Communication System Stability Evaluation Method and Device

Abstract

The present invention provides a method and apparatus for evaluating the stability of a communication system. The method includes: receiving subscribed messages in Kafka, where Kafka is used to publish operation behavior information of multiple data tables in the background database of the centralized business support system cBSS; screening out valid data from the subscribed messages in Kafka; converting the valid data into a first preset data and / or a second preset data; calculating corresponding evaluation scores according to the first preset data and / or the second preset data, so as to evaluate the stability of cBSS through the evaluation scores. The present invention can automatically collect the monitoring metrics of the centralized business support system cBSS, analyze and integrate the monitoring metrics, and obtain evaluation scores reflecting the stability of cBSS, thereby objectively and quickly reflecting the operating conditions of cBSS.

Description

Technical Field

[0001] The present invention relates to the field of communication technologies, and in particular, to a method and device for evaluating the stability of a communication system. Background Art

[0002] A central Business Support System (cBSS) is a communication system that centrally manages the core systems in the business support system domain. After the cBSS is put into operation, it is necessary to monitor the running status of the system to obtain the stability of the system operation and timely discover problems in the system operation.

[0003] Currently, various monitoring indicators of the cBSS usually rely on manual judgment and evaluation to discover existing problems, and the manual evaluation results are used as the basis for evaluating the system stability.

[0004] However, this method is usually time-consuming and laborious. It is necessary to view system logs and program running status through various methods, or make a comprehensive judgment based on manual experience and combined with other monitoring indicators of the system. Therefore, the entire evaluation process has complicated steps, and the evaluation results are easily affected by subjective factors, with low accuracy and low efficiency. Summary of the Invention

[0005] The present invention provides a method and device for evaluating the stability of a communication system, so as to automatically collect monitoring indicators of the central Business Support System cBSS, analyze and integrate the monitoring indicators, obtain an evaluation score reflecting the stability of the cBSS, and thus objectively and quickly obtain the running status of the cBSS.

[0006] In a first aspect, the present invention provides a method for evaluating the stability of a communication system, including:

[0007] Receiving subscription messages in Kafka, where Kafka is used to publish operation behavior information of multiple data tables in the background database of the central Business Support System cBSS;

[0008] Filtering out valid data from the subscription messages in Kafka;

[0009] Converting the valid data into first preset data and / or second preset data;

[0010] Calculating a corresponding evaluation score according to the first preset data and / or the second preset data, so as to evaluate the stability of the cBSS through the evaluation score.

[0011] Optionally, the filtering out valid data from the subscription messages in Kafka includes:

[0012] Receive the subscribed messages in the Kafka through Storm, and filter the subscribed messages to screen out the valid data. Among them, the subscribed messages refer to the operation behavior information of multiple data tables in the background database of cBSS. The data tables include: business work order table, call detail record table. The operation behavior information includes: insertion information of the data table, update information of the data table. The valid data refers to the preset monitoring indicators for analyzing the stability of cBSS.

[0013] Optionally, the preset monitoring indicators for analyzing the stability of cBSS include: database DBTime, execution time of Structured Query Language (SQL) statements, processing time of user call rating process, processing time of user call centralized collection process, and partition situation of each processing process in the time period of call processing.

[0014] Optionally, before converting the valid data into the first preset data and / or the second preset data, it further includes:

[0015] Store the valid data in an in-memory database;

[0016] Determine the target monitoring indicators from the in-memory database and present the target monitoring indicators in the form of a chart.

[0017] Optionally, the first preset data refers to the values of the monitoring indicators of cBSS within the target time period of each day, and the average value of the monitoring indicators within the target time period in the preset cycle obtained by statistics; the second preset data refers to the distribution quantity of the monitoring indicators of cBSS within each value range in the preset cycle.

[0018] Optionally, calculating the corresponding evaluation score according to the first preset data and / or the second preset data includes:

[0019] Store the first preset data and / or the second preset data in an in-memory database;

[0020] Determine the target monitoring indicators from the in-memory database;

[0021] Calculate the evaluation score corresponding to the target monitoring indicator through the first preset data and / or calculate the corresponding evaluation score through the second preset data.

[0022] Optionally, the formula for calculating the evaluation score corresponding to the target monitoring indicator through the first preset data is as follows:

[0023]

[0024] Where: Q is the evaluation score corresponding to the target monitoring index calculated through the first preset data, r is the average value of the target monitoring index during the target time period within the preset cycle, and c is the value of the target monitoring index during the target time period on the current day.

[0025] Optionally, the formula for calculating the evaluation score corresponding to the target monitoring index through the second preset data is as follows:

[0026] S = normalize(S i + S N )

[0027] S i = w i * p i

[0028] S N = w N *(1 - x 0.5 )* e -x

[0029] Where: S is the evaluation score corresponding to the target monitoring index calculated through the second preset data, S i is the basic evaluation score of the i-th value interval, i is a natural number greater than or equal to 0, S N is the auxiliary evaluation score, normalize(S i + S N ) is to normalize S i + S N to a value between the interval [0, 100], w i is the weight of the i-th value interval, p i is the proportion of the number of target monitoring indicators within the i-th value interval to the number of target monitoring indicators within the preset cycle, w N is the weight of the auxiliary evaluation score, and x is a value between the interval [0, 1].

[0030] Optionally, it further includes:

[0031] Presenting the evaluation score of the target monitoring index in the form of a chart.

[0032] In a second aspect, the present invention provides a communication system stability evaluation device, including:

[0033] A receiving module, configured to receive subscription messages in Kafka, where Kafka is used to publish operation behavior information of multiple data tables in the background database of the collection centralized business support system cBSS;

[0034] A screening module, configured to screen out valid data from the subscription messages in Kafka;

[0035] A conversion module for converting the valid data into first preset data and / or second preset data;

[0036] An evaluation module for calculating corresponding evaluation scores based on the first preset data and / or the second preset data to evaluate the stability of cBSS through the evaluation scores.

[0037] Optionally, the screening module is specifically configured to:

[0038] Receive the subscribed messages in the Kafka through Storm, filter the subscribed messages, and screen out the valid data, where the subscribed messages refer to the operation behavior information of multiple data tables in the background database of cBSS, the data tables include: business work order table, call detail record table, and the operation behavior information includes: insertion information of the data table, update information of the data table; the valid data refers to the preset monitoring indicators for analyzing the stability of cBSS.

[0039] Optionally, the preset monitoring indicators for analyzing the stability of cBSS include: database DBTime, execution time of Structured Query Language (SQL) statements, processing time of user call rating process, processing time of user call centralized collection process, and partition situation of each processing process during the time period of call processing. Optionally, it further includes a storage module for storing the valid data into an in-memory database before converting the valid data into first preset data and / or second preset data;

[0040] Determine the target monitoring indicators from the in-memory database and present the target monitoring indicators in the form of a chart.

[0041] Optionally, the first preset data refers to the values of the monitoring indicators of cBSS during the target time period of each day, and the average value of the monitoring indicators during the target time period within the preset period; the second preset data refers to the distribution quantity of the monitoring indicators of cBSS within each value range within the preset period.

[0042] Optionally, the evaluation module is specifically configured to:

[0043] Store the first preset data and / or the second preset data into the in-memory database;

[0044] Determine the target monitoring indicators from the in-memory database;

[0045] Calculate the evaluation scores corresponding to the target monitoring indicators through the first preset data and / or calculate the corresponding evaluation scores through the second preset data.

[0046] Optionally, the formula for calculating the evaluation scores corresponding to the target monitoring indicators through the first preset data is as follows:

[0047]

[0048] Where: Q is the evaluation score corresponding to the target monitoring index calculated from the first preset data, r is the mean value of the target monitoring index within the target time period in the preset cycle, and c is the value of the target monitoring index within the target time period on the current day.

[0049] Optionally, the formula for calculating the evaluation score corresponding to the target monitoring index from the second preset data is as follows:

[0050] S = normalize(S i + S N )

[0051] S i = w i * p i

[0052] S N = w N *(1 - x 0.5 )* e -x

[0053] Where: S is the evaluation score corresponding to the target monitoring index calculated from the second preset data, S i is the basic evaluation score of the i-th value interval, i is a natural number greater than or equal to 0, S N is the auxiliary evaluation score, normalize(S i + S N ) is to normalize S i + S N to a value between the interval [0, 100], w i is the weight of the i-th value interval, p i is the proportion of the number of target monitoring indexes within the i-th value interval to the number of target monitoring indexes in the preset cycle, w N is the weight of the auxiliary evaluation score, and x is a value between the interval [0, 1].

[0054] Optionally, it further includes a display module for presenting the evaluation score of the target monitoring index in the form of a chart.

[0055] In a third aspect, the present invention provides a communication system stability evaluation device, including:

[0056] A memory for storing programs;

[0057] A processor for executing the program stored in the memory. When the program is executed, the processor is used to execute any one of the methods in the first aspect.

[0058] In a fourth aspect, the present invention provides a computer-readable storage medium, including: instructions which, when running on a computer, cause the computer to execute the method described in any one of the first aspect.

[0059] The communication system stability evaluation method and device provided by the present invention collect monitoring metrics of the centralized business support system cBSS and store them in Kafka; screen out valid data from Kafka; convert the valid data into first preset data and / or second preset data; calculate corresponding evaluation scores according to the first preset data and / or the second preset data, so as to evaluate the stability of cBSS through the evaluation scores. The present invention can automatically collect the monitoring metrics of the centralized business support system cBSS, analyze and integrate the monitoring metrics, and obtain evaluation scores reflecting the stability of cBSS, thereby objectively and quickly reflecting the operating conditions of cBSS. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] To more clearly illustrate the technical solutions in the embodiments of the present invention or in the prior art, the following briefly introduces the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0061] Figure 1 It is a schematic diagram of the application scenario of the communication system stability evaluation method provided by the present invention;

[0062] Figure 2 It is a flowchart of the communication system stability evaluation method provided in Embodiment 1 of the present invention;

[0063] Figure 3 It is a flowchart of the communication system stability evaluation method provided in Embodiment 2 of the present invention;

[0064] Figure 4 It is a schematic structural diagram of the communication system stability evaluation device provided in Embodiment 3 of the present invention;

[0065] Figure 5 It is a schematic structural diagram of the communication system stability evaluation device provided in Embodiment 4 of the present invention;

[0066] Figure 6 It is a schematic structural diagram of the communication system stability evaluation device provided in Embodiment 5 of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0067] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Apparently, the described embodiments are some but not all of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0068] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and do not necessarily need to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0069] The following will specifically describe the technical solutions of the present invention with specific embodiments. These several specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments.

[0070] The following will explain some terms in this application to facilitate the understanding of those skilled in the art:

[0071] 1) Kafka is a high-throughput distributed publish-subscribe messaging system that can handle all action stream data in websites with a large number of consumers. Such actions (web page browsing, searching, and other user actions) are a key factor in many social functions on modern networks. These data are usually addressed by processing logs and log aggregation due to throughput requirements. The purpose of Kafka is to unify online and offline message processing through the parallel loading mechanism of Hadoop and also to provide real-time consumption through a cluster.

[0072] 2) DB Time is an important metric for analyzing the performance of an Oracle database in the time dimension. By gradually decomposing this metric, the primary events of wasting resources or resource contention can be located, so as to achieve the optimization purpose by reducing waiting and minimizing the resource usage of each request. DB Time (request time) = DB Wait Time (DB waiting time) + DB CPU Time (DB CPU service time).

[0073] 3) Structured Query Language (SQL). Structured Query Language is a database query and programming language used to access data and query, update, and manage relational database systems. SQL statements are a language for operating on databases.

[0074] 4) Storm is a free and open-source, distributed, highly fault-tolerant real-time computing system. Storm makes continuous stream computing easy, making up for the real-time requirements that cannot be met by Hadoop batch processing. It is often used in fields such as real-time analysis, online machine learning, continuous computing, distributed remote calls, and ETL. Therefore, it is very convenient and fast to use Storm for real-time processing of system data. For the received Kafka messages, first perform the first-level filtering. After filtering out the unnecessary information, further process the valid information.

[0075] The communication system stability evaluation method provided by the present invention has obvious advantages compared with the method of manually judging and evaluating to discover the problems of cBSS. The existing evaluation methods need to view system logs and program running status through various methods, or make comprehensive judgments based on manual experience combined with other system monitoring indicators. Therefore, the entire evaluation process has complicated steps, and the evaluation results are easily affected by subjective factors, with low accuracy and low efficiency.

[0076] The communication system stability evaluation method provided by the present invention aims to solve the above technical problems of the prior art.

[0077] The technical solutions of the present invention and how the technical solutions of this application solve the above technical problems will be described in detail below with specific embodiments. These several specific embodiments below can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present invention will be described below with reference to the accompanying drawings.

[0078] Figure 1 It is a schematic diagram of the application scenario of the communication system stability evaluation method provided by the present invention. As Figure 1 shown, first, use the operation data of the centralized business support system cBSS as the data source, obtain the monitoring indicators of cBSS according to the operation data, and store the monitoring indicators of cBSS in Kafka; then use Storm to read the monitoring indicators in Kafka, filter and distribute the read monitoring indicators, and store them in the in-memory database. Finally, process and analyze the target monitoring indicators in the in-memory database to obtain the evaluation score of cBSS, and this evaluation score is used to evaluate the stability of cBSS.

[0079] Figure 2The flowchart of the communication system stability evaluation method provided in Embodiment 1 of the present invention is as follows. Figure 2 As shown in the figure, the method in this embodiment may include:

[0080] S101. Receive the subscribed messages in Kafka.

[0081] In this embodiment, Kafka is used to publish the operation behavior information of multiple data tables in the background database of the collection and centralized business support system cBSS. Kafka is a high-throughput distributed publish-subscribe messaging system that can handle all action stream data in websites with a large number of consumers. It is easy to scale outwards and provides high throughput for both publishing and subscribing; it supports multiple subscribers, can automatically balance consumers when failures occur, and persists messages to disk, so it can be used for batch consumption, such as ETL, and real-time applications. Among them, the monitoring metrics are: the execution time of the DBTime statement, the execution time of the Structured Query Language (SQL) statement, the user call bill rating processing time, the user call bill centralized collection processing time, and the partition situation of the call bill processing time.

[0082] S102. Filter out the valid data from the subscribed messages in Kafka.

[0083] In this embodiment, Storm can be used to receive the subscribed messages in Kafka and filter the subscribed messages to filter out the valid data. Among them, the subscribed messages refer to the operation behavior information of multiple data tables in the background database of cBSS. The data tables include: the business work order table and the call detail record table. The operation behavior information includes: the insertion information of the data table and the update information of the data table. The valid data refers to the preset monitoring metrics for analyzing the stability of cBSS. Storm is used to perform real-time processing on the subscribed messages read from Kafka and filter the subscribed messages to filter out the unnecessary monitoring metrics to obtain the valid data. Among them, the preset monitoring metrics for analyzing the stability of cBSS include: the database DBTime, the execution time of the Structured Query Language (SQL) statement, the processing time of the user call bill rating process, the processing time of the user call bill centralized collection process, and the partition situation of each processing process of the call bill processing in the time period.

[0084] S103. Convert the valid data into the first preset data and / or the second preset data.

[0085] In this embodiment, the valid data is converted into the first preset data and / or the second preset data in a preset format. The first preset data refers to the values of the monitoring metrics of the cBSS during the target time period of each day, as well as the average value of the monitoring metrics during the target time period within the preset period obtained through statistics. The second preset data refers to the distribution quantity of the monitoring metrics of the cBSS within each value range within the preset period. In this embodiment, the forms of the first preset data and the second preset data are not limited. Theoretically, the data format can be appropriately adjusted according to the stability evaluation parameters of the cBSS. For example, it can also be the peak value of the monitoring metrics of the cBSS during the preset time period, or the number of times the monitoring metrics of the cBSS appear within the target value range, etc.

[0086] S104. Calculate the corresponding evaluation score according to the first preset data and / or the second preset data, so as to evaluate the stability of the cBSS through the evaluation score.

[0087] In this embodiment, by integrating and analyzing the first preset data and / or the second preset data, the corresponding evaluation score is calculated, so as to evaluate the stability of the cBSS through the evaluation score.

[0088] Optionally, store the first preset data and / or the second preset data in the in-memory database; determine the target monitoring metrics from the in-memory database; calculate the evaluation score corresponding to the target monitoring metrics through the first preset data and / or calculate the corresponding evaluation score through the second preset data. Among them, the formula for calculating the evaluation score corresponding to the target monitoring metrics through the first preset data is as follows:

[0089]

[0090] In the formula: Q is the evaluation score corresponding to the target monitoring metrics calculated through the first preset data, r is the average value of the target monitoring metrics during the target time period within the preset period, and c is the value of the target monitoring metrics during the target time period of the current day.

[0091] The formula for calculating the evaluation score corresponding to the target monitoring metrics through the second preset data is as follows:

[0092] S = normalize(S i +S N )

[0093] S i =w i *p i

[0094] S N =w N *(1 - x 0.5 )*e -x

[0095] Where: S is the evaluation score corresponding to the target monitoring index calculated from the second preset data, S i is the basic evaluation score of the i-th value interval, i is a natural number greater than or equal to 0, S N is the auxiliary evaluation score, normalize(S i +S N ) means normalizing S i +S N to a value between the interval [0, 100], w i is the weight of the i-th value interval, p i is the ratio of the number of target monitoring indexes in the i-th value interval to the number of target monitoring indexes in the preset period, w N is the weight of the auxiliary evaluation score, and x is a value between the interval [0, 1].

[0096] Optionally, in order to more clearly and intuitively reflect the stability of the communication system, the evaluation score of the target monitoring index can also be presented in the form of a chart.

[0097] Specifically, the influxdb and grafana architectures can be adopted to achieve automated chart display. Influxdb is an open-source distributed time series, time, and metrics database, and granfana is an open source graphical data display tool that can customize data sources, custom reports, display data, etc.

[0098] In this embodiment, by receiving subscription messages in Kafka; screening out valid data from the subscription messages in Kafka; converting the valid data into first preset data and / or second preset data; calculating the corresponding evaluation score according to the first preset data and / or second preset data, so as to evaluate the stability of cBSS through the evaluation score. The present invention can automatically collect the monitoring indexes of the centralized business support system cBSS, analyze and integrate the monitoring indexes, and obtain the evaluation score reflecting the stability of cBSS, so as to objectively and quickly obtain the operating conditions of cBSS.

[0099] Figure 3 is the flowchart of the communication system stability evaluation method provided by the second embodiment of the present invention. As Figure 3 shown, the method in this embodiment may include:

[0100] S201. Receive subscription messages in Kafka.

[0101] S202. Screen out valid data from the subscription messages in Kafka.

[0102] In this embodiment, for the specific implementation processes of step S201 and step S202, refer to Figure 2 the relevant descriptions in the method shown, which will not be elaborated here.

[0103] S203. Store the valid data in an in-memory database.

[0104] In this embodiment, an in-memory database (such as redis, influxdb, etc.) can be used to store the valid data. Compared with disks, the data read and write speed of memory is several orders of magnitude higher. Saving data in memory can greatly improve the performance of the application compared with accessing data from disks. The in-memory database abandons the traditional way of disk data management, redesigns the architecture for all data in memory, and also makes corresponding improvements in data caching, fast algorithms, and parallel operations. Therefore, the data processing speed is much faster than that of traditional databases, generally more than 10 times. Thus, valid data can be better stored and the processing efficiency of valid data can be improved.

[0105] S204. Determine the target monitoring metrics from the in-memory database and present the target monitoring metrics in the form of a chart.

[0106] In this embodiment, the target monitoring metrics can be first selected from the in-memory database and presented in the form of a chart. For example, the changes in the target monitoring metrics within a preset period are characterized in the form of a line chart, so that before calculating the evaluation score, the obtained chart can be manually analyzed to preliminarily obtain the operating status of cBSS. Specifically, influxdb and grafana can be used to automatically build the monitoring chart, or the monitoring chart interface can be established by writing html code to display the target monitoring metrics. Through the display of the monitoring chart, it can help the staff judge the system operating status based on experience, and can also indirectly verify the analysis result of the evaluation score to ensure the accuracy of the evaluation result of the communication system.

[0107] S205. Convert the valid data into the first preset data and / or the second preset data.

[0108] S206. Calculate the corresponding evaluation score according to the first preset data and / or the second preset data to evaluate the stability of cBSS through the evaluation score.

[0109] In this embodiment, for the specific implementation processes of step S205 and step S206, refer to Figure 2 the relevant descriptions in the method shown, which will not be elaborated here.

[0110] In this embodiment, subscription messages in Kafka are received; valid data is filtered out from the subscription messages in Kafka; the valid data is stored in an in-memory database, target monitoring metrics are determined from the in-memory database, and the target monitoring metrics are presented in the form of a chart. Additionally, the valid data is converted into first preset data and / or second preset data; corresponding evaluation scores are calculated based on the first preset data and / or the second preset data, so as to evaluate the stability of cBSS through the evaluation scores. The present invention can automatically collect the monitoring metrics of the centralized business support system cBSS, present the target monitoring metrics in the form of a chart, and analyze and integrate the monitoring metrics to obtain an evaluation score reflecting the stability of cBSS, thereby objectively and quickly obtaining the operating status of cBSS and ensuring the accuracy of the evaluation results of the communication system.

[0111] Figure 4 FIG. 4 is a structural schematic diagram of a communication system stability evaluation device provided in Embodiment 3 of the present invention, as Figure 4 shown, the device in this embodiment may include:

[0112] A receiving module 10, configured to receive subscription messages in Kafka;

[0113] A filtering module 20, configured to filter out valid data from the subscription messages in Kafka;

[0114] A conversion module 30, configured to convert the valid data into first preset data and / or second preset data;

[0115] An evaluation module 40, configured to calculate corresponding evaluation scores based on the first preset data and / or the second preset data, so as to evaluate the stability of cBSS through the evaluation scores.

[0116] Optionally, the filtering module 20 is specifically configured to:

[0117] Receive the subscription messages in Kafka through Storm, filter the subscription messages, and filter out valid data, where the subscription messages refer to the operation behavior information of multiple data tables in the background database of cBSS, the data tables include: business work order table, call detail record table, and the operation behavior information includes: insertion information of the data table, update information of the data table; the valid data refers to the monitoring metrics preset for analyzing the stability of cBSS.

[0118] Optionally, the preset monitoring metrics for analyzing the stability of cBSS include: database DBTime, execution time of Structured Query Language (SQL) statements, processing time of user call bill rating process, processing time of user call bill centralized collection process, and partitioning situation of each processing process of call bill processing in the time period. Optionally, the first preset data refers to the values of the monitoring metrics of cBSS within the target time period every day, and the average value of the monitoring metrics within the target time period in the preset period obtained by statistics; the second preset data refers to the distribution quantity of the monitoring metrics of cBSS within each value range in the preset period.

[0119] Optionally, the evaluation module 40 is specifically configured to:

[0120] Store the first preset data and / or the second preset data into the in-memory database;

[0121] Determine the target monitoring metrics from the in-memory database;

[0122] Calculate the evaluation score corresponding to the target monitoring metrics through the first preset data and / or calculate the corresponding evaluation score through the second preset data.

[0123] Optionally, the formula for calculating the evaluation score corresponding to the target monitoring metrics through the first preset data is as follows:

[0124]

[0125] In the formula: Q is the evaluation score corresponding to the target monitoring metrics calculated through the first preset data, r is the average value of the target monitoring metrics within the target time period in the preset period, and c is the value of the target monitoring metrics within the target time period on the current day.

[0126] Optionally, the formula for calculating the evaluation score corresponding to the target monitoring metrics through the second preset data is as follows:

[0127] S = normalize(S i + S N )

[0128] S i = w i * p i

[0129] S N = w N * (1 - x 0.5 ) * e -x

[0130] In the formula: S is the evaluation score corresponding to the target monitoring metrics calculated through the second preset data, S iis the basic evaluation score for the i-th value range, where i is a natural number greater than or equal to 0, and S N is the auxiliary evaluation score, and normalize(S i +S N ) is to normalize S i +S N to a value between the range [0, 100]. w i is the weight for the i-th value range, and p i is the ratio of the number of target monitoring indicators within the i-th value range to the number of target monitoring indicators within a preset period. w N is the weight of the auxiliary evaluation score, and x is a value between the range [0, 1].

[0131] Optionally, it further includes a display module for presenting the evaluation score of the target monitoring indicator in the form of a chart.

[0132] This embodiment can execute the technical solutions in the above Figure 2 and Figure 3 shown methods. The implementation process and technical effects are similar to those of the above methods and will not be elaborated here.

[0133] Figure 5 is a schematic structural diagram of a communication system stability evaluation device provided in Embodiment 4 of the present invention. As Figure 5 shown, on the basis of the device shown in Figure 4 , this embodiment of the device may further include:

[0134] A storage module 50 for storing the valid data into an in-memory database before converting the valid data into the first preset data and / or the second preset data;

[0135] Determine the target monitoring indicators from the in-memory database and present the target monitoring indicators in the form of a chart.

[0136] This embodiment can execute the technical solutions in the above Figure 2 and Figure 3 shown methods. The implementation process and technical effects are similar to those of the above methods and will not be elaborated here.

[0137] Figure 6 is a schematic structural diagram of a communication system stability evaluation device provided in Embodiment 5 of the present invention. As Figure 6 shown, the communication system stability evaluation device 60 in this embodiment may include:

[0138] A processor 61 and a memory 62; where:

[0139] The memory 62 is used to store executable instructions, and this memory may also be flash (flash memory).

[0140] A processor 61 for executing executable instructions stored in a memory to implement each step in the methods involved in the above embodiments. For details, reference may be made to the relevant descriptions in the foregoing method embodiments.

[0141] Optionally, the memory 62 can be either independent or integrated with the processor 61.

[0142] When the memory 62 is a device independent of the processor 61, the electronic terminal 60 may further include:

[0143] A bus 63 for connecting the memory 62 and the processor 61.

[0144] In addition, an embodiment of the present application further provides a computer-readable storage medium. Computer-executable instructions are stored in the computer-readable storage medium. When at least one processor of a user device executes the computer-executable instructions, the user device executes the above various possible methods.

[0145] Among them, the computer-readable medium includes a computer storage medium and a communication medium. The communication medium includes any medium facilitating the transmission of a computer program from one place to another. The storage medium can be any available medium accessible by a general or special-purpose computer. An exemplary storage medium is coupled to the processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an ASIC. Additionally, the ASIC can be located in a user device. Of course, the processor and the storage medium can also exist as discrete components in a communication device.

[0146] Those of ordinary skill in the art can understand that all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions. The foregoing program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps including those of the above method embodiments; and the foregoing storage medium includes: ROM, RAM, magnetic disk, or optical disk, etc., which can store program codes.

[0147] 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 them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for evaluating the stability of a communication system, characterized in that, including: Receiving subscribed messages in Kafka, where the Kafka is used to publish operation behavior information of multiple data tables in the background database of the convergent business support system cBSS; Filtering out valid data from the subscribed messages in Kafka; Converting the valid data into first preset data and / or second preset data; The first preset data refers to the values of the monitoring metrics of cBSS during the target time period of each day, and the average value of the monitoring metrics during the target time period within a preset period obtained through statistics; The second preset data refers to the distribution quantity of the monitoring metrics of cBSS within each value range within a preset period; Calculating corresponding evaluation scores based on the first preset data and / or the second preset data to evaluate the stability of cBSS through the evaluation scores; wherein, storing the first preset data and / or the second preset data into an in-memory database; determining target monitoring metrics from the in-memory database; calculating the evaluation scores corresponding to the target monitoring metrics through the first preset data and / or calculating the corresponding evaluation scores through the second preset data; The formula for calculating the evaluation score corresponding to the target monitoring metric through the first preset data is as follows: In the formula: Q is the evaluation score corresponding to the target monitoring metric calculated through the first preset data, r is the average value of the target monitoring metric during the target time period within a preset period, and c is the value of the target monitoring metric during the target time period of the current day; The formula for calculating the evaluation score corresponding to the target monitoring metric through the second preset data is as follows: S = normalize(S i + S N ) S i = w i * p i S N = w N *(1 - x 0.5 )*e -x Where: S is the evaluation score corresponding to the target monitoring index calculated through the second preset data, S i is the basic evaluation score of the i-th value interval, i is a natural number greater than or equal to 0, S N is the auxiliary evaluation score, normalize(S i +S N ) is to normalize S i +S N to a value between the interval [0, 100], w i is the weight of the i-th value interval, p i is the ratio of the number of target monitoring indexes in the i-th value interval to the number of target monitoring indexes in the preset period, w N is the weight of the auxiliary evaluation score, and x is a value between the interval [0, 1].

2. The method according to claim 1, characterized in that, The filtering out valid data from the subscribed messages in Kafka includes: Receiving the subscribed messages in the Kafka through Storm and filtering the subscribed messages to filter out valid data, where the subscribed messages refer to the operation behavior information of multiple data tables in the background database of cBSS, the data tables include: business work order tables, call detail record tables, and the operation behavior information includes: insertion information of the data tables, update information of the data tables; the valid data refers to the preset monitoring metrics for analyzing the stability of cBSS.

3. The method according to claim 2, characterized in that, The preset monitoring metrics for analyzing the stability of cBSS include: database DBTime, execution time of SQL statements, processing time of user call rating process, processing time of user call centralized collection process, and partition situation of each processing process of call processing in the time period.

4. The method according to claim 1, characterized in that, Before converting the valid data into the first preset data and / or the second preset data, it further includes: Storing the valid data into an in-memory database; Determining target monitoring metrics from the in-memory database and presenting the target monitoring metrics in a graphical manner.

5. The method according to claim 1, characterized in that, It further includes: Presenting the evaluation scores of the target monitoring metrics in a graphical manner.

6. A device for evaluating the stability of a communication system, characterized in that, including: A receiving module for receiving subscribed messages in Kafka, where the Kafka is used to publish operation behavior information of multiple data tables in the background database of the convergent business support system cBSS; A filtering module for filtering out valid data from the subscribed messages in Kafka; A conversion module, configured to convert the valid data into first preset data and / or second preset data; The first preset data refers to the values of the monitoring metrics of cBSS within the target time period of each day, as well as the average value of the monitoring metrics within the target time period in the preset period obtained through statistics; The second preset data refers to the distribution quantities of the monitoring metrics of cBSS within each value range in the preset period; An evaluation module, configured to calculate corresponding evaluation scores according to the first preset data and / or the second preset data, so as to evaluate the stability of cBSS through the evaluation scores; wherein, storing the first preset data and / or the second preset data into an in-memory database; determining a target monitoring metric from the in-memory database; calculating an evaluation score corresponding to the target monitoring metric through the first preset data and / or calculating a corresponding evaluation score through the second preset data; The formula for calculating the evaluation score corresponding to the target monitoring metric through the first preset data is as follows: In the formula: Q is the evaluation score corresponding to the target monitoring metric calculated through the first preset data, r is the average value of the target monitoring metric within the target time period in the preset period, and c is the value of the target monitoring metric within the target time period of the current day; The formula for calculating the evaluation score corresponding to the target monitoring metric through the second preset data is as follows: S = normalize(S i + S N ) S i = w i * p i S N = w N *(1 - x 0.5 )*e -x Where: S is the evaluation score corresponding to the target monitoring index calculated through the second preset data, S i is the basic evaluation score of the i-th value interval, i is a natural number greater than or equal to 0, S N is the auxiliary evaluation score, normalize(S i +S N ) is to normalize S i +S N to a value between the interval [0, 100], w i is the weight of the i-th value interval, p i is the ratio of the number of target monitoring indexes in the i-th value interval to the number of target monitoring indexes in the preset period, w N is the weight of the auxiliary evaluation score, and x is a value between the interval [0, 1].

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