An Internet of Things card intelligent flow recharge monitoring system and control method

Abstract

The present invention relates to the field of digital information transmission technology, specifically to an Internet of Things card intelligent traffic recharge monitoring system and control method, the system comprising: a data acquisition module, a system performance evaluation module, a service quality evaluation module, a comprehensive performance evaluation early warning module and a monitoring system database. The present invention provides an Internet of Things card intelligent traffic recharge monitoring system and control method, comprehensively analyzes the system performance and service quality, and continuously optimizes the system through the analysis results, which can ensure that the system achieves the best balance between performance and quality, thereby improving the efficiency and stability of the system when processing tasks, and can also ensure the high availability of the system, which is conducive to the system in the process of providing services, enhancing user satisfaction and improving business continuity. At the same time, it helps to improve the comprehensive efficiency of the system, thereby enhancing the competitiveness of the system in the market, and is also conducive to realizing refined operation and maintenance, thereby reducing operation and maintenance costs.

Description

Technical Field

[0001] The present invention relates to the technical field of digital information transmission, and in particular to an Internet of Things card intelligent flow recharge monitoring system and control method. Background Art

[0002] With the rapid development and widespread adoption of IoT technology, traffic management issues for IoT cards, key components connecting IoT devices and networks, have become increasingly prominent. IoT devices are numerous and widely distributed, and each requires a stable network connection and sufficient data traffic to ensure real-time data transmission and processing. Consequently, the IoT card intelligent data recharge monitoring system has emerged.

[0003] For example, the invention patent with announcement number: CN117896163B is a network traffic monitoring system, which includes a refined topology construction module, an abnormal traffic monitoring module and a network device control module; it can divide multiple devices in each network more finely, construct multiple sub-network topologies of each network, and obtain the network topology of each network; it can monitor the operating traffic of multiple devices in real time, determine the abnormal devices and their degree of abnormality in each network; it can also determine the associated devices of the abnormal devices and their degree of association based on the network topology of each network, and take corresponding control measures based on the characteristic information and degree of abnormality of the abnormal devices and the characteristic information and degree of association of the associated devices.

[0004] For example, the invention patent with announcement number: CN106953909B is an intelligent recharge monitoring system and control method for an Internet of Things card, including a traffic pool module, a sending module, a monitoring and receiving module, a parsing and diversion business processing module, a reply module and a monitoring module. Different Internet of Things cards with the same package are combined to form a traffic pool. All Internet of Things cards under the traffic pool share traffic, take out the business in the recharge waiting queue and parse it. The system searches the system's existing traffic pool for recharge based on the conditions such as the operator type and package type of the business combined with the system retrieval algorithm; the principle of recharge is to use the traffic pool of the same operator as the initiator to recharge the initiator; because of the traffic pool sharing mode, recharge can use the traffic in the traffic pool to recharge, further reducing the charges.

[0005] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems: the current Internet of Things card intelligent recharge monitoring system optimizes the traffic recharge results through a retrieval algorithm, but in actual applications, the system performance will also affect the judgment of the traffic recharge results, and it is impossible to further understand the system operation status, which may lead to untimely response when a fault occurs, affecting the stability and reliability of the system. Summary of the Invention

[0006] In view of the shortcomings of the existing technology, the present invention provides an Internet of Things card intelligent traffic recharge monitoring system and control method, which can effectively solve the problems involved in the above-mentioned background technology.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: The present invention provides an Internet of Things card intelligent traffic recharge monitoring system, including: a data acquisition module for collecting system performance data and system operation data;

[0008] A system performance evaluation module is used to obtain a system performance evaluation index based on system performance data through processing;

[0009] The service quality evaluation module is used to obtain the system service quality evaluation index based on the system operation data through processing;

[0010] The comprehensive performance evaluation and early warning module is used to obtain the system comprehensive performance evaluation index based on the system performance evaluation index and the service quality evaluation index through comprehensive analysis, evaluate the system performance based on the system comprehensive performance evaluation index, obtain the evaluation results and provide feedback.

[0011] As a further method, the system performance data and system operation data are collected, and the specific process is: setting a monitoring period, and deploying a number of system operation nodes within the monitoring period, and counting the system performance data and operation data within the monitoring period.

[0012] The system performance data includes hardware equipment performance data and the recharge response time and throughput of each system operation node within the monitoring period.

[0013] The system operation data includes system availability, transaction success rate and user complaint resolution rate during the monitoring period.

[0014] As a further method, the hardware device performance data includes the total amount of system hardware resources, the system hardware resource operation speed of each system operation node, network bandwidth, network delay and the number of parallel users during the monitoring period.

[0015] As a further method, the system performance evaluation index is obtained through processing, and the specific process is:

[0016] According to the system hardware resource operating speed, network bandwidth and network delay of each system operation node during the monitoring period, the critical system hardware resource operating speed, critical network bandwidth and critical network delay are extracted from the monitoring system database, and the system response time impact characteristic value is obtained through comprehensive analysis.

[0017] According to the total amount of system hardware resources, the network bandwidth of each system operation node and the number of parallel users during the monitoring period, the critical system hardware resource total amount, critical network bandwidth and critical number of parallel users are extracted from the monitoring system database, and the system throughput impact characteristic value is obtained through comprehensive analysis.

[0018] According to the system response time influencing characteristic values ​​and the system throughput influencing characteristic values, the system response time influencing characteristic factors and the system throughput influencing characteristic factors are matched, and the critical recharge response time and critical throughput are extracted from the monitoring system database. The system performance evaluation index is obtained by comprehensive analysis of the recharge response time and throughput of each system operation node during the monitoring period.

[0019] As a further method, the system performance evaluation index is a quantitative evaluation data obtained by comprehensively analyzing the recharge response time, throughput, system response time influencing characteristic factors and system throughput influencing characteristic factors of each system operation node within the monitoring period, which is used to quantitatively evaluate the performance of the system and provide a basis for evaluating the comprehensive effectiveness of the system.

[0020] As a further method, the system service quality evaluation index is obtained through processing. The specific process is: based on the system availability, transaction success rate and user complaint resolution rate within the monitoring period, the critical system availability, critical transaction success rate and critical user complaint resolution rate are extracted from the monitoring system database, and the system service quality evaluation index is obtained through comprehensive analysis.

[0021] As a further method, the comprehensive analysis obtains the system comprehensive effectiveness evaluation index. The specific analysis process is: based on the system performance evaluation index and the service quality evaluation index, the comprehensive analysis obtains the system comprehensive effectiveness evaluation index, and the system comprehensive effectiveness evaluation index is used to quantitatively evaluate the comprehensive effectiveness of the system.

[0022] As a further method, the system is evaluated based on the system comprehensive performance evaluation index. The specific evaluation process is: extracting the system comprehensive performance evaluation index threshold from the monitoring system database, comparing the system comprehensive performance evaluation index with the system comprehensive performance evaluation index threshold; if the system comprehensive performance evaluation index is higher than or equal to the system comprehensive performance evaluation index threshold, the system comprehensive performance is evaluated as qualified; if the system comprehensive performance evaluation index is lower than the system comprehensive performance evaluation index threshold, the system comprehensive performance is evaluated as unqualified, and early warning feedback is given to the unqualified system.

[0023] As a further method, the system performance evaluation index, the specific numerical expression is:

[0024] ;

[0025] Where, represents the system performance evaluation index, Indicates the The recharge response time of each system operation node, Indicates the The throughput of the system running nodes, Indicates the critical recharge response time, represents the critical throughput, Indicates the characteristic factor affecting the system response time, Indicates the characteristic factor affecting system throughput.

[0026] On the other hand, the present invention also provides an Internet of Things card intelligent traffic recharge control method, including: S1. collecting system performance data and system operation data.

[0027] S2. Based on the system performance data, a system performance evaluation index is obtained through processing.

[0028] S3. Based on the system operation data, the system service quality evaluation index is obtained through processing.

[0029] S4. Based on the system performance evaluation index and service quality evaluation index, a comprehensive analysis is conducted to obtain the system comprehensive effectiveness evaluation index. Based on the system comprehensive effectiveness evaluation index, the system effectiveness is evaluated, the evaluation results are obtained and feedback is provided.

[0030] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects:

[0031] (1) The present invention provides an IoT card intelligent traffic recharge monitoring system and control method, which comprehensively analyzes system performance and service quality. Based on the system performance evaluation and service quality evaluation results, the system is continuously optimized to ensure that the system achieves the best balance between performance and quality, which helps to improve the overall efficiency of the system, thereby enhancing the system's competitiveness in the market and creating more value. It is also conducive to achieving refined operation and maintenance, thereby reducing operation and maintenance costs.

[0032] (2) By evaluating system performance, the present invention can identify performance bottlenecks and optimize them, thereby improving system operating efficiency. It can also promptly identify system performance issues and take measures to reduce the risk of system failure. At the same time, based on the performance evaluation results, system resources can be rationally planned to meet business development needs, which is conducive to improving the efficiency and stability of the system when processing tasks.

[0033] (3) By evaluating the system service quality, the present invention helps optimize service processes, ensure high system availability, and thus reduce the impact of failures on business. At the same time, evaluating the system service quality helps strengthen system security protection, reduce security risks, enhance user satisfaction, and improve business continuity.

[0034] (4) The present invention clarifies the specific impact of hardware resources on performance. By rationally allocating resources and optimizing hardware resources, the system response time can be reduced, the user experience can be improved, and user satisfaction and loyalty can be increased, which is conducive to reducing system stability problems caused by resource competition or overload. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The present invention is further described with reference to the accompanying drawings. However, the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative effort.

[0036] Figure 1 This is a schematic diagram of system module connections of the present invention.

[0037] Figure 2 Schematic diagram of the functional relationship between the system service quality evaluation index and the system comprehensive effectiveness evaluation index involved in the embodiment of the present invention. DETAILED DESCRIPTION

[0038] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0039] Reference Figure 1 As shown, the first aspect of the present invention provides an Internet of Things card intelligent traffic recharge monitoring system, including: a data acquisition module for collecting system performance data and system operation data.

[0040] Specifically, the collection of system performance data and system operation data includes the following steps: setting a monitoring period, deploying a number of system operation nodes within the monitoring period, and collecting statistics on the system performance data and operation data within the monitoring period.

[0041] The system performance data includes hardware equipment performance data and the recharge response time and throughput of each system operation node within the monitoring period.

[0042] The system operation data includes system availability, transaction success rate and user complaint resolution rate during the monitoring period.

[0043] Furthermore, the hardware device performance data includes the total amount of system hardware resources, the system hardware resource operation speed of each system operation node, network bandwidth, network delay and the number of parallel users during the monitoring period.

[0044] The system performance evaluation module is used to obtain a system performance evaluation index based on system performance data through processing.

[0045] Specifically, the system performance evaluation index is obtained through processing, and the specific process is: according to the system hardware resource operating speed, network bandwidth and network delay of each system operating node during the monitoring period, the critical system hardware resource operating speed, critical network bandwidth and critical network delay are extracted from the monitoring system database, and the system response time impact characteristic value is obtained through comprehensive analysis.

[0046] It should be understood that the system response time impact characteristic value is a quantitative evaluation data obtained through a comprehensive analysis of the system hardware resource operating speed, network bandwidth and network delay of each system operation node during the monitoring period. It is used to quantitatively evaluate the impact of the system response time on the system hardware performance and provide a basis for evaluating the comprehensive performance of the system.

[0047] In a specific embodiment, the numerical expression of the system response time impact characteristic value is:

[0048] ;

[0049] Where, Indicates the system response time affects the characteristic value, represents a natural constant, Indicates the number of each system running node, , Indicates the total number of nodes running in the system. Indicates the system hardware resource running speed of the t-th system running node, represents the network bandwidth of the t-th system running node, represents the network delay of the t-th system running node, Indicates the critical system hardware resource operating speed, Indicates the critical network bandwidth, Indicates critical network delay, Indicates the system response time impact factor corresponding to the preset hardware resource running speed. Indicates the system response time impact factor corresponding to the preset network bandwidth. Indicates the system response time impact factor corresponding to the preset network delay.

[0050] It should be explained that in this embodiment, the operating speed of the system hardware resources specifically refers to the operating speed of the central processing unit, which can be obtained by checking the task manager. The operating speed of the central processing unit will directly affect the speed of processing requests. If the central processing unit is slow, even if the central processing unit utilization is not high, the speed of processing requests will be slow, resulting in an increase in response time. Network bandwidth determines the speed at which data is transmitted in the network. You can use online services such as Speedtest.net to test the speed of your Internet connection, including download and upload bandwidth. If the network bandwidth is insufficient, even if the central processing unit and memory performance are very high, data transmission will become a bottleneck, resulting in an increase in response time. Network latency is the time required for a data packet to be transmitted in the network. You can use traceroute or tracert to view the routers that the data packet passes through to reach the target host, and display the latency of each hop. High latency means that it takes longer for requests and responses to be transmitted in the network, which directly affects the response time.

[0051] It should be explained that in this embodiment, if the hardware resource processing speed is fast but the network bandwidth is insufficient, a bottleneck effect may occur, that is, the processed data cannot be transmitted in time. Conversely, if the network bandwidth is sufficient but the processing speed is slow, it may cause data backlog and fail to fully utilize the bandwidth resources. Fast processing speed helps to reduce the time data waits for processing, thereby indirectly reducing the total network delay. If the processing speed is slow, even if the network delay is low, it may cause the overall response time to become longer. Increasing bandwidth helps to alleviate the delay problem caused by network congestion. Comprehensive analysis of the system hardware resource operating speed, network bandwidth and network delay can make the assessment of the impact of system hardware resources on system response time more comprehensive.

[0052] It should be understood that, from the above embodiments, the greater the operating speed of the system hardware resources, the faster the system hardware resources operate; the larger the network bandwidth, the more sufficient the network bandwidth; the smaller the network delay, the shorter the corresponding system response time, and the smaller the system response time impact characteristic value. It needs to be explained that the impact in this embodiment is a negative impact.

[0053] It should be explained that in this embodiment, the system response time impact factor corresponding to the hardware resource operating speed, the system response time impact factor corresponding to the network bandwidth, and the system response time impact factor corresponding to the network delay have a value range of 0 to 1. Based on the relationship between the system hardware resource operating speed, network bandwidth, and network delay and the system response time impact characteristic value in the historical data, a mapping set of the system hardware resource operating speed, network bandwidth, and network delay and their corresponding system response time impact factors is established. The real-time system hardware resource operating speed, network bandwidth, and network delay are input to obtain the system response time impact factor corresponding to the hardware resource operating speed, the system response time impact factor corresponding to the network bandwidth, and the system response time impact factor corresponding to the network delay from the mapping set. The above impact factors are all extracted from the monitoring system database.

[0054] According to the total amount of system hardware resources, the network bandwidth of each system operation node and the number of parallel users during the monitoring period, the critical system hardware resource total amount, critical network bandwidth and critical number of parallel users are extracted from the monitoring system database, and the system throughput impact characteristic value is obtained through comprehensive analysis.

[0055] It should be understood that the system throughput impact characteristic value is a quantitative evaluation data obtained through a comprehensive analysis of the total amount of system hardware resources, the network bandwidth of each system operation node, and the number of parallel users during the monitoring period. It is used to quantitatively evaluate the impact of system hardware performance on system throughput and provide a basis for evaluating the overall performance of the system.

[0056] In a specific embodiment, the numerical expression of the system throughput impact characteristic value is:

[0057] ;

[0058] Where, Indicates the system throughput impact characteristic value, Indicates the total amount of system hardware resources. represents the network bandwidth of the t-th system running node, Indicates the number of parallel users of the t-th system running node, Indicates the total amount of critical system hardware resources, Indicates the critical network bandwidth, represents the critical number of parallel users, Indicates the system throughput impact factor corresponding to the preset total amount of system hardware resources. Indicates the system throughput impact factor corresponding to the preset network bandwidth. Indicates the system throughput impact factor corresponding to the preset number of parallel users.

[0059] It's important to explain that the total system hardware resources, specifically the total amount of the CPU, memory, and storage, directly determine the system's ability to handle large numbers of tasks. The greater the total resources, the more concurrent tasks the system can theoretically handle, and the higher the throughput. Network bandwidth is one of the bottlenecks for data transmission. If the network bandwidth is insufficient to support large amounts of data transmission, even if the system hardware resources are sufficient, the system's throughput will be limited. The number of concurrent users reflects the number of requests the system needs to process at a given time. As the number of concurrent users increases, system throughput is likely to increase because system resources are fully utilized.

[0060] It should be explained that, in this embodiment, the greater the total amount of hardware resources, the more parallel users can be supported. For example, a higher-performance CPU and a larger memory capacity can handle more requests. Conversely, if hardware resources are limited, other measures need to be taken to optimize system performance, such as load balancing, caching strategies, etc. A higher network bandwidth can support more parallel users to exchange data simultaneously, reducing data transmission delays. If the network bandwidth is insufficient, it may become a bottleneck, limiting the maximum number of parallel users that the system can support. Even if hardware resources are sufficient, if the network bandwidth is limited, it may also affect the performance and service quality of the system. For example, a large number of data transmission requests may cause network congestion, and even if the hardware processing capacity is strong, it cannot be effectively utilized. A comprehensive analysis of the total amount of system hardware resources, network bandwidth, and number of parallel users can make the assessment of the impact of system hardware resources on system throughput more comprehensive and accurate.

[0061] It should be understood that, from the above embodiments, when the total amount of system hardware resources is larger, the network bandwidth is larger, and the number of parallel users is also larger, the corresponding system throughput is larger, and the system throughput impact characteristic value is larger. It should be explained that the impact in this embodiment is a positive impact.

[0062] It should be explained that in this embodiment, the system throughput impact factors corresponding to the total amount of system hardware resources, the system throughput impact factors corresponding to the network bandwidth, and the system throughput impact factors corresponding to the number of parallel users range from 0 to 1. Based on the relationship between the total amount of system hardware resources, network bandwidth, and number of parallel users and the system throughput impact characteristic values ​​in historical data, a mapping set of the total amount of system hardware resources, network bandwidth, and number of parallel users and their corresponding system throughput impact factors is established. The real-time total amount of system hardware resources, network bandwidth, and number of parallel users are input to obtain the system throughput impact factors corresponding to the total amount of system hardware resources, the system throughput impact factors corresponding to the network bandwidth, and the system throughput impact factors corresponding to the number of parallel users from the mapping set. The above impact factors are all extracted from the monitoring system database.

[0063] It should be noted that the above-mentioned embodiments clearly define the specific impact of hardware resources on performance, which helps to rationally allocate resources and avoid resource waste or shortages. By analyzing hardware resource usage, performance bottlenecks can be quickly identified, such as determining whether insufficient CPU processing power or memory capacity limits are causing long response times. Understanding the extent of the impact of hardware resources on performance can provide a basis for decision-making on whether to upgrade hardware and avoid unnecessary costs. Assessing the support of existing hardware resources for system scalability can prepare for future system growth or increased load. Based on hardware resource usage, system performance during peak hours or under increased load can be predicted, allowing resource allocation to be planned in advance. By analyzing the impact of hardware resources on performance and conducting capacity planning, the system can ensure normal operation under the expected load. When a system failure occurs, analyzing hardware resource usage can help determine the cause and accelerate the recovery process. By optimizing hardware resource usage, system response time can be reduced, user experience can be improved, and user satisfaction and loyalty can be increased. It also facilitates the rational allocation and optimization of hardware resources, reducing system stability issues caused by resource competition or overload.

[0064] According to the system response time influencing characteristic values ​​and the system throughput influencing characteristic values, the system response time influencing characteristic factors and the system throughput influencing characteristic factors are matched, and the critical recharge response time and critical throughput are extracted from the monitoring system database. The system performance evaluation index is obtained by comprehensive analysis of the recharge response time and throughput of each system operation node during the monitoring period.

[0065] It should be understood that the system performance evaluation index is a quantitative evaluation data obtained by comprehensively analyzing the recharge response time, throughput, system response time influencing characteristic factors and system throughput influencing characteristic factors of each system operation node during the monitoring period. It is used to quantitatively evaluate the performance of the system and provide a basis for evaluating the comprehensive effectiveness of the system.

[0066] In a specific embodiment, the numerical expression of the system performance evaluation index is:

[0067] ;

[0068] Where, represents the system performance evaluation index, Indicates the recharge response time of the t-th system operation node, represents the throughput of the t-th system running node, Indicates the critical recharge response time, represents the critical throughput, Indicates the characteristic factor affecting the system response time, Indicates the characteristic factor affecting system throughput.

[0069] Table 1 Example of systematic evaluation index data

[0070] serial number Recharge response time (milliseconds) Throughput (requests / second) System Performance Evaluation Index 1 1.5 800 1.302 2 2.5 900 1.146 3 1.0 1100 1.233 4 3.0 700 1.157 5 1.8 1000 1.179

[0071] It should be explained that in this embodiment, the critical recharge response time is set to 2 milliseconds, the critical throughput is set to 1000 requests / second, the system response time impact characteristic factor is set to 0.5, and the system throughput impact characteristic factor is set to 0.8. It should be noted that only a single system is considered in this table.

[0072] It should be understood that, from this embodiment, a longer recharge response time indicates a slower system processing speed, a smaller throughput indicates a lower number of requests processed by the system, and a smaller system performance evaluation index indicates worse system performance.

[0073] It should be explained that response time refers to the time interval from the user initiating a request to the system returning a response. Throughput refers to the number of requests or data volume that the system can process per unit time. System response time and throughput can be collected using performance monitoring tools such as NewRelic, Datadog, Prometheus, etc. In most cases, response time and throughput show an inverse relationship. When throughput increases, in order to process more requests, each request may have to wait longer to be processed, resulting in an increase in response time. As throughput increases, the system may encounter bottlenecks such as insufficient resources such as processors, memory, and disks, which will result in a longer time to process a single request, which in turn leads to an increase in response time.

[0074] It's important to explain that the system performance evaluation index primarily includes metrics such as system processing capacity, response time, throughput, and resource utilization. It reflects the efficiency and stability of the system when processing tasks. System performance evaluation can identify performance bottlenecks and optimize them, thereby improving system efficiency. It can also promptly detect system performance issues and take action to reduce the risk of system failure. Performance evaluation results can also be used to rationally plan system resources to meet business development needs.

[0075] Furthermore, the system response time influencing characteristic factors and the system throughput influencing characteristic factors are matched. The specific matching process is: based on historical experimental data, a mapping set of the system response time influencing characteristic value interval and the system throughput influencing characteristic value interval and the influencing characteristic factor corresponding to their intervals is constructed, the real-time system response time influencing characteristic value and the system throughput influencing characteristic value are obtained, and the intervals in which the system response time influencing characteristic value and the system throughput influencing characteristic value are respectively matched, and the influencing characteristic factor corresponding to the system response time influencing characteristic value and the influencing characteristic factor corresponding to the system throughput influencing characteristic value are obtained from the mapping set.

[0076] It should be explained that the matching of the influencing characteristic factors in the above embodiment can help identify which factors have the greatest impact on system response time and throughput, thereby accurately locating performance bottlenecks. The influencing characteristic factors provide quantitative indicators for performance issues, making performance evaluation more scientific and accurate. By comparing the weights of different influencing characteristic factors, it can be determined which performance issues need to be addressed first, thereby rationally allocating resources and optimizing work. Understanding the influencing characteristic factors can help predict future trends in system performance, thereby taking preventive measures to avoid potential failures. The analysis of influencing characteristic factors can provide direction for performance optimization, such as improving performance by adjusting configuration, optimizing algorithms, or increasing resources. By analyzing the influencing characteristic factors, system resources can also be managed more effectively, such as adjusting load balancing strategies based on key influencing factors of throughput.

[0077] The service quality evaluation module is used to obtain the system service quality evaluation index based on the system operation data through processing.

[0078] Specifically, the system service quality evaluation index is obtained after processing. The specific process is: based on the system availability, transaction success rate and user complaint resolution rate within the monitoring period, the critical system availability, critical transaction success rate and critical user complaint resolution rate are extracted from the monitoring system database, and the system service quality evaluation index is obtained through comprehensive analysis.

[0079] It should be understood that the system service quality evaluation index is a quantitative evaluation data obtained through a comprehensive analysis of system availability, transaction success rate and user complaint resolution rate within the monitoring period. It is used to quantitatively evaluate the service quality of the system and provide a basis for evaluating the overall effectiveness of the system.

[0080] In a specific embodiment, the specific expression of the system service quality evaluation index is:

[0081] ;

[0082] Where, represents the system service quality evaluation index, Indicates the system availability during the monitoring period. Indicates the transaction success rate within the monitoring period, Indicates the user complaint resolution rate within the monitoring period. Indicates critical system availability, represents the critical transaction success rate, represents the critical user complaint resolution rate, Indicates the system service quality impact factor corresponding to the preset system availability, Indicates the system service quality impact factor corresponding to the preset transaction success rate, Indicates the system service quality impact factor corresponding to the preset user complaint resolution rate.

[0083] It's important to explain that system availability refers to the system's ability to operate normally within a predetermined timeframe, specifically the probability that the system is in an acceptable service state. A high-availability system is able to respond to user requests at any given time. System availability is often expressed as "n nines," such as 99.9%, 99.99%, and so on. The higher the number, the higher the system's availability. The transaction success rate refers to the percentage of transactions successfully completed by the system. A system with a high transaction success rate means that most transactions are successfully completed without failure due to system failures or errors. The user complaint resolution rate refers to the percentage of user complaints successfully resolved by the system or service provider. An efficient complaint resolution mechanism can promptly and effectively resolve user issues and improve user satisfaction. The above parameters can all be obtained by processing data recorded by system log tools.

[0084] It should be noted that in this embodiment, high system availability generally means a lower system failure rate, thus increasing transaction success rates. Low system availability can lead to transaction failures or interruptions, thereby reducing transaction success rates. When system availability is high, users encounter fewer problems, resulting in fewer complaints. However, even in a high-availability system, effective mechanisms are required to quickly resolve inevitable issues and improve user complaint resolution rates. A high transaction success rate generally means fewer transaction problems, which in turn reduces user complaints. When a transaction fails, an efficient user complaint resolution process can quickly resolve the issue, improve user satisfaction, and indirectly increase future transaction success rates. A comprehensive analysis of system availability, transaction success rate, and user complaint resolution rate can provide a more comprehensive and accurate assessment of system service quality.

[0085] It should be understood that, from the above embodiments, the greater the system availability, the stronger the system's ability to operate normally during the monitoring period; the greater the system transaction success rate, the fewer system failures during the monitoring period; the greater the user complaint resolution rate, the stronger the system's ability to solve problems; and the corresponding system service quality evaluation index is greater, indicating that the system's service quality is higher.

[0086] It should be explained that in this embodiment, the system service quality impact factors corresponding to system availability, transaction success rate, and user complaint resolution rate range from 0 to 1. Based on the relationship between system availability, transaction success rate, and user complaint resolution rate in historical data and the system service quality evaluation index, a mapping set of system availability, transaction success rate, and user complaint resolution rate and their corresponding system service quality impact factors is established. By inputting real-time system availability, transaction success rate, and user complaint resolution rate, the system service quality impact factors corresponding to system availability, transaction success rate, and user complaint resolution rate are obtained from the mapping set. These impact factors are all extracted from the monitoring system database.

[0087] It's important to explain that the system service quality evaluation index primarily encompasses reliability, availability, security, and user experience. It reflects the degree of user satisfaction and business continuity during the system's service delivery. Evaluating system service quality not only prioritizes user experience but also helps optimize service processes, thereby increasing user satisfaction. It also ensures high system availability and minimizes the impact of failures on business operations. It also helps strengthen system security and mitigate security risks.

[0088] The comprehensive performance evaluation and early warning module is used to obtain the system comprehensive performance evaluation index based on the system performance evaluation index and the service quality evaluation index through comprehensive analysis, evaluate the system performance based on the system comprehensive performance evaluation index, obtain the evaluation results and provide feedback.

[0089] Specifically, a comprehensive analysis is performed to obtain a comprehensive system performance evaluation index. The specific analysis process is as follows: based on the system performance evaluation index and the service quality evaluation index, a comprehensive analysis is performed to obtain a comprehensive system performance evaluation index. The comprehensive system performance evaluation index is used to quantitatively evaluate the comprehensive performance of the system. The higher the comprehensive system performance evaluation index, the better the comprehensive performance of the system.

[0090] In a specific embodiment, the numerical expression of the system comprehensive effectiveness evaluation index is:

[0091] ;

[0092] Where, represents the comprehensive performance evaluation index of the system, represents a natural constant, represents the system performance evaluation index, represents the system service quality evaluation index, Indicates the comprehensive performance impact factor corresponding to the preset system performance evaluation index, Indicates the comprehensive performance impact factor corresponding to the preset system service quality evaluation index.

[0093] It should be understood that, from the above embodiments, when the system performance evaluation index is larger and the system service quality evaluation index is also larger, the system comprehensive effectiveness evaluation index is larger, indicating that the system comprehensive effectiveness is better.

[0094] It should be explained that, in this embodiment, the comprehensive effectiveness impact factor corresponding to the system performance evaluation index is set to 0.6, and the comprehensive effectiveness impact factor corresponding to the system service quality evaluation index is set to 0.4.

[0095] It should be understood that if Figure 2 As shown, curve a represents the relationship between the system service quality evaluation index and the system comprehensive effectiveness evaluation index when the system performance evaluation index is 1.047, curve b represents the relationship between the system service quality evaluation index and the system comprehensive effectiveness evaluation index when the system performance evaluation index is 1.103, and curve c represents the relationship between the system service quality evaluation index and the system comprehensive effectiveness evaluation index when the system performance evaluation index is 1.336.

[0096] It should be explained that in this embodiment, the comprehensive efficiency impact factor corresponding to the system performance evaluation index and the comprehensive efficiency impact factor corresponding to the system service quality evaluation index range from 0 to 1. Based on the relationship between the system performance evaluation index and the system service quality evaluation index in historical data and the system comprehensive efficiency evaluation index, a mapping set of the system performance evaluation index and the system service quality evaluation index and their corresponding comprehensive efficiency impact factors is established. The real-time system performance evaluation index and the system service quality evaluation index are input to obtain the comprehensive efficiency impact factor corresponding to the system performance evaluation index and the comprehensive efficiency impact factor corresponding to the system service quality evaluation index from the mapping set. The above-mentioned impact factors are all extracted from the monitoring system database.

[0097] It should be explained that system comprehensive effectiveness refers to the system's comprehensive performance in terms of performance, service, cost, and benefits. It is a comprehensive assessment of the system's overall strength. In this embodiment, there is a close connection between the system performance evaluation index, the system service quality evaluation index, and system comprehensive effectiveness. System performance is the foundation, and service quality is the guarantee; together, they determine the level of system comprehensive effectiveness. The system performance evaluation index and the service quality evaluation index influence each other and contribute to system comprehensive effectiveness. Optimizing any one of these aspects can improve system comprehensive effectiveness, and synergistic optimization is more conducive to improving system comprehensive effectiveness. By improving system performance and service quality, the system's competitiveness in the market can be enhanced and more value can be created. Through continuous evaluation of system performance and service quality, refined operation and maintenance can be achieved, reducing operation and maintenance costs. Good system performance and service quality support business innovation and promote business development. In practical applications, while pursuing high-performance systems, system service quality should not be neglected to ensure the optimal balance between performance and quality. Based on the results of system performance and service quality evaluations, continuous optimization is carried out to improve system comprehensive effectiveness. System evaluation is conducted from multiple angles and levels to fully understand the system status. Make full use of evaluation data to provide strong support for system improvement. Always pay attention to user needs, focus on improving user experience, and improve the overall efficiency of the system.

[0098] Furthermore, the system is evaluated based on the system comprehensive performance evaluation index. The specific evaluation process is as follows: the system comprehensive performance evaluation index threshold is extracted from the monitoring system database, and the system comprehensive performance evaluation index is compared with the system comprehensive performance evaluation index threshold. If the system comprehensive performance evaluation index is higher than or equal to the system comprehensive performance evaluation index threshold, the system comprehensive performance is evaluated as qualified; if the system comprehensive performance evaluation index is lower than the system comprehensive performance evaluation index threshold, the system comprehensive performance is evaluated as unqualified, and an early warning feedback is given to the unqualified system.

[0099] In a specific embodiment, the data in the monitoring system database includes the data extracted in the above embodiments, such as the critical system hardware resource operating speed, critical network bandwidth, and critical network delay, the system throughput impact factor corresponding to the total amount of system hardware resources, the system throughput impact factor corresponding to the network bandwidth, and the system throughput impact factor corresponding to the number of parallel users, as well as the threshold of the system comprehensive performance evaluation index. The data in the monitoring system database can be obtained by using a RESTful API or a Graph QL interface and then through an HTTP request. Alternatively, special tools or frameworks can be used to help obtain data according to the system technology stack, such as Django's ORM, Laravel's Eloquent ORM, etc.

[0100] The second aspect of the present invention provides an Internet of Things card intelligent traffic recharge control method, including: S1. collecting system performance data and system operation data.

[0101] S2. Based on the system performance data, a system performance evaluation index is obtained through processing.

[0102] S3. Based on the system operation data, the system service quality evaluation index is obtained through processing.

[0103] S4. Based on the system performance evaluation index and service quality evaluation index, a comprehensive analysis is conducted to obtain the system comprehensive effectiveness evaluation index. Based on the system comprehensive effectiveness evaluation index, the system effectiveness is evaluated, the evaluation results are obtained and feedback is provided.

[0104] Specifically, the specific process of the control method is to evaluate the system's performance based on the system's comprehensive performance evaluation indicators, and issue early warning prompts for unqualified systems. When the system's comprehensive performance indicators reach the early warning conditions, relevant personnel need to be notified through email, text messages, instant messaging tools, etc. The alarm information should contain sufficient information, such as the type of problem, the scope of impact, and recommended solutions. Develop an emergency response plan to ensure that specific actions are taken immediately after receiving the early warning. Then use problem tracking systems such as JIRA and Bugzilla to record early warning events and handling processes. Finally, analyze the root cause of the early warning event and record the solution for future reference. Through the above-mentioned early warning feedback process, continuous optimization of system performance can be achieved.

[0105] The above content is merely an example and explanation of the structure of the present invention. Those skilled in the art may make various modifications or additions to the described specific embodiments or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the scope of protection of the present invention.

Claims

1. An IoT card intelligent traffic recharge monitoring system, characterized in that: include: Data collection module, used to collect system performance data and system operation data; The specific process of collecting system performance data and system operation data is as follows: setting a monitoring period, deploying a number of system operation nodes within the monitoring period, and collecting statistics on system performance data and operation data within the monitoring period; The system performance data includes hardware equipment performance data and the recharge response time and throughput of each system operation node within the monitoring period; The system operation data includes system availability, transaction success rate and user complaint resolution rate within the monitoring period; A system performance evaluation module, used to obtain a system performance evaluation index based on system performance data through processing; The system performance evaluation index is obtained through processing, and the specific process is: according to the system hardware resource operation speed, network bandwidth and network delay of each system operation node in the monitoring period, the critical system hardware resource operation speed, critical network bandwidth and critical network delay are extracted from the monitoring system database, and the system response time impact characteristic value is obtained through comprehensive analysis; According to the total amount of system hardware resources, network bandwidth of each system operation node and the number of parallel users during the monitoring period, the critical total amount of system hardware resources, critical network bandwidth and critical number of parallel users are extracted from the monitoring system database, and the system throughput impact characteristic value is obtained through comprehensive analysis; According to the system response time influencing characteristic value and the system throughput influencing characteristic value, the system response time influencing characteristic factor and the system throughput influencing characteristic factor are matched, and the critical recharge response time and critical throughput are extracted from the monitoring system database. The system performance evaluation index is obtained by comprehensive analysis of the recharge response time and throughput of each system operation node within the monitoring period. The specific numerical expression of the system performance evaluation index is: ； In the formula, represents the system performance evaluation index, Indicates the recharge response time of the tth system operation node, represents the throughput of the tth system running node, Indicates the critical recharge response time, represents the critical throughput, Indicates the characteristic factor affecting the system response time, Indicates the characteristic factor affecting system throughput; A service quality evaluation module is used to obtain a system service quality evaluation index based on system operation data after processing; The specific expression of the system service quality evaluation index is: ； In the formula, represents the system service quality evaluation index, Indicates the system availability during the monitoring period. Indicates the transaction success rate within the monitoring period. Indicates the user complaint resolution rate within the monitoring period. represents critical system availability, represents the critical transaction success rate, represents the critical user complaint resolution rate, Indicates the system service quality impact factor corresponding to the preset system availability, Indicates the system service quality impact factor corresponding to the preset transaction success rate, Indicates the system service quality impact factor corresponding to the preset user complaint resolution rate; The comprehensive performance evaluation and early warning module is used to obtain the system comprehensive performance evaluation index based on the system performance evaluation index and the service quality evaluation index through comprehensive analysis, and to evaluate the system performance based on the system comprehensive performance evaluation index, obtain the evaluation results and provide feedback; The numerical expression of the system comprehensive effectiveness evaluation index is: ； In the formula, represents the comprehensive performance evaluation index of the system, e represents the natural constant, represents the system performance evaluation index, represents the system service quality evaluation index, Indicates the comprehensive performance impact factor corresponding to the preset system performance evaluation index, Indicates the comprehensive performance impact factor corresponding to the preset system service quality evaluation index; t represents the number of each system running node, , s represents the total number of running nodes in the system.

2. According to claim 1, an Internet of Things card intelligent flow recharge monitoring system is characterized in that: The hardware equipment performance data includes the total amount of system hardware resources, the system hardware resource operation speed of each system operation node, network bandwidth, network delay and the number of parallel users during the monitoring period.

3. According to claim 1, an Internet of Things card intelligent flow recharge monitoring system is characterized in that: The system performance evaluation index is a quantitative evaluation data obtained by comprehensively analyzing the recharge response time, throughput, system response time influencing characteristic factors and system throughput influencing characteristic factors of each system operation node within the monitoring period, and is used to quantitatively evaluate the performance of the system and provide a basis for evaluating the comprehensive effectiveness of the system.

4. According to claim 1, an Internet of Things card intelligent flow recharge monitoring system is characterized in that: The system service quality evaluation index is obtained through processing, and the specific process is as follows: According to the system availability, transaction success rate and user complaint resolution rate within the monitoring period, the critical system availability, critical transaction success rate and critical user complaint resolution rate are extracted from the monitoring system database, and the system service quality evaluation index is obtained through comprehensive analysis.

5. According to claim 4, an Internet of Things card intelligent flow recharge monitoring system is characterized in that: The comprehensive analysis obtains the system comprehensive performance evaluation index, and the specific analysis process is as follows: According to the system performance evaluation index and the service quality evaluation index, a comprehensive analysis is performed to obtain a system comprehensive effectiveness evaluation index, which is used to quantitatively evaluate the comprehensive effectiveness of the system.

6. According to claim 5, an Internet of Things card intelligent flow recharge monitoring system is characterized in that: The system is evaluated based on the comprehensive system performance evaluation index, and the specific evaluation process is as follows: The system comprehensive performance evaluation index threshold is extracted from the monitoring system database, and the system comprehensive performance evaluation index is compared with the system comprehensive performance evaluation index threshold. If the system comprehensive performance evaluation index is higher than or equal to the system comprehensive performance evaluation index threshold, the system comprehensive performance is evaluated as qualified; if the system comprehensive performance evaluation index is lower than the system comprehensive performance evaluation index threshold, the system comprehensive performance is evaluated as unqualified, and an early warning feedback is given to the unqualified system.

7. A method for an Internet of Things card intelligent flow recharge monitoring system as described in any one of claims 1 to 6, characterized in that: include: S1. Collect system performance data and system operation data; S2. According to the system performance data, a system performance evaluation index is obtained through processing; S3. Based on the system operation data, the system service quality evaluation index is obtained after processing; S4. Based on the system performance evaluation index and service quality evaluation index, a comprehensive analysis is conducted to obtain the system comprehensive effectiveness evaluation index. Based on the system comprehensive effectiveness evaluation index, the system is evaluated for effectiveness, the evaluation results are obtained and feedback is provided.

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