For enumerated communication parameters, such as modulation and coding schemes and forwarding paths, the parameter offset is determined according to a preset enumeration state difference level. The preset enumeration state difference level is divided into 3 levels, which are based on the degree of impact of parameter changes on system performance. The greater the degree of impact, the higher the difference level and the larger the parameter offset, corresponding to parameter offsets of 0.3, 0.6, and 1.0, respectively. Secondly, for each target communication parameter, the final value of the parameter variability state corresponding to that parameter is extracted as the parameter's activity level. A higher activity level indicates that the parameter has changed more frequently recently, with a value range of 0 to 1. Then, the absolute value of the parameter offset of each target communication parameter is multiplied by its activity level to obtain the initial perturbation amount of that target communication parameter, so that communication parameters with larger parameter adjustment amplitudes and higher activity levels correspond to larger initial perturbation amounts. Next, the service disturbance amplification coefficient corresponding to each target communication parameter is determined based on the service carrying status of the target communication object. The service carrying status includes the currently carried service type, service priority, service bandwidth utilization, and service latency sensitivity level. The specific determination criteria are as follows: when carrying Level 1 real-time services (representing the highest priority), with a service bandwidth utilization ≥80% or a high service latency sensitivity level, the service disturbance amplification coefficient is 3; when carrying Level 2-3 services, with a service bandwidth utilization between 50% and 80% or a medium service latency sensitivity level, the service disturbance amplification coefficient is 2; when carrying Level 4-5 services, with a service bandwidth utilization <50% or a low service latency sensitivity level, the service disturbance amplification coefficient is 1. The criteria for determining the service latency sensitivity level are as follows: high sensitivity level corresponds to a service latency requirement ≤50ms, medium sensitivity level corresponds to a service latency requirement between 50ms and 100ms, and low sensitivity level corresponds to a service latency requirement >100ms.

[0044] In addition, in specific implementation, based on a preset parameter coupling relationship table, the associated communication parameters and coupling strength corresponding to each target communication parameter are determined. This parameter coupling relationship table is consistent with the parameter coupling matrix and is pre-stored in the local storage module of the SDN controller. The table clearly records the coupling relationship and coupling strength level between each communication parameter. The initial disturbance of each target communication parameter is diffused to its associated communication parameters. For each associated communication parameter, the disturbance diffusion ratio is determined according to the coupling strength between it and the target communication parameter. The coupling strength is divided into three levels: strong, medium, and weak, corresponding to diffusion ratios of 50%, 30%, and 50%, respectively. The coupling strength is determined by the degree of influence of the linkage adjustment between parameters. An influence degree of ≥80% is considered strong coupling, an influence degree between 30% and 80% is considered medium coupling, and an influence degree of <30% is considered weak coupling. The degree of influence can be calculated by comparing the performance difference before and after parameter adjustment using historical configuration feedback data, or it can be determined by referring to conventional parameter coupling standards in the communication field. The initial disturbance amount of the target communication parameter is allocated to the associated communication parameter according to the corresponding proportion, which is used as the diffusion disturbance amount of the associated communication parameter. The value range is 0 to 1. The larger the value, the stronger the disturbance to the associated parameter. Finally, the initial disturbance of each target communication parameter is amplified. Specifically, the initial disturbance of each target communication parameter is multiplied by the service disturbance amplification factor corresponding to that parameter. The result is the amplified initial disturbance of each target communication parameter. The amplified initial disturbances of all target communication parameters are summed, and the diffusion disturbances corresponding to all associated communication parameters are summed. The sum of these two sums is the configuration disturbance potential energy corresponding to the candidate configuration scheme. The value range of the configuration disturbance potential energy is 0 to 100. The higher the value, the greater the overall impact of the candidate configuration scheme on system stability during the switching process.

[0045] It should be noted that by comparing each parameter to determine the target communication parameters and their offsets, the disturbance assessment can be accurate to the granularity of individual parameters, avoiding the coarse-grained assessment method that treats all parameters equally. The introduction of change activity allows frequently changing parameters to receive higher initial disturbance amounts, thereby suppressing the behavior of repeatedly adjusting the same set of parameters. The service disturbance amplification factor enables the disturbance assessment to distinguish the differences in the sensitivity of different service types to parameter changes. The disturbance diffusion processing allows the coupling relationship between parameters to be included in the disturbance assessment, avoiding the neglect of the joint disturbance effect caused by changes in related parameters.

[0046] In some embodiments, the parameter release strategy is generated based on the configuration perturbation potential energy corresponding to each candidate configuration scheme in the following manner: For each candidate configuration scheme, performance evolution is extrapolated based on the communication operation data of the target communication object, business scenario tags, and link resource status to obtain the expected performance gain of the candidate configuration scheme. Based on the parameter offset between the candidate configuration scheme and the current communication parameter configuration, the effective range of the configuration, and the device execution state of the target communication object, the switching disturbance is calculated to obtain the configuration switching cost of the candidate configuration scheme. The configuration disturbance potential, expected performance gain, and configuration switching cost of each candidate configuration scheme are jointly ranked to determine the parameter release strategy with the highest comprehensive evaluation value.

[0047] It should be noted that the expected performance gain is used to characterize the performance improvement expected to be obtained after the candidate configuration scheme is executed; the configuration switching cost is used to characterize the execution cost required for the candidate configuration scheme to switch from the current configuration to the target configuration; the parameter release strategy is used to control the way the target communication parameter configuration is issued and the effective rhythm, including the immediate effective strategy, the step-by-step effective strategy, and the delayed effective strategy.

[0048] In practice, firstly, for each candidate configuration scheme, the parameter configurations in that scheme are substituted into the current runtime environment model. This runtime environment model is constructed from the communication operation data of the target communication object, service scenario tags, and link resource status. The link resource status is based on link telemetry data and also includes resource-related information such as remaining available bandwidth, link occupancy rate, and link resource allocation priority. This information can be derived from link telemetry data combined with link resource statistics reported by the device. This runtime environment model is pre-stored in the local model library of the SDN controller. The model explicitly includes the correlation mapping relationship between each parameter configuration and system performance indicators. The system performance under the candidate configuration scheme is simulated using this model, and the throughput, latency, and reliability—three core performance indicators—are measured. Then, the measured results of each indicator are compared with the corresponding values ​​under the current communication parameter configuration. The numerical values ​​of the indicators are compared to calculate the improvement of each indicator relative to the current configuration. Then, the improvement values ​​are normalized to ensure that the normalized gain values ​​fall within the range of 0 to 1. The three normalized gains are then weighted and summed according to preset gain weights, where the preset gain weights are allocated as follows: throughput gain 40%, latency reduction gain 30%, and reliability gain 30%. The calculation result is the expected performance gain of the candidate configuration scheme, with a value range of 0 to 1. The higher the value, the more significant the system performance improvement brought about by the implementation of the candidate configuration scheme. The calculation methods for throughput, latency, and reliability can refer to the conventional testing standards in the field of communications. Throughput is calculated by the amount of data successfully transmitted per unit time, latency is calculated by the transmission time of data from the sender to the receiver, and reliability is calculated by the data transmission success rate.

[0049] In practice, the cost of performing the configuration switch is evaluated based on the parameter offset between the candidate configuration scheme and the current communication parameter configuration, the scope of the configuration, and the device execution status of the target communication object. Specifically, since the parameter offset directly determines the signaling overhead of parameter issuance, the larger the absolute value of the parameter offset and the more parameters involved, the greater the signaling overhead required for parameter issuance. The scope of the configuration directly determines the reconfiguration time for the device to apply the new configuration. The larger the scope of the configuration, for example, the more devices, ports, and service flows involved, the longer the reconfiguration time required for the device to complete the loading and activation of the new configuration. The device execution status of the target communication object directly affects the service interruption duration during the configuration switch, and also indirectly affects the signaling overhead and reconfiguration time. Therefore, the evaluated cost includes the signaling overhead required for parameter issuance, the device execution status, and the cost of the device execution status. The specific evaluation methods for each cost, including the reconfiguration time required for the new configuration and the potential service interruption duration during the configuration switchover, are as follows: signaling overhead is calculated by statistically analyzing the number of signaling messages exchanged during parameter distribution and the size of each message; reconfiguration time is calculated by statistically analyzing the configuration loading time reported by the device; service interruption duration is calculated by analyzing the time difference between service traffic interruptions before and after the configuration switchover; after completing the specific calculation of each cost, each cost is normalized, with a value range of 0 to 1; the three normalized costs are then weighted and summed according to preset cost weights, where the preset cost weights are allocated as follows: parameter distribution overhead accounts for 20%, device reconfiguration time accounts for 40%, and service interruption duration accounts for 40%; the result is the configuration switchover cost of the candidate configuration scheme, with a value range of 0 to 1. The higher the value, the greater the cost required to perform the configuration switchover.

[0050] In addition, in specific implementation, the configuration disturbance potential energy, expected performance gain, and configuration switching cost corresponding to each candidate configuration scheme are jointly ranked; the configuration disturbance potential energy, expected performance gain, and configuration switching cost are weighted according to preset weights, where the expected performance gain corresponds to a positive evaluation weight, and the configuration disturbance potential energy and configuration switching cost correspond to negative evaluation weights. All three weights are determined comprehensively based on the engineering practice requirements of communication network parameter configuration, the priority of each indicator's impact on system operation, and historical configuration feedback data; the weighted calculation result is used as the comprehensive evaluation value of each candidate configuration scheme; and the candidate configuration scheme with the highest comprehensive evaluation value is determined as the target candidate configuration. The scheme generates a parameter release strategy based on the target communication parameters, parameter offsets, configuration disturbance potential energy, and configuration switching cost corresponding to the target candidate configuration scheme. The parameter release strategy specifically includes the communication parameters to be released, the parameter release order, the single release amplitude, the release time interval, and the release termination condition. The specific requirements for each element are as follows: the communication parameters to be released are all the target communication parameters determined in the target candidate configuration scheme; the parameter release order is sorted from low to high according to the disturbance degree of each target communication parameter, and the disturbance degree is determined by the initial disturbance amount corresponding to each target communication parameter; the single release amplitude is the number of communication parameters to be released in each group, combined with the configuration disturbance potential energy level.

[0051] The specific release method is determined based on the configured disturbance potential energy level: The preset first threshold is 30, and the second threshold is 60. When the configured disturbance potential energy is lower than the first threshold, an immediate effect strategy is adopted, sending all communication parameters to be released at once and making them effective simultaneously. The release termination condition is the completion of all parameters taking effect. When the configured disturbance potential energy is between the first and second thresholds, a step-by-step effect strategy is adopted. Communication parameters to be released are grouped according to the disturbance level from low to high, with each group containing 1-3 target communication parameters. These are sent and take effect sequentially, with a preset release time interval of 500ms between groups. The release termination condition is the completion of all parameters in each group taking effect or the triggering of an abnormal termination condition, such as a service interruption duration ≥ 500ms. When the configured disturbance potential energy is higher than the second threshold, a delayed effect strategy is adopted, with a preset delay time of 30s. After the delay time is reached, all communication parameters to be released are sent and take effect simultaneously. The release termination condition is the completion of all parameters taking effect or the triggering of an abnormal termination condition.

[0052] It should be noted that by jointly incorporating configuration disturbance potential, expected performance gain, and configuration switching cost into the evaluation, the selection of candidate configuration schemes takes into account the three dimensions of benefit, cost, and disturbance, avoiding the one-sidedness of focusing on only a single dimension; the differentiated release strategy allows high-disturbance configurations to obtain a longer effective transition period, reducing the impact of configuration changes on the communication system; the step-by-step effective mechanism, by breaking down high-disturbance configurations into multiple low-disturbance sub-steps, makes high-benefit but high-disturbance configuration schemes feasible under the premise of controlled disturbance.

[0053] In step S104, according to the parameter release strategy, the SDN controller sends a communication parameter configuration instruction to the target communication object and triggers a parameter variability state update.

[0054] In some embodiments, according to the parameter release strategy, the SDN controller issues communication parameter configuration instructions to the target communication object and triggers parameter variability state updates, which can be done in the following ways: The optimal parameter release strategy is parsed to generate segmented communication parameter configuration instructions, and the communication parameter configuration instructions are sent to the target communication object through the southbound interface of the SDN controller. After the communication parameter configuration command takes effect, the operation feedback data is collected, and it is determined whether the operation feedback data meets the preset update conditions. If it does not meet the conditions, the configuration rollback is triggered and the corresponding parameter release strategy is reset. Otherwise, the parameter variability status is updated.

[0055] In practice, the SDN controller first parses the parameter release policy and generates segmented communication parameter configuration instructions according to the policy type. The immediate-effective policy merges all communication parameters to be released into one instruction segment, carrying an immediate-effective flag conforming to the southbound interface protocol. For the step-effective policy, each instruction segment is assigned an effective sequence number and an effective time interval consistent with the inter-group release time interval. The delayed-effective policy merges all communication parameters to be released into one instruction segment, carrying a delayed-effective flag consistent with the preset delay time. Next, the SDN controller sequentially sends the instructions to the target communication object via the southbound interface according to the instruction segment order. Under the step-effective policy, after sending the first instruction segment, the SDN controller waits for the target communication object to return an effective confirmation message. After confirming the successful effectiveness of the instruction segment and a 200ms stable observation period, the next instruction segment is sent, until all are sent. Both the immediate-effective and delayed-effective policies send the corresponding instruction segments at once. The delayed-effective policy requires waiting for the delay time carried by the instruction segment to arrive before triggering the target communication object to execute the instruction content.

[0056] In addition, in specific implementation, after all instruction segments are executed, the SDN controller collects the operational feedback data after the configuration change of the target communication object through the southbound interface, including configuration execution results, link operation data, service queue operation data, and port operation data. All data can be directly extracted from the device's reported status information. Among them, the configuration execution results are divided into success and failure, which are used to characterize the status of instruction reception, parsing, and effectiveness. Then, it is determined whether the operational feedback data meets the preset update conditions. The preset update conditions are: the configuration execution result is successful, the link latency is ≤50ms, the packet loss rate is ≤0.1%, the queue occupancy rate is ≤80% of the device's buffer capacity, the number of port error packets is ≤1 per 100 packets, and the abnormal fluctuation of the operational indicators after the configuration takes effect is ≤20% compared with the time before the configuration takes effect. If the operational feedback data does not meet any of the preset update conditions, the instruction in the current configuration distribution phase is determined to be in an unacceptable state. The SDN controller immediately triggers a configuration rollback, restoring the current communication parameter configuration before the configuration change. After the rollback is completed, the SDN controller generates a rollback record with the same format as the release disturbance record based on the parameters involved in the rollback, the values ​​before and after the rollback, the triggering reason, and the operational feedback data after the rollback. The parameter release strategy is reset based on this record. The reset methods include: adjusting the single release amplitude (i.e., reducing the number of parameters in each group by 1), extending the release time interval (i.e., extending it by 200ms on the original basis), changing the parameter release order (i.e., rearranging them from low to high according to the initial disturbance amount) or terminating the release of subsequent parameters. The specific method is determined based on the rollback reason: if the disturbance is too large, the release amplitude and time interval are adjusted first; if the parameters are incompatible, the release order is changed first; if multiple rollbacks are ineffective, the release of subsequent parameters is terminated.

[0057] If the operational feedback data meets all preset update conditions, the instructions in the current configuration distribution phase are determined to be in an acceptable effective state. The SDN controller generates a release disturbance record with the same format as the parameter change trajectory sequence mentioned above, based on the identifier, release magnitude, release time, release count, and operational feedback data of the effective parameters. This record is then merged into the trajectory sequence of the corresponding communication parameters. Based on the updated trajectory sequence, the change activity, configuration rollback strength, device queue congestion level, and link fluctuation stability are recalculated according to the steps mentioned above to complete the parameter variability status update. If there are incomplete distribution phases in the parameter release strategy, the SDN controller continues to distribute the instructions for the next phase after meeting the release time interval and configuration validity conditions, until all phases are completed.

[0058] It should be noted that the segmented distribution mechanism enables high-disturbance configuration schemes to take effect gradually under controlled rhythm. The stable observation period between each instruction segment provides a fixed time window for configuration impact assessment, effectively reducing the risk of operational oscillations caused by simultaneous changes in batch parameters. The configuration rollback mechanism provides rapid recovery capability when configuration changes do not achieve the expected results, avoiding the target communication object being in a suboptimal state for a long time after configuration change failure.

[0059] Therefore, this application demonstrates that, firstly, by classifying business scenarios, the generation of candidate configuration schemes becomes scenario-specific, avoiding response delays during scenario switching; multi-parameter linkage correction ensures the physical feasibility of candidate schemes; generating multiple combinations according to preset step sizes ensures that candidate schemes cover different adjustment ranges; by analyzing the historical change trajectory of each communication parameter, the temporal dimension change characteristics of each communication parameter can be quantified; then, by comparing each item to determine the target communication parameter and its offset, the disturbance assessment can be accurate to the granularity of a single parameter, avoiding the coarse-grained assessment method that treats all parameters equally; and finally, the configuration... The evaluation incorporates disturbance potential energy, expected performance gain, and configuration switching cost, ensuring that the selection of candidate configuration schemes takes into account the three dimensions of benefit, cost, and disturbance. The differentiated release strategy allows high-disturbance configurations to have a longer effective transition period. The step-by-step effective mechanism breaks down high-disturbance configurations into multiple low-disturbance sub-steps, making high-benefit schemes feasible under the premise of controlled disturbance. Finally, the segmented distribution mechanism allows high-disturbance configurations to take effect gradually at a controlled pace. The stable observation period between each instruction segment provides a time window for configuration impact assessment, reducing operational oscillations caused by simultaneous changes in batch parameters and ensuring the stable operation of communication objects.

[0060] In summary, the technical solution adopted in this application can adaptively adjust communication parameters to achieve controlled disturbance configuration, thereby improving communication stability.

[0061] Furthermore, in another aspect of this application, in some embodiments, this application provides an adaptive configuration system for variable communication parameters in a communication system, with reference to... Figure 4 The figure is a schematic diagram of the structure of a variable communication parameter adaptive configuration system in a communication system according to some embodiments of this application. The variable communication parameter adaptive configuration system in the communication system includes: The data acquisition module 201 is used to acquire the communication operation data and current communication parameter configuration of the target communication object through the southbound interface of the SDN controller; The deduction and analysis module 202 is used to perform scenario-based deduction on the communication operation data, generate multiple candidate configuration schemes for the target communication object, and perform trajectory analysis based on the current communication parameter configuration to obtain the parameter variability state. The strategy generation module 203 is used to perform perturbation mapping processing on the parameter variability state for each candidate configuration scheme, determine the configuration perturbation potential energy of the candidate configuration scheme, and then generate a parameter release strategy based on the configuration perturbation potential energy corresponding to each candidate configuration scheme. The configuration update module 204 is used to send communication parameter configuration instructions to the target communication object through the SDN controller and trigger parameter variability state update according to the parameter release strategy.

[0062] In addition, this application also provides a computer device, the computer device including a memory and a processor, the memory storing code, and the processor being configured to acquire the code and execute the above-described adaptive configuration method for variable communication parameters in a communication system.

[0063] In some embodiments, reference Figure 5 The figure is a schematic diagram of the structure of a computer device implementing a method for adaptive configuration of variable communication parameters in a communication system, according to some embodiments of this application. The method for adaptive configuration of variable communication parameters in a communication system in the above embodiments can... Figure 5 The computer device shown is used to implement this, and the computer device includes at least one processor 301, a communication bus 302, a memory 303, and at least one communication interface 304.

[0064] The processor 301 may be a general-purpose central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more methods for controlling the execution of the adaptive configuration method for variable communication parameters in the communication system of this application.

[0065] The communication bus 302 can be used to transmit information between the aforementioned components.

[0066] The memory 303 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disks or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. The memory 303 may exist independently and be connected to the processor 301 via the communication bus 302. The memory 303 may also be integrated with the processor 301.

[0067] The memory 303 stores program code for executing the scheme of this application, and its execution is controlled by the processor 301. The processor 301 executes the program code stored in the memory 303. The program code may include one or more software modules. In the above embodiments, the determination of the adaptive configuration method for variable communication parameters in the communication system can be implemented by the processor 301 and one or more software modules in the program code in the memory 303.

[0068] Communication interface 304 uses any transceiver-like device for communicating with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area networks (WLAN), etc.

[0069] In a specific implementation, as one example, a computer device may include multiple processors, each of which may be a single-core (single-CPU) processor or a multi-core (multi-CPU) processor. Here, a processor may refer to one or more devices, circuits, and / or processing cores used to process data (e.g., computer program instructions).

[0070] The aforementioned computer device can be a general-purpose computer device or a special-purpose computer device. In specific implementations, the computer device can be a desktop computer, a portable computer, a network server, a handheld digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device, or an embedded device. This application does not limit the type of computer device.

[0071] In addition, this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the adaptive configuration method for variable communication parameters in the above-described communication system.

[0072] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0073] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for adaptive configuration of variable communication parameters in a communication system, characterized in that, Includes the following steps: The communication operation data and current communication parameter configuration of the target communication object are obtained through the southbound interface of the SDN controller. The communication operation data is used to perform scenario-based simulation to generate multiple candidate configuration schemes for the target communication object. Based on the current communication parameter configuration, trajectory analysis is performed to obtain the parameter variability state. For each candidate configuration scheme, the parameter variability state is perturbed and mapped to determine the configuration perturbation potential energy of the candidate configuration scheme. Then, based on the configuration perturbation potential energy corresponding to each candidate configuration scheme, a parameter release strategy is generated. Based on the parameter release strategy, the SDN controller sends communication parameter configuration instructions to the target communication object and triggers parameter variability state updates.

2. The method as described in claim 1, characterized in that, Obtaining the communication operation data and current communication parameter configuration of the target communication object through the southbound interface of the SDN controller specifically includes: Collect communication status monitoring data and the current configuration table stored locally on the device from the forwarding device, access device or edge gateway corresponding to the target communication object; The communication status monitoring data is preprocessed to generate communication operation data corresponding to the current sliding time window; The current configuration table is associated with the communication operation data to obtain the current communication parameter configuration of the target communication object.

3. The method as described in claim 1, characterized in that, Scenario-based simulation of the communication operation data to generate multiple candidate configuration schemes for the target communication object specifically includes: Based on the communication operation data, identify the business scenario tag of the target communication object; Obtain the parameter template that matches the business scenario tag; By combining link constraints, service priorities, and device-side resource reserves, the parameter template is modified through multi-parameter linkage to generate multiple candidate configuration schemes that meet preset feasibility constraints.

4. The method as described in claim 1, characterized in that, Trajectory analysis based on the current communication parameter configuration yields the following specific parameter variability states: Based on the current communication parameter configuration and the historical communication parameter configuration, a parameter change trajectory is constructed, and then core temporal features are extracted from the parameter change trajectory; The core temporal features are scaled to form a parameter variability vector. The parameter reverse adjustment frequency and configuration rollback strength are determined based on the parameter change trajectory sequence, and the device queue congestion level and link fluctuation stability are determined based on the communication operation data. Based on the parameter reverse adjustment frequency, configuration rollback strength, device queue congestion level and link fluctuation stability, generate the state fusion factor corresponding to the current sliding time window; The parameter variability vector is fused using the state fusion factor to obtain a parameter variability state that characterizes the intensity of changes in the time dimension of communication parameters.

5. The method as described in claim 1, characterized in that, For each candidate configuration scheme, the perturbation mapping process is performed on the parameter variability state to determine the configuration perturbation potential energy of the candidate configuration scheme, specifically including: For each candidate configuration scheme, a comparison is performed item by item based on the current communication parameter configuration to determine the target communication parameter whose value has changed and the parameter offset corresponding to each target communication parameter; Based on the variability state of the parameters, determine the activity level of each target communication parameter within the current sliding time window; Based on the parameter offset and change activity corresponding to each target communication parameter, the initial disturbance amount corresponding to each target communication parameter is determined; Based on the service carrying status of the target communication object, determine the service disturbance amplification coefficient corresponding to each target communication parameter; The initial disturbance of the target communication parameter is diffused to the associated communication parameters of the target communication parameter to obtain the diffused disturbance of each associated communication parameter. Potential energy is pooled from all initial disturbances, service disturbance amplification coefficients, and diffusion disturbances to obtain the configuration disturbance potential energy corresponding to the candidate configuration scheme.

6. The method as described in claim 1, characterized in that, Based on the configuration disturbance potential energy corresponding to each candidate configuration scheme, the parameter release strategy specifically includes: For each candidate configuration scheme, performance evolution is extrapolated based on the communication operation data of the target communication object, business scenario tags, and link resource status to obtain the expected performance gain of the candidate configuration scheme. Based on the parameter offset between the candidate configuration scheme and the current communication parameter configuration, the effective range of the configuration, and the device execution state of the target communication object, the switching disturbance is calculated to obtain the configuration switching cost of the candidate configuration scheme. The configuration disturbance potential, expected performance gain, and configuration switching cost of each candidate configuration scheme are jointly ranked to determine the parameter release strategy with the highest comprehensive evaluation value.

7. The method as described in claim 1, characterized in that, According to the parameter release strategy, the process of issuing communication parameter configuration instructions to the target communication object through the SDN controller and triggering parameter variability state updates specifically includes: The optimal parameter release strategy is parsed to generate segmented communication parameter configuration instructions, and the communication parameter configuration instructions are sent to the target communication object through the southbound interface of the SDN controller. After the communication parameter configuration command takes effect, the operation feedback data is collected, and it is determined whether the operation feedback data meets the preset update conditions. If it does not meet the conditions, the configuration rollback is triggered and the corresponding parameter release strategy is reset. Otherwise, the parameter variability status is updated.

8. A variable communication parameter adaptive configuration system for a communication system, used to execute the variable communication parameter adaptive configuration method for a communication system as described in any one of claims 1 to 7, characterized in that, The system includes: The data acquisition module is used to acquire the communication operation data and current communication parameter configuration of the target communication object through the southbound interface of the SDN controller; The deduction and analysis module is used to perform scenario-based deduction on the communication operation data, generate multiple candidate configuration schemes for the target communication object, and perform trajectory analysis based on the current communication parameter configuration to obtain the parameter variability state. The strategy generation module is used to perform perturbation mapping processing on the parameter variability state for each candidate configuration scheme, determine the configuration perturbation potential energy of the candidate configuration scheme, and then generate a parameter release strategy based on the configuration perturbation potential energy corresponding to each candidate configuration scheme. The configuration update module is used to send communication parameter configuration instructions to the target communication object through the SDN controller and trigger parameter variability state updates according to the parameter release strategy.

9. A computer device, characterized in that, The computer device includes a memory and a processor, the memory storing code, and the processor being configured to retrieve the code and execute the adaptive configuration method for variable communication parameters in a communication system as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the adaptive configuration method for variable communication parameters in a communication system as described in any one of claims 1 to 7.

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