Printing communication network optimization method

Abstract

The invention provides a printing communication network optimization method, and relates to the technical field of printing optimization, and the method comprises the steps: obtaining a printing communication network demand of a user in real time, outputting network demand information, and obtaining corresponding real-time network parameters based on the network demand information; evaluating and analyzing the real-time network parameters in combination with a preset evaluation index, and outputting a real-time network evaluation result; performing optimization analysis on the real-time network evaluation result in combination with historical network optimization data obtained from a historical database, and selecting an optimization scheme matched with an optimization analysis result from a strategy database; network configuration and parameters in the printing process are optimized and adjusted based on the optimization scheme, the optimized and adjusted network state is evaluated and analyzed in combination with a real-time network evaluation result, and an optimization evaluation result is obtained. The stability and reliability of a communication network in the printing industry are improved, the quality of the communication network in the printing process is improved, and normal operation of printing operation is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of printing optimization, and in particular to a printing communication network optimization method. Background Art

[0002] Print communication network optimization method refers to the method of improving network performance, efficiency and user experience by adjusting and improving various parameters, structures and processes in the print communication network.

[0003] At present, the network quality and performance of the commonly used communication network methods in the printing industry can no longer meet the increasing needs of printing enterprise users, especially when faced with the need to transmit large amounts of high-resolution images, design files and other large-capacity data, as well as real-time collaboration and remote control operations that require low latency and high stability. The stability, security and efficiency of the communication network can no longer be guaranteed.

[0004] Therefore, the present invention provides a printing communication network optimization method. Summary of the invention

[0005] The present invention provides a printing communication network optimization method for improving network performance and efficiency, reducing the risk of network failure, thereby improving the stability and reliability of the communication network in the printing industry, improving the quality of the communication network during the printing process, and ensuring the normal progress of the printing operation.

[0006] The present invention provides a printing communication network optimization method, comprising: Step 1: obtaining the user's printing communication network requirements in real time, outputting network requirement information, and obtaining corresponding real-time network parameters based on the network requirement information; Step 2: Evaluate and analyze the real-time network parameters in combination with preset evaluation indicators, and output the real-time network evaluation results; Step 3: Combine the historical network optimization data obtained from the historical database, perform optimization analysis on the real-time network evaluation results, and select an optimization solution that matches the optimization analysis results from the strategy database; Step 4: Optimize and adjust the network configuration and parameters in the printing process based on the optimization scheme, and evaluate and analyze the optimized and adjusted network status in combination with the real-time network evaluation result to obtain an optimization evaluation result.

[0007] Preferably, the real-time acquisition of the user's printing communication network demand and output of network demand information includes: Obtain users' LAN communication network requirements, WAN communication network requirements, and cloud service network requirements in real time, and summarize and output network demand information.

[0008] Preferably, the acquiring corresponding real-time network parameters based on the network demand information includes: Extracting features from the network demand information, and constructing a demand feature set based on the extracted features; Real-time network data matching the required feature set is acquired in a real-time database, and real-time network parameters are output.

[0009] Preferably, before evaluating and analyzing the real-time network parameters in combination with preset evaluation indicators, the following steps are included: In combination with the preset demand-indicator comparison table, an evaluation indicator matching the demand feature set is obtained in the indicator database, and a first indicator set is constructed; Obtain the manual indicator selection instruction input by the user and the indicator self-selection instruction generated by the system, select the evaluation indicators in the first indicator set based on the manual indicator selection instruction and the indicator self-selection instruction, obtain the preset evaluation indicators and summarize and output the evaluation indicator set.

[0010] Preferably, selecting the evaluation indicators in the first indicator set based on the manual indicator selection instruction and the indicator self-selection instruction includes: Obtaining the first execution priority of each manual indicator selection instruction, and at the same time, obtaining the second execution priority corresponding to each indicator self-selection instruction, and summarizing them to obtain a priority information table; Prioritize the instructions in the priority information table using a preset sorting rule, perform conflict analysis, and output the conflict analysis result; Based on the manual indicator selection instructions and the indicator self-selection instructions that do not have conflicts in the conflict analysis results, the evaluation indicators in the first indicator set are selected.

[0011] Preferably, step 2 includes: Based on the preset evaluation indicators, the corresponding real-time network parameters are evaluated and analyzed to obtain evaluation sub-results corresponding to each preset evaluation indicator; At the same time, the weight factors corresponding to the preset evaluation indicators are obtained, and the preset algorithms are used to summarize and analyze the evaluation sub-results to obtain the overall analysis results, and the real-time network evaluation results are output based on the evaluation sub-results and the overall analysis results.

[0012] Preferably, step 3 includes: Perform keyword recognition and extraction on the real-time network parameters, match them with preset network keywords in a preset word library, and output a keyword matching word set; Based on the keyword matching word set, primary reference data having a similarity with the keyword matching word set greater than or equal to a first similarity and secondary reference data having a similarity with the keyword recognition word set less than the first similarity and greater than or equal to a second similarity are selected from a historical database, wherein both the primary reference data and the secondary reference data include historical network operation parameter data, historical network optimization parameter data, and historical optimization evaluation data; Marking the primary reference data and the secondary reference data with distinguishing marks, and classifying and analyzing the marked primary reference data and the secondary reference data to obtain first data corresponding to the primary reference data and second data corresponding to the secondary reference data in each category; At the same time, obtaining the timestamps corresponding to the first data and the second data in each category, performing time alignment, and outputting a data-time sequence comparison table; Based on the data-time series comparison table and in combination with a preset data-curve construction method, a primary reference curve corresponding to the first data and a secondary reference curve corresponding to the second data in each category are respectively constructed; At the same time, the real-time network parameters and the real-time network evaluation results are processed using the preset data-curve construction method to construct a real-time parameter curve and a real-time evaluation curve under each category, and feature alignment is performed with the corresponding preset feature points in the primary reference curve and the secondary reference curve; Among them, the algorithm used to align the features of the curve is as follows: ; in, represents the alignment judgment value corresponding to the i-th time offset under the k-th preset feature point; when When , it means that the curves f(t) and g(t) are aligned according to the i-th time offset under the k-th preset feature point. When , it means that the curve is not aligned; Represents the time offset value of the curve function f(t) relative to g(t) at the k-th preset feature point; Represents the parameter value of the curve function f(t) at the nth discrete time point; Represents the parameter value of the curve function g(t) at the nth discrete time point; Represents the curve function g(t) at the nth discrete time point after time translation The parameter value after Represents the cross-correlation value between the time domain curve functions f(t) and g(t); Indicates the m time offsets under the kth preset feature point The maximum value among all the cross-correlation values ​​between the time domain curve functions f(t) and g(t) obtained after traversal; Represents the m time offsets from the kth preset feature point The corresponding offset error redundant mean; Compare and analyze the real-time parameter curve, the primary reference curve, and the secondary reference curve of the same category after feature alignment with the benchmark curve constructed based on the standard parameters to obtain a first curve comparison result; At the same time, the real-time evaluation curve, the primary reference curve, and the secondary reference curve under the same category after feature alignment are respectively compared and analyzed with the target optimization curve constructed based on the optimization target parameters to obtain a second curve comparison result; The first curve comparison result and the second curve comparison result are optimized and analyzed in combination with preset optimization analysis indicators, and an optimization solution matching the optimization analysis result is selected from the strategy database in combination with a preset result-strategy comparison table.

[0013] Preferably, step 4 includes: The optimization scheme is obtained and content is parsed, and divided into a first optimization scheme corresponding to the optimization and adjustment of network device setting parameters, a second optimization scheme corresponding to the optimization and adjustment of the network topology structure, and a third optimization scheme corresponding to the optimization and adjustment of the data transmission path according to the parsed content; Optimizing and adjusting the printed communication network based on the first optimization scheme, the second optimization scheme, and the third optimization scheme; The optimizing and adjusting of the network topology structure based on the second optimization scheme includes: Acquire the current network topology and output a real-time topology, wherein the real-time topology includes a production line network, an office network, a data center network, a remote access network, a supply chain network, and a customer service network; At the same time, in the second optimization scheme, optimizable items corresponding to each network under the real-time topology structure and optimization strategies corresponding to each optimizable item are obtained, wherein the optimization strategies include structure simplification strategy, redundancy and fault tolerance mechanism optimization strategy, equipment layout optimization strategy, network layering optimization strategy and expansion optimization strategy; Obtaining the optimization goals input by the user and the system, and selecting the items to be optimized from the optimizable items based on the optimization goals, and at the same time, outputting the optimization strategies matching the items to be optimized, and combining the comparison relationship between the items to be optimized and the optimization strategies to construct an item-strategy comparison table; Based on the item-strategy comparison table, each of the items to be optimized is optimized and adjusted, and data of each optimized item after optimization and adjustment is obtained, and an evaluation analysis is performed in combination with the preset evaluation index to output a first evaluation result; The real-time network evaluation result and the first evaluation result are compared and analyzed, and network status change data before and after optimization adjustment is determined based on the comparison and analysis result, and the optimization evaluation result is output.

[0014] The present invention provides a printing communication network optimization method, which realizes effective optimization of the printing communication network by acquiring user needs in real time, combining historical data for optimization analysis, and selecting the best optimization scheme according to preset evaluation indicators. The present invention combines real-time needs and historical data, can more accurately adjust network parameters, improve network performance and efficiency, reduce network failure risks, and thus improve the stability and reliability of the communication network in the printing industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0016] Figure 1 It is a flow chart of a printing communication network optimization method provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] like Figure 1 As shown, a printing communication network optimization method provided by an embodiment of the present invention includes: Step 1: Obtain the user's printing communication network requirements in real time, output network requirement information, and obtain corresponding real-time network parameters based on the network requirement information; Step 2: Evaluate and analyze the real-time network parameters in combination with preset evaluation indicators, and output the real-time network evaluation results; Step 3: Combine the historical network optimization data obtained from the historical database to optimize the real-time network evaluation results, and select an optimization solution that matches the optimization analysis results from the strategy database; Step 4: Based on the optimization scheme, the network configuration and parameters in the printing process are optimized and adjusted, and the network status after optimization and adjustment is evaluated and analyzed in combination with the real-time network evaluation results to obtain the optimization evaluation results.

[0019] In this embodiment, the printing communication network demand refers to the demand for the communication network in the printing industry, including data transmission speed, network stability, and data security; In this embodiment, network demand information: specific demand information of the user for the printing communication network, such as bandwidth requirements, data transmission delay requirements, etc.; In this embodiment, real-time network parameters: real-time network parameters acquired according to network demand information, used to adjust network configuration and parameters; In this embodiment, the preset evaluation indicators are: indicators for evaluating network performance, such as bandwidth utilization, data transmission speed, network delay, etc.; In this embodiment, the real-time network evaluation result is: the network performance evaluation result obtained after evaluation and analysis based on the real-time network parameters and the preset evaluation indicators, for example, the network bandwidth utilization rate is 60% and the delay is 30ms; In this embodiment, historical database: a database storing historical network optimization data, used for analyzing and optimizing the current network status; In this embodiment, historical network optimization data: that is, data collected when optimizing the network over a certain period of time in the past, used for reference and analysis of the current network status; In this embodiment, the strategy database: a database storing various optimization solutions, used to select an optimization solution that matches the optimization analysis result; In this embodiment, the optimization scheme: an optimization scheme selected based on historical network optimization data and real-time network evaluation results, used to adjust network configuration and parameters; In this embodiment, the network status refers to the network status after the network is optimized and adjusted; In this embodiment, the optimization evaluation result is an optimization effect evaluation result obtained after evaluating and analyzing the network status after optimization adjustment.

[0020] Implementation principle and beneficial effects of this embodiment: The present invention realizes effective optimization of the printing communication network by acquiring user needs in real time, combining historical data for optimization analysis, and selecting the best optimization scheme according to preset evaluation indicators. The present invention combines real-time needs and historical data to more accurately adjust network parameters, improve network performance and efficiency, and reduce the risk of network failures, thereby improving the stability and reliability of the communication network in the printing industry.

[0021] An embodiment of the present invention provides a printing communication network optimization method, which obtains the printing communication network requirements of users in real time and outputs network requirement information, including: Obtain users' LAN communication network requirements, WAN communication network requirements, and cloud service network requirements in real time, and summarize and output network demand information.

[0022] In this embodiment, the LAN communication network requirements include: the communication requirements of the LAN within the printing industry, including data exchange between departments within the printing company, connection requirements between printers and devices, etc. For example, within the printing company, the design department needs to quickly transmit the design files to the printing workshop, and the printing workshop needs to feed back the printing progress to the design department in real time; In this embodiment, the wide area network communication network requirements are: communication requirements between different branches or remote office locations of a printing company, including remote collaboration, remote monitoring and data sharing, etc. For example, assuming that a printing company has multiple branches, it is necessary to realize design file sharing and collaboration between branches, as well as remote monitoring of the operating status of printing equipment in each branch; In this embodiment, cloud service network requirements: the printing company utilizes the network services provided by the cloud service provider, such as storage, backup, applications, etc. For example, the printing company may store design files in the cloud to facilitate sharing and access by different departments and branches, and use cloud applications for collaboration and project management. This is part of the cloud service network requirements.

[0023] The implementation principle and beneficial effects of this embodiment: The present invention helps to more comprehensively understand user needs by subdividing the user's printing communication network needs into local area network, wide area network and cloud service network needs, and provides customized optimization solutions for different network environments. The present invention can formulate corresponding optimization strategies according to different types of network needs, and analyze and optimize in combination with real-time data and historical databases, thereby improving the stability, security and efficiency of the printing communication network. The present invention helps to improve the internal collaboration efficiency of the printing industry, strengthen the communication connection between branches, optimize the utilization effect of cloud services, etc. At the same time, it helps to improve the overall production efficiency and competitiveness of the printing industry.

[0024] An embodiment of the present invention provides a printing communication network optimization method, which obtains corresponding real-time network parameters based on network demand information, including: Extract features from network demand information, and construct a demand feature set based on the extracted features; Real-time network data matching the required feature set is obtained in the real-time database, and real-time network parameters are output.

[0025] In this embodiment, the demand feature set is a feature set extracted from the network demand information, which is used to describe the demand features of the printing communication network and help identify different types of network demands. For example, the feature set extracted from the network demand information of the printing company may include data transmission volume, priority requirements, security requirements, etc. Specifically, the design department needs to transmit design files with high priority, and the printing workshop needs to ensure the security of printing data. In this embodiment, the real-time database: a database storing real-time network data, including real-time information such as network device status, bandwidth utilization, delay, etc.; In this embodiment, real-time network parameters: network parameters extracted from real-time network data matched with the demand feature set, used to adjust and optimize the printing communication network.

[0026] The implementation principle and beneficial effects of this embodiment: The present invention extracts features from network demand information, constructs a demand feature set, and obtains matching real-time network data from a real-time database, thereby realizing the function of adjusting network parameters according to demand features. The present invention can flexibly adjust network parameters according to different demand features, improve network response speed, optimize bandwidth allocation, enhance network security, etc., and is helpful to improve the stability and reliability of the communication network in the printing industry.

[0027] A printing communication network optimization method provided by an embodiment of the present invention includes: before evaluating and analyzing real-time network parameters in combination with preset evaluation indicators, the method includes: Combined with the preset demand-indicator comparison table, the evaluation indicators matching the demand feature set are obtained in the indicator database, and the first indicator set is constructed; Obtain the manual indicator selection instruction input by the user and the indicator self-selection instruction generated by the system, select the evaluation indicators in the first indicator set based on the manual indicator selection instruction and the indicator self-selection instruction, obtain the preset evaluation indicators and summarize and output the evaluation indicator set.

[0028] In this embodiment, the preset demand-indicator comparison table: a comparison table containing mapping relationships between different demand characteristics and evaluation indicators, which is preset and used to guide the selection of indicators in the evaluation process. For example, the demand characteristics corresponding to the design department may correspond to the evaluation indicator of data transmission speed, and the demand characteristics corresponding to the printing workshop may correspond to the evaluation indicator of device connection status; In this embodiment, the indicator database: stores various possible evaluation indicators, and is used to obtain corresponding evaluation indicators according to the matching of the demand feature set; In this embodiment, the evaluation index: an index used to evaluate the performance of the printing communication network, such as latency, bandwidth utilization, data transmission speed, etc.; In this embodiment, the first indicator set: a set of evaluation indicators matched with the demand feature set obtained from the indicator database; In this embodiment, manual indicator selection instructions: instructions provided by the user to guide the system to select evaluation indicators; In this embodiment, the indicator self-selection instruction: an instruction automatically generated by the system to guide the indicator selection; In this embodiment, the evaluation index set is a set of indicators finally selected for evaluating and analyzing network performance.

[0029] Implementation principle and beneficial effects of this embodiment: The present invention selects evaluation indicators according to the instructions input by the user and the instructions automatically generated by the system by combining the preset demand-indicator comparison table, thereby providing guidance for the evaluation and analysis of real-time network parameters. The present invention can select appropriate evaluation indicators according to specific needs and the system's own conditions, which helps to more comprehensively evaluate the performance of the printed communication network.

[0030] An embodiment of the present invention provides a printing communication network optimization method, which selects evaluation indicators in a first indicator set based on a manual indicator selection instruction and an indicator self-selection instruction, including: Obtain the first execution priority of each manual indicator selection instruction, and at the same time, obtain the second execution priority corresponding to each indicator self-selection instruction, and summarize them to obtain a priority information table; Prioritize the instructions in the priority information table using preset sorting rules, perform conflict analysis, and output the conflict analysis results; Based on the manual indicator selection instructions and the indicator self-selection instructions that do not have conflicts in the conflict analysis results, the evaluation indicators in the first indicator set are selected.

[0031] In this embodiment, the first execution priority: that is, the execution priority corresponding to the manual indicator selection instruction, represents the priority of the evaluation indicator specified by the user during the execution process. For example, the design department may specify the data transmission speed as the first execution priority; In this embodiment, the second execution priority is the execution priority corresponding to the indicator self-selection instruction, and the system sets the priority of the automatically generated evaluation indicator during the execution process. For example, the system may generate bandwidth utilization as the second execution priority according to the network load condition; In this embodiment, the priority information table: a table containing the execution priority information corresponding to each instruction, which is used for subsequent sorting and conflict analysis; In this embodiment, the preset sorting rule: specifies the rule for sorting instructions according to the priority information, generally sorting the instructions from high to low according to the execution priority; In this embodiment, the conflict analysis result refers to the situation where conflicts or contradictions between instructions are found after the execution priorities are sorted, which need to be further processed or resolved.

[0032] The implementation principle and beneficial effects of this embodiment: The present invention obtains execution priority information, summarizes the priority information table, performs sorting and conflict analysis according to preset sorting rules, and finally selects conflict-free evaluation indicators. The present invention can effectively select appropriate evaluation indicators according to user needs and the instruction priority automatically generated by the system, improve the pertinence and effect of network optimization, and further improve the performance and efficiency of the printed communication network.

[0033] An embodiment of the present invention provides a printing communication network optimization method, in step 2, including: Based on the preset evaluation indicators, the corresponding real-time network parameters are evaluated and analyzed to obtain evaluation sub-results corresponding to each preset evaluation indicator; At the same time, the weight factors corresponding to each preset evaluation indicator are obtained, and the preset algorithm is used to summarize and analyze the evaluation sub-results to obtain the overall analysis results, and the real-time network evaluation results are output based on the evaluation sub-results and the overall analysis results.

[0034] In this embodiment, the evaluation sub-result is a specific evaluation result obtained for each preset evaluation indicator, which is used to characterize the network performance under each indicator. For example, for the preset evaluation indicator of data transmission speed, the evaluation sub-result may be that the actual data transmission speed is 100 Mbps per second. In this embodiment, the weight factor is used to measure the importance of each evaluation indicator in the overall analysis result, and affects the weight of each evaluation sub-result in the summary analysis. For example, for the two evaluation indicators of data transmission speed and bandwidth utilization, the weight factor may be 0.7 for data transmission speed and 0.3 for bandwidth utilization; In this embodiment, preset algorithm: a preset algorithm or method for weighted aggregation of each evaluation sub-result according to a weight factor; In this embodiment, summary analysis: each evaluation sub-result is weighted and summarized according to the weight factor to obtain an overall analysis result; In this embodiment, the overall analysis result: the final network evaluation result obtained by weighted aggregation of the evaluation sub-results reflects the overall network performance.

[0035] Implementation principle and beneficial effects of this embodiment: The present invention outputs real-time network evaluation results by weighted aggregation of evaluation sub-results, taking into account the importance of each evaluation index. The present invention can more comprehensively evaluate network performance, improve the accuracy and objectivity of network evaluation, and help decision makers better understand the network performance status, so as to take targeted optimization measures.

[0036] An embodiment of the present invention provides a printing communication network optimization method, wherein step 3 includes: Perform keyword recognition and extraction on real-time network parameters, match them with preset network keywords in a preset word library, and output a keyword matching word set; Based on the keyword matching word set, primary reference data having a similarity with the keyword matching word set greater than or equal to a first similarity and secondary reference data having a similarity with the keyword recognition word set less than the first similarity and greater than or equal to a second similarity are selected from the historical database, wherein both the primary reference data and the secondary reference data include historical network operation parameter data, historical network optimization parameter data, and historical optimization evaluation data; Marking the primary reference data and the secondary reference data with distinguishing marks, and classifying, analyzing and dividing the marked primary reference data and the secondary reference data to obtain first data corresponding to the primary reference data and second data corresponding to the secondary reference data under each category; At the same time, the timestamps corresponding to the first data and the second data under each category are obtained, and the time alignment is performed to output a data-time sequence comparison table; Based on the data-time series comparison table and in combination with the preset data-curve construction method, a main reference curve corresponding to the first data and a secondary reference curve corresponding to the second data under each category are respectively constructed; At the same time, the real-time network parameters and the real-time network evaluation results are processed using the preset data-curve construction method to construct the real-time parameter curve and the real-time evaluation curve under each category, and the features are aligned with the corresponding preset feature points in the primary reference curve and the secondary reference curve; Among them, the algorithm used to align the features of the curve is as follows: ; in, represents the alignment judgment value corresponding to the i-th time offset under the k-th preset feature point; when When , it means that the curves f(t) and g(t) are aligned according to the i-th time offset under the k-th preset feature point. When , it means that the curve is not aligned; Represents the time offset value of the curve function f(t) relative to g(t) at the k-th preset feature point; Represents the parameter value of the curve function f(t) at the nth discrete time point; Represents the parameter value of the curve function g(t) at the nth discrete time point; Represents the curve function g(t) at the nth discrete time point after time translation The parameter value after Represents the cross-correlation value between the time domain curve functions f(t) and g(t); Indicates the m time offsets under the kth preset feature point The maximum value among all the cross-correlation values ​​between the time domain curve functions f(t) and g(t) obtained after traversal; Represents the m time offsets from the kth preset feature point The corresponding offset error redundant mean; The real-time parameter curve, the primary reference curve, and the secondary reference curve of the same category after feature alignment are respectively compared and analyzed with the benchmark curve constructed based on the standard parameters to obtain a first curve comparison result; At the same time, the real-time evaluation curve, the primary reference curve, and the secondary reference curve under the same category after feature alignment are respectively compared and analyzed with the target optimization curve constructed based on the optimization target parameters to obtain the second curve comparison result; The first curve comparison result and the second curve comparison result are optimized and analyzed in combination with preset optimization analysis indicators, and an optimization solution matching the optimization analysis result is selected from the strategy database in combination with a preset result-strategy comparison table.

[0037] In this embodiment, keyword identification and extraction: identifying and extracting keywords or key information in real-time network parameters, for example, keywords such as data transmission speed and bandwidth utilization; In this embodiment, the preset word library: a pre-set word library containing keywords or key phrases, used to match keywords in real-time network parameters; In this embodiment, preset network keywords: keywords in a preset word library, used to match keywords in real-time network parameters; In this embodiment, the keyword matching word set: a set of successfully matched keywords, including keywords in the real-time network parameters that match the preset network keywords; In this embodiment, similarity: an indicator used to measure the similarity between two data sets; In this embodiment, the first similarity: a similarity threshold set for screening the primary reference data; In this embodiment, the main reference data: historical data having a similarity with the keyword matching word set greater than or equal to a first similarity, including network operation parameters, network optimization parameters and optimization evaluation data; In this embodiment, the second similarity: a similarity threshold set for screening the secondary reference data; In this embodiment, the secondary reference data: historical data having a similarity with the keyword matching word set less than the first similarity and greater than or equal to the second similarity, corresponding to the primary reference data, and used for subsequent data analysis in combination with the primary reference data; In this embodiment, historical network operation parameter data: records various parameter data of past network operation, such as bandwidth utilization, data transmission speed, etc.; In this embodiment, the historical network optimization parameter data includes various parameters used in past network optimization, such as routing configuration, transmission protocol, etc.; In this embodiment, historical optimization evaluation data: records the evaluation results of past network optimization solutions, including network performance indicators, optimization effects, etc.; In this embodiment, the distinguishing mark and label: the primary reference data and the secondary reference data are marked to distinguish their roles in the analysis process, for example, the primary reference data is marked with "A" and the secondary reference data is marked with "B"; In this embodiment, classification analysis and division: classifying and analyzing data according to specific standards to better understand and process the data; In this embodiment, category: the data is divided into different categories according to specific criteria to facilitate subsequent analysis, for example, the data is divided into three categories of low load, medium load and high load according to the network load level; In this embodiment, first data: data corresponding to the primary reference data in each category; In this embodiment, the second data: data corresponding to the secondary reference data in each category; In this embodiment, timestamp: records the time information of data, used for time alignment and analysis of data; In this embodiment, time alignment: aligning the time information of different data sets to facilitate subsequent comparative analysis; In this embodiment, data-time series comparison table: a comparison table recording data and time information, used for subsequent curve construction and comparative analysis; In this embodiment, the preset data-curve construction method: the method for constructing the corresponding curve according to the data is preset, for example, the primary reference curve and the secondary reference curve are constructed using the Fourier transform method; In this embodiment, the main reference curve: a curve corresponding to the first data in each category, used as a main reference for comparative analysis; In this embodiment, the secondary reference curve: a curve corresponding to the second data in each category, used as a secondary reference for comparative analysis; In this embodiment, real-time parameter curve: a curve constructed according to real-time network parameters, used for comparison with the primary reference curve and the secondary reference curve in comparative analysis; In this embodiment, the real-time evaluation curve is a curve constructed based on the real-time network evaluation results, used to evaluate network performance, and compared and analyzed with the primary reference curve and the secondary reference curve; In this embodiment, preset feature points: during the curve construction and feature alignment process, preset key feature points are used to align different curves, such as peaks, valleys or other important data points; In this embodiment, feature alignment: different curves are aligned according to feature points, so as to compare and analyze the similarities and differences between different curves; In this embodiment, standard parameters: network parameters used as a benchmark for comparative analysis, usually reference parameters determined in advance; In this embodiment, the reference curve is a reference curve constructed according to standard parameters and used for comparative analysis with the real-time parameter curve; In this embodiment, the first curve comparison result: the result obtained by comparing and analyzing the real-time parameter curve, the primary reference curve, the secondary reference curve and the benchmark curve under the same category, which is used to evaluate the change and deviation of network performance, for example, the result obtained by comparing and analyzing the real-time bandwidth utilization curve with the benchmark curve, such as exceeding the threshold, fluctuation, etc.; In this embodiment, the optimization target parameter is a target parameter used to guide network optimization, which is usually a network performance indicator that is desired to be optimized or improved, such as maximum bandwidth utilization, minimum delay time, etc.; In this embodiment, the target optimization curve: a target optimization curve constructed according to the optimization target parameters, used to evaluate the effect of network optimization; In this embodiment, the second curve comparison result: the result obtained by comparing and analyzing the real-time evaluation curve, the primary reference curve, the secondary reference curve and the target optimization curve under the same category, which is used to evaluate the optimization effect and the achievement of the target, for example, the result obtained by comparing and analyzing the real-time evaluation curve and the target optimization curve, such as the achievement of the target, the degree of improvement, etc.; In this embodiment, preset optimization analysis indicators: indicators set in advance for evaluating network performance and optimization effects, used to guide the optimization analysis process, such as bandwidth utilization improvement rate, delay reduction degree, etc.; In this embodiment, the preset result-strategy comparison table is a table or database that compares the preset optimization analysis results with the corresponding optimization strategies, and is used to select the most suitable optimization solution.

[0038] The implementation principle and beneficial effects of this embodiment: The present invention divides historical data into primary reference data and secondary reference data through keyword matching and similarity screening, and performs curve construction and comparative analysis. Through the feature alignment algorithm, it ensures that different curves are aligned at key feature points, which helps to more accurately evaluate network performance, and finally selects the most suitable optimization scheme by combining optimization analysis indicators and strategy database. The present invention utilizes keyword matching, similarity screening and curve comparative analysis, combined with the preset data-curve construction method, to monitor and optimize network parameters in real time, which can more accurately identify network problems, improve network operation efficiency, and formulate more effective optimization strategies based on historical data, thereby improving network reliability and performance.

[0039] An embodiment of the present invention provides a printing communication network optimization method, in step 4, including: Acquire the optimization plan and parse its contents, and divide it into a first optimization plan corresponding to the optimization and adjustment of network device setting parameters, a second optimization plan corresponding to the optimization and adjustment of the network topology structure, and a third optimization plan corresponding to the optimization and adjustment of the data transmission path according to the parsed contents; Optimizing and adjusting the printed communication network based on the first optimization scheme, the second optimization scheme, and the third optimization scheme; The network topology structure is optimized and adjusted based on the second optimization scheme, including: Obtain the current network topology and output the real-time topology, which includes production line network, office network, data center network, remote access network, supply chain network and customer service network; At the same time, in the second optimization scheme, the optimizable items corresponding to each network under the real-time topology structure and the optimization strategies corresponding to each optimizable item are obtained, wherein the optimization strategies include structure simplification strategy, redundancy and fault tolerance mechanism optimization strategy, equipment layout optimization strategy, network layering optimization strategy and expansion optimization strategy; Obtain the optimization goals input by the user and the system, and select the items to be optimized from the optimizable items based on the optimization goals. At the same time, output the optimization strategies that match the items to be optimized, and build an item-strategy comparison table based on the comparison relationship between the items to be optimized and the optimization strategies; Based on the item-strategy comparison table, each item to be optimized is optimized and adjusted, and the data of each optimized item after optimization and adjustment is obtained, and the first evaluation result is output by evaluating and analyzing the preset evaluation indicators; The real-time network evaluation result and the first evaluation result are compared and analyzed, and the network status change data before and after the optimization adjustment is determined based on the comparison and analysis result, and the optimization evaluation result is output.

[0040] In this embodiment, the network device setting parameter optimization adjustment: optimizing and adjusting the configuration parameters of the network device to improve network performance and efficiency; In this embodiment, the first optimization scheme: an optimization scheme for setting parameters of network devices, including adjusting parameters such as bandwidth and buffer size of the device; In this embodiment, the network topology structure is optimized and adjusted: the network structure and connection relationship are optimized and adjusted to improve the network communication efficiency and stability; In this embodiment, the second optimization scheme: an optimization scheme for the network topology structure, including optimizing the network layout, simplifying the structure, improving the redundancy mechanism, etc., for example, adding a backup link; In this embodiment, the optimization and adjustment of the data transmission path refers to optimizing and adjusting the data transmission path in the network to reduce delay, increase transmission speed, etc.; In this embodiment, the third optimization scheme: an optimization scheme for the data transmission path, including selecting the best transmission path, optimizing the data packet forwarding strategy, etc.; In this embodiment, real-time topology structure: the topology structure of the current network, including the connection relationship between different parts such as the production line network, office network, data center network, remote access network, supply chain network and customer service network; In this embodiment, production line network: the network part related to printing production, used to manage and monitor printing equipment, production processes, etc., for example, the network connecting printing machines, quality control systems and production data collection systems In this embodiment, office network: a network used for internal office and communication within a company, including the connection of devices such as computers, printers, and telephones, for example, an internal office network connecting employee computers, servers, and printers; In this embodiment, data center network: a network structure used to store and manage data, usually including a large number of servers and storage devices, for example, a network connecting data center servers, storage devices and network devices; In this embodiment, remote access network: a network that allows remote users to access company resources through the network, such as remote office, remote monitoring, etc., for example, a remote access network that connects a remote employee's computer and a company server; In this embodiment, supply chain network: a network for managing and optimizing supply chain processes, including network connections with suppliers, manufacturers, and distributors, for example, a supply chain network connecting suppliers, manufacturers, and distributors; In this embodiment, customer service network: a network used to provide customer service and support, including a customer service center, an online support system, etc., for example, a network connecting a customer service center, an online customer service system, and a customer database; In this embodiment, the optimizable items are items that can be optimized; In this embodiment, optimization strategy refers to a strategy or method for optimizing an optimizable item; In this embodiment, the structure simplification strategy: optimizes the network structure, reduces unnecessary complexity, and improves network operation efficiency, for example, simplifies the network topology and reduces intermediate nodes; In this embodiment, the redundancy and fault-tolerance mechanism optimization strategy: adding redundant paths and fault-tolerance mechanisms to improve the reliability and stability of the network, for example, setting up a backup link to cope with the failure of the main link; In this embodiment, the device layout optimization strategy: optimizes the layout and deployment of devices to improve network performance and management efficiency, for example, adjusting the server location to reduce data transmission delay; In this embodiment, the network layered optimization strategy: divides the network into different layers to achieve more effective management and control, for example, divides the network into a core layer, a convergence layer, and an access layer to optimize data traffic; In this embodiment, the optimization strategy is expanded: network capabilities are expanded to accommodate future growth and demand, for example, increasing network bandwidth to support more users and data traffic; In this embodiment, optimization goal: a specific goal or standard set to improve network performance, reliability or other aspects, for example, increasing data transmission speed, reducing network latency, increasing network security, etc.; In this embodiment, the item to be optimized is a specific part or parameter that needs to be adjusted or improved during the network optimization process, such as network bandwidth allocation, device configuration, data transmission path, etc.; In this embodiment, the item-strategy comparison table is a table or list that matches the items to be optimized with the corresponding optimization strategies, and is used to guide the optimization adjustment process. Through the comparison table, it is possible to clearly understand the optimization strategy that should be adopted for each item to be optimized; In this embodiment, the first evaluation result: the result of evaluating the network performance according to the preset evaluation index after the optimization adjustment is performed, which can help evaluate the effect and effectiveness of the optimization adjustment; In this embodiment, network status change data: specific data of changes in network status before and after optimization and adjustment, which may include network bandwidth utilization, device load, data transmission speed, etc.

[0041] The implementation principle and beneficial effects of this embodiment: The present invention can improve network performance, reduce delays, and improve data transmission efficiency by optimizing and adjusting network device setting parameters, network topology, and data transmission paths, thereby improving user experience and network reliability. In addition, through the analysis of real-time topology structures and the selection of optimization schemes, the most optimized network optimization strategy can be formulated according to specific circumstances to make the network more stable and efficient. Furthermore, through evaluation analysis and comparative analysis, problems can be discovered in a timely manner and corresponding measures can be taken, thereby achieving the goal of network optimization.

[0042] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A printing communication network optimization method, characterized in that: include: Step 1: obtaining the user's printing communication network requirements in real time, outputting network requirement information, and obtaining corresponding real-time network parameters based on the network requirement information; Step 2: Evaluate and analyze the real-time network parameters in combination with preset evaluation indicators, and output the real-time network evaluation results; Step 3: Combine the historical network optimization data obtained from the historical database, perform optimization analysis on the real-time network evaluation results, and select an optimization solution that matches the optimization analysis results from the strategy database; Step 4: Optimize and adjust the network configuration and parameters in the printing process based on the optimization scheme, and evaluate and analyze the optimized and adjusted network status in combination with the real-time network evaluation result to obtain an optimization evaluation result.

2. A printing communication network optimization method according to claim 1, characterized in that: The real-time acquisition of the user's printing communication network demand and output of network demand information includes: Obtain users' LAN communication network requirements, WAN communication network requirements, and cloud service network requirements in real time, and summarize and output network demand information.

3. A printing communication network optimization method according to claim 1, characterized in that: The obtaining corresponding real-time network parameters based on the network demand information includes: Extracting features from the network demand information, and constructing a demand feature set based on the extracted features; Real-time network data matching the required feature set is acquired in a real-time database, and real-time network parameters are output.

4. A printing communication network optimization method according to claim 3, characterized in that: Before evaluating and analyzing the real-time network parameters in combination with preset evaluation indicators, the following steps are included: In combination with the preset demand-indicator comparison table, an evaluation indicator matching the demand feature set is obtained in the indicator database, and a first indicator set is constructed; Obtain the manual indicator selection instruction input by the user and the indicator self-selection instruction generated by the system, select the evaluation indicators in the first indicator set based on the manual indicator selection instruction and the indicator self-selection instruction, obtain the preset evaluation indicators and summarize and output the evaluation indicator set.

5. A printing communication network optimization method according to claim 4, characterized in that: Selecting the evaluation indicators in the first indicator set based on the manual indicator selection instruction and the indicator self-selection instruction includes: Obtaining the first execution priority of each manual indicator selection instruction, and at the same time, obtaining the second execution priority corresponding to each indicator self-selection instruction, and summarizing them to obtain a priority information table; Prioritize the instructions in the priority information table using a preset sorting rule, perform conflict analysis, and output the conflict analysis result; Based on the manual indicator selection instructions and the indicator self-selection instructions that do not have conflicts in the conflict analysis results, the evaluation indicators in the first indicator set are selected.

6. A printing communication network optimization method according to claim 1, characterized in that: Step 2 includes: Based on the preset evaluation indicators, the corresponding real-time network parameters are evaluated and analyzed to obtain evaluation sub-results corresponding to each preset evaluation indicator; At the same time, the weight factors corresponding to the preset evaluation indicators are obtained, and the preset algorithms are used to summarize and analyze the evaluation sub-results to obtain the overall analysis results, and the real-time network evaluation results are output based on the evaluation sub-results and the overall analysis results.

7. A printing communication network optimization method according to claim 1, characterized in that: Step 3 includes: Perform keyword recognition and extraction on the real-time network parameters, match them with preset network keywords in a preset word library, and output a keyword matching word set; Based on the keyword matching word set, primary reference data having a similarity with the keyword matching word set greater than or equal to a first similarity and secondary reference data having a similarity with the keyword recognition word set less than the first similarity and greater than or equal to a second similarity are selected from a historical database, wherein both the primary reference data and the secondary reference data include historical network operation parameter data, historical network optimization parameter data, and historical optimization evaluation data; Marking the primary reference data and the secondary reference data with distinguishing marks, and classifying and analyzing the marked primary reference data and the secondary reference data to obtain first data corresponding to the primary reference data and second data corresponding to the secondary reference data in each category; At the same time, obtaining the timestamps corresponding to the first data and the second data in each category, performing time alignment, and outputting a data-time sequence comparison table; Based on the data-time series comparison table and in combination with a preset data-curve construction method, a primary reference curve corresponding to the first data and a secondary reference curve corresponding to the second data in each category are respectively constructed; At the same time, the real-time network parameters and the real-time network evaluation results are processed using the preset data-curve construction method to construct a real-time parameter curve and a real-time evaluation curve under each category, and feature alignment is performed with the corresponding preset feature points in the primary reference curve and the secondary reference curve; Among them, the algorithm used to align the features of the curve is as follows: ； in, represents the alignment judgment value corresponding to the i-th time offset under the k-th preset feature point; when When , it means that the curves f(t) and g(t) are aligned according to the i-th time offset under the k-th preset feature point. When , it means that the curve is not aligned; Represents the time offset value of the curve function f(t) relative to g(t) at the k-th preset feature point; Represents the parameter value of the curve function f(t) at the nth discrete time point; Represents the parameter value of the curve function g(t) at the nth discrete time point; Represents the curve function g(t) at the nth discrete time point after time translation The parameter value after Represents the cross-correlation value between the time domain curve functions f(t) and g(t); Indicates the m time offsets under the kth preset feature point The maximum value among all the cross-correlation values ​​between the time domain curve functions f(t) and g(t) obtained after traversal; Represents the m time offsets from the kth preset feature point The corresponding offset error redundant mean; Compare and analyze the real-time parameter curve, the primary reference curve, and the secondary reference curve of the same category after feature alignment with the benchmark curve constructed based on the standard parameters to obtain a first curve comparison result; At the same time, the real-time evaluation curve, the primary reference curve, and the secondary reference curve under the same category after feature alignment are respectively compared and analyzed with the target optimization curve constructed based on the optimization target parameters to obtain a second curve comparison result; The first curve comparison result and the second curve comparison result are optimized and analyzed in combination with preset optimization analysis indicators, and an optimization solution matching the optimization analysis result is selected from the strategy database in combination with a preset result-strategy comparison table.

8. A printing communication network optimization method according to claim 1, characterized in that: Step 4 includes: The optimization scheme is obtained and content is parsed, and divided into a first optimization scheme corresponding to the optimization and adjustment of network device setting parameters, a second optimization scheme corresponding to the optimization and adjustment of the network topology structure, and a third optimization scheme corresponding to the optimization and adjustment of the data transmission path according to the parsed content; Optimizing and adjusting the printed communication network based on the first optimization scheme, the second optimization scheme, and the third optimization scheme; The optimizing and adjusting of the network topology structure based on the second optimization scheme includes: Acquire the current network topology and output a real-time topology, wherein the real-time topology includes a production line network, an office network, a data center network, a remote access network, a supply chain network, and a customer service network; At the same time, in the second optimization scheme, optimizable items corresponding to each network under the real-time topology structure and optimization strategies corresponding to each optimizable item are obtained, wherein the optimization strategies include structure simplification strategy, redundancy and fault tolerance mechanism optimization strategy, equipment layout optimization strategy, network layering optimization strategy and expansion optimization strategy; Obtaining the optimization goals input by the user and the system, and selecting the items to be optimized from the optimizable items based on the optimization goals, and at the same time, outputting the optimization strategies matching the items to be optimized, and combining the comparison relationship between the items to be optimized and the optimization strategies to construct an item-strategy comparison table; Based on the item-strategy comparison table, each of the items to be optimized is optimized and adjusted, and data of each optimized item after optimization and adjustment is obtained, and an evaluation analysis is performed in combination with the preset evaluation index to output a first evaluation result; The real-time network evaluation result and the first evaluation result are compared and analyzed, and network status change data before and after optimization adjustment is determined based on the comparison and analysis result, and the optimization evaluation result is output.

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