CN110516928B

CN110516928B - Decision method, device, equipment and computer readable medium for business private line

Info

Publication number: CN110516928B
Application number: CN201910734027.6A
Authority: CN
Inventors: 任凌舒; 罗全锋
Original assignee: Advanced New Technologies Co Ltd
Current assignee: Advanced New Technologies Co Ltd; Advantageous New Technologies Co Ltd
Priority date: 2019-08-09
Filing date: 2019-08-09
Publication date: 2023-08-22
Anticipated expiration: 2039-08-09
Also published as: CN110516928A

Abstract

The embodiment of the specification discloses a decision method, a decision device, decision equipment and a computer-readable medium for a special service line. The decision method of the service private line comprises the following steps: acquiring service statistics information of a service private line in a preset time period based on a message center at preset time intervals, wherein the preset time intervals are smaller than a first time period, the preset time period is smaller than a second time period, and the message center is used for caching the service information of the service private line; calculating service index information according to the service statistical information; determining state information of the special service line based on the service index information and a preset service index threshold; and making a decision on the special service line according to the state information of the special service line.

Description

Decision method, device, equipment and computer readable medium for business private line

Technical Field

The present application relates to the field of computer technologies, and in particular, to a method, an apparatus, a device, and a computer readable medium for deciding a service private line.

Background

In a financial network system, dedicated lines of business may be used for financial data exchange between individual financial institutions. In this context, financial institutions generally refer to institutions engaged in financial activities, such as, for example, internet, banking, various banks, third party payment institutions, securities, funds, insurance companies, and the like. In the use process of the special service line, network link abnormality caused by various reasons may occur. For example, a dedicated link between two opponent financial institutions may occur due to network link congestion caused by a large amount of traffic in a short time, or the like. For another example, a link between the third party payment mechanism and the internet/silver link may be abnormal in a private line due to a system failure of a certain machine room of one party.

Generally, it is possible to determine whether an abnormality occurs in a dedicated line of service by querying and analyzing historical service data of the dedicated line of service from a log, and then reject the abnormal dedicated line. In the existing decision method based on the data source collected by the log, the system is required to output and store each service in the form of the log, then analyze, correlate, summarize and calculate the log, and in the process of data processing, the data can be written into an external stable storage system, such as a distributed file system, which can cause a large amount of data delay caused by data replication, disk I/O and the like, so that the timeliness of the current special line decision of the service is not high, usually in the order of minutes. However, for large clearing organizations, the timeliness of decisions is critical. For example, the total amount of business processed per minute can reach millions of levels by using business special lines established between large clearing organizations and opponents, and the business processed by each business special line can reach hundreds of thousands of levels. In view of this, there is a need to provide a low-latency, high-aging service line decision scheme.

Disclosure of Invention

In view of this, embodiments of the present application provide a method, an apparatus, a device, and a computer readable medium for determining a dedicated line of service, which are used to improve the timeliness of the dedicated line of service in determining the dedicated line of service.

In order to solve the above technical problems, the embodiments of the present specification are implemented as follows:

the decision method of the service private line provided by the embodiment of the specification comprises the following steps: acquiring service statistics information of a service private line in a preset time period based on a message center at preset time intervals, wherein the preset time intervals are smaller than a first time period, the preset time period is smaller than a second time period, and the message center is used for caching the service information of the service private line; calculating service index information according to the service statistical information; determining state information of the special service line based on the service index information and a preset service index threshold; and making a decision on the special service line according to the state information of the special service line.

The decision device of a service private line provided in the embodiment of the present specification includes: the acquisition module is used for acquiring the business statistics information of the business special line in a preset time period based on the message center at preset time intervals, wherein the preset time intervals are smaller than the first time period, the preset time period is smaller than the second time period, and the message center is used for caching the business information of the business special line; the calculating module is used for calculating service index information according to the service statistical information; the judging module is used for determining the state information of the special service line based on the service index information and a preset service index threshold value; and the decision module is used for deciding the special service line according to the state information of the special service line.

The decision device of a service private line provided in the embodiment of the present specification includes:

at least one processor; the method comprises the steps of,

a memory communicatively coupled to the at least one processor; wherein,,

the memory stores instructions executable by the at least one processor to enable the at least one processor to:

acquiring service statistics information of a service private line in a preset time period based on a message center at preset time intervals, wherein the preset time intervals are smaller than a first time period, the preset time period is smaller than a second time period, and the message center is used for caching the service information of the service private line; calculating service index information according to the service statistical information; determining state information of the special service line based on the service index information and a preset service index threshold; and making a decision on the special service line according to the state information of the special service line.

Embodiments of the present disclosure provide a computer readable medium having computer readable instructions stored thereon, where the computer readable instructions are executable by a processor to implement the above-described business specific line decision method.

The above-mentioned at least one technical scheme that this description embodiment adopted can reach following beneficial effect:

the method comprises the steps of firstly acquiring business statistics information of a business private line in a preset time period smaller than a second time period based on a message center at a preset time interval smaller than a first time period, calculating business index information according to the business statistics information, then determining state information of the business private line based on the business statistics information and a preset index threshold value, and finally making a decision on the business private line based on the state information. Based on the scheme, the data acquisition is performed through the message center instead of the data acquisition system based on the log, compared with the traditional business private line decision method, the time delay caused by data replication, disk I/O and the like in the process of using the log data acquisition is avoided, and the timeliness of business private line decision is improved.

Drawings

The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a limitation on the application. In the drawings:

FIG. 1 shows a flow diagram of a decision method for a business specific line according to an embodiment;

FIG. 2 shows a schematic diagram of a decision flow of a business specific line decision method according to an embodiment;

FIG. 3 shows a schematic diagram of a decision link of a business specific decision method according to an embodiment;

fig. 4 shows a schematic structural diagram of a decision device of a dedicated service line according to an embodiment;

fig. 5 shows a schematic structural diagram of a decision device of a dedicated service line according to an embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be clearly and completely described below with reference to specific embodiments of the present application and corresponding drawings. It will be apparent that the described embodiments are only some, but not all, embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.

The following describes in detail the technical solutions provided by the embodiments of the present application with reference to the accompanying drawings.

Fig. 1 shows a flow diagram of a decision method for a dedicated line of business according to an embodiment. From the program perspective, the execution subject of the flow may be a program or an application client that is installed on an application server.

As shown in fig. 1, the process may include the steps of:

s110: and acquiring the service statistics information of the service private line in a preset time period based on the message center at preset time intervals, wherein the preset time intervals are smaller than the first time period, the preset time period is smaller than the second time period, and the message center is used for caching the service information of the service private line.

The special service line is a special link for transmitting data in the data network, so that the transmission of user data is safe and reliable, and a plurality of special service lines can be arranged between two terminals and/or servers. In general, in order to enhance the load capacity and stability of a service, a plurality of special lines of the service are provided between two or more designated nodes, for example, a plurality of special lines of the service may be provided between a banking institution and a third party payment institution for transmitting various information between the banking institution and the third party payment institution, such as performing service processing such as payment, refund, inquiry, etc.

Wherein the traffic statistics reflects statistics of traffic conditions performed on the traffic line. For example, the service statistics information includes, but is not limited to, service request number information, system success/failure number information, communication success/failure number information, and the like over a service line for a predetermined period of time.

The message center may be a device for caching service information of a service private line, and in particular, acquiring service statistics based on the message center may specifically refer to acquiring the service statistics based on real-time data acquisition data sources. According to an embodiment, an implementation manner of acquiring service statistics based on a message center may be as follows: for a certain special service line, periodically collecting single service statistical information of each application using the special service line for data transmission in a preset time period, sending the single service statistical information to a message center, summarizing the single service statistical information in the message center to obtain total service statistical information of the special service line in the preset time period, and inquiring the counted service statistical information in the preset time period at preset time intervals.

The preset time interval may refer to a certain frequency to acquire service statistics, and the preset time interval may be less than a first duration, where the first duration may be not greater than 60 seconds, more preferably not greater than 20s, and even more preferably not greater than 10s. For example, service statistics of a service private line may be queried every 3 s. Wherein the predetermined time period may be a last time period before the current time, the predetermined time period may be less than a second time period, and the second time period may be not more than 60 seconds, more preferably not more than 20 seconds, still more preferably not more than 10 seconds. For example, the traffic statistics of each statistics may be statistics based on traffic data within the first 5s of the current time. Wherein the first time period and the second time period may be the same or different. The duration of the preset time interval may be the same as or different from the duration of the predetermined time period. For example, the preset time interval may be 2s-3s and the duration of the preset time period may be 5s-10s.

The scheme of taking the log data as the standby data source ensures the usability of the whole business special line decision system and improves the stability of the system under the condition that the data cannot be normally acquired from the single data source.

S120: and calculating service index information according to the service statistical information.

The service index information may represent an index calculated based on the service statistics information, and may be used to represent a state of a service line. According to an embodiment, the traffic index information may include, but is not limited to, traffic request number information per unit time, system success/failure rate per unit time, communication success/failure rate per unit time, and the like. Wherein, the unit time may refer to each second time, that is, the service index may be a second level index.

According to an embodiment, before calculating the traffic index information according to the traffic statistics information, the method may further include: checking whether the service statistical information accords with service index information calculation conditions or not to obtain a first check result; if the first checking result is no, exiting the decision process; the calculating the service index information according to the service statistics information specifically includes calculating the service index information according to the service statistics information if the first verification result is yes.

According to an embodiment, the verifying whether the service statistics information meets the service index information calculation condition may specifically include: and checking whether all the required service statistical information is acquired. For example, when all of the number of service requests, the number of system successes/failures, and the number of communication successes/failures on the service line within a predetermined period of time are acquired, the integrity check is considered to be passed, and the first check result is yes, the acquired service statistics information may be used to calculate the service index information. For example, when at least one of the three types of data cannot be acquired, or when the acquired service request quantity information is zero, the integrity check is considered to be failed, if the first check result is no, the index calculation is not continued, and the decision process is directly exited.

S130: and determining the state information of the special service line based on the service index information and a preset service index threshold value.

The preset service index threshold value can be used for comparing with the service index information, and according to a comparison result, corresponding state information of the service private line is obtained. The traffic indicator threshold may represent an operating parameter of the traffic line under normal use conditions.

According to an embodiment, the service indicator threshold may be calculated according to historical service statistics of the service private line, or may be set empirically. In any case, the traffic index threshold value for performing the abnormality determination is preset. Even when the business index threshold is calculated from historical data, the business index threshold is calculated and stored offline in advance, rather than being calculated in real-time during the real-time decision process. Such a setting makes it possible to avoid unnecessary delay of the decision link due to calculation of the index threshold value and to improve the timeliness of the decision link.

S140: and making a decision on the special service line according to the state information of the special service line.

The state information may indicate that the dedicated line is in a normal state or an abnormal state. Wherein making a decision on the dedicated line may include not performing any operation on the dedicated line when the dedicated line is in a normal state; and when the special service line is in an abnormal state, executing a rejection operation and/or executing an alarm notification for the special service line.

Wherein, the step of eliminating the special line means that the transaction does not reach the opponent mechanism through the special line any more. For example, if there are N special lines between the third party payment mechanism and the internet, in the case of peer-to-peer data distribution, each special line carries 1/N traffic, if one of the special lines is removed, all the services are carried by the remaining N-1 special lines, and in the case of peer-to-peer data distribution, each special line carries 1/(N-1) traffic.

According to an optional embodiment, the deciding the dedicated service line according to the state information of the dedicated service line specifically includes: if the state information of the special service line indicates that the special service line is in an abnormal state, judging whether the special service line meets a special line rejection condition or not; and if the special line rejection condition is met, rejecting the service special line.

According to an embodiment, the dedicated line eliminating condition may include, for example, conditions that at least a predetermined number of dedicated lines may be used, at least a predetermined proportion of dedicated lines may be used, at least a predetermined number of dedicated lines may be used within the same area, at least a predetermined proportion of dedicated lines may be used within the same area, etc., but is not limited thereto.

In this embodiment, when the special service line is abnormal, the rejection operation is not directly performed, but is performed only when a predetermined special line rejection condition is satisfied, that is, based on the configuration conditions of all special lines of the current organization, risk prevention and control are performed to ensure the minimum number of special lines in a usable state, so as to ensure the overall stable availability of the service system.

In addition, according to the embodiment, an alarm notification may be sent to a development maintainer or the like for the special line of the business determined to be abnormal, so that the maintainer performs manual intervention on the special line of the abnormal business.

According to one or more embodiments described above, a method for deciding a dedicated line of service is provided. In the scheme provided by the application, the index information of the special business line is acquired by collecting the data source based on the real-time data of the message center instead of summarizing the data source based on the log data, so that the data delay is low and the timeliness of the second-level decision is improved. In addition, before the abnormal special lines are rejected, the rejection condition is judged, so that the minimum quantity of the special lines is ensured, and related business information cannot be transmitted due to the fact that the quantity of the special lines is too small and the like is avoided.

Based on the above examples, the present application also provides the following implementation manners of the improved service private line decision method.

According to an alternative embodiment, the method for deciding a dedicated service line further includes: when the acquisition of the service statistics information of the service dedicated line based on the message center at S110 fails, the service statistics information of the service dedicated line may optionally be acquired based on log data of the service dedicated line. The log data acquisition can specifically adopt a monitoring platform based on log analysis and taking a service as a core, such as an XFLUSH platform. Here, the data delay of acquiring the service statistics information based on the system log data acquisition data source is about 30s, and the data delay of the mode of acquiring the data by the real-time data acquisition data source is about 5s, so that the decision method of the service private line adopts the real-time data acquisition system based on the message center by default, and only when the real-time data acquisition system fails, the system log based data acquisition system is adopted as the data source.

In the embodiment, the system log is used as a standby data source, and when the real-time data source is unavailable, the system log is automatically switched to the log data source, so that the normal operation of a decision system model is ensured, the normal embodiment of a decision scheme is ensured, and the stability of a decision system is improved.

According to an alternative embodiment, in S130, the preset index threshold may be a baseline threshold pre-calculated according to historical service information of the dedicated service line. Specifically, the baseline threshold may be calculated prior to S110. Specifically, historical service statistical information of a service private line in a preset time period within a date selected according to a preset rule is obtained; and calculating a baseline threshold value corresponding to the business special line and the preset time period based on the historical business statistical information.

The historical service statistics information may include, but is not limited to, historical service request number information, historical system success/failure number information, historical communication success/failure number information, and the like. The baseline threshold value calculated according to the historical traffic statistics information may include a total traffic baseline threshold value, a system success number baseline threshold value, a system success rate baseline threshold value, a communication success rate baseline threshold value, and the like, but is not limited thereto.

Wherein the date selected according to the predetermined rule may be, for example, several days selected according to a certain rule before the current date. The calculation of the baseline threshold may take, for example, 1 minute as a time window, and statistically calculate the baseline of the historical business statistics data distribution in the same minute every day in the selected date, and then take the baseline as the baseline threshold of the business statistics in the minute corresponding to the day to be decided. For example, determining whether the traffic index of a certain traffic dedicated line is abnormal in the period of 10:00:00-10:01:00 today may be determined based on a baseline threshold calculated from historical traffic statistics of the traffic dedicated line in the period of 10:00:00-10:01:00 daily in a selected historical date as the traffic index threshold. For another example, determining whether a second-level traffic index of a traffic line is abnormal in any period of 10:00:00-10:00:05, 10:00:10-10:00:15, 10:00:20-10:00:22, etc. may be based on a baseline threshold calculated from historical traffic statistics of the traffic line in a period of 10:00:00-10:01:00 daily in a selected historical date.

According to an embodiment, in S130, the determining the state information of the dedicated line based on the service indicator information and a preset service indicator threshold may specifically include: acquiring a baseline threshold value of the special service line corresponding to the preset time period; judging whether the business index information meets a first judging condition or not based on the baseline threshold value; and if the first judging condition is met, determining the state information of the special service line as an abnormal state.

Wherein the first determination condition is a determination condition having the baseline threshold value as a parameter. As an example, the first decision condition may be TPS > = tps_threshold & (CSS < = css_base | (sys_tssy < = sys_tssy_base | and sys_tss < = sys_tss_base)), where TPS represents the number of transaction requests per second, tps_threshold represents the success rate of communication per second, css_base represents the BASELINE THRESHOLD of success rate of communication, sys_tssy represents the number of system success per second, sys_tssy represents the BASELINE THRESHOLD of system success per second, sys_tss represents the system success rate per second, and sys_tss_base represents the BASELINE THRESHOLD of system success rate per second, the special line is abnormal if the decision condition is satisfied.

In this embodiment, the baseline threshold corresponding to the predetermined period of time may be calculated in advance, rather than in real-time, which avoids unnecessary data delays in making the anomaly determination. In addition, the baseline threshold value calculated based on the historical business statistics is a predicted value substantially, and is a predicted value of the corresponding business private line in the corresponding time period, and compared with the mode of judging by using a fixed value in the traditional judging method, the judgment is more accurate, and the special line abnormal condition is more sensitive to the identification.

According to an embodiment, before the determining whether the traffic index information meets the first determination condition based on the baseline threshold value, the method may further include: checking whether all required baseline thresholds are acquired or not to obtain a second checking result; if the second check result is negative, judging whether the service index information meets a second judging condition or not based on an experience threshold value; if the second judging condition is met, determining the state information of the special service line as an abnormal state; the step of judging whether the business index information meets the first judging condition based on the baseline threshold value specifically comprises judging whether the business index information meets the first judging condition based on the baseline threshold value if the second checking result is yes.

Specifically, it may be checked whether all the required baseline thresholds are acquired, for example, whether all of the historical service request number information, the historical system success/failure number information, and the historical communication success/failure number information of the corresponding times are acquired. For example, if only a part of the three is acquired, or the number of historical service requests is zero, the integrity check is not passed.

Specifically, in the case where the integrity check is not passed, the determination method is switched to use the empirical threshold as an index threshold to perform the determination. The empirical threshold may be preset threshold information, for example, the empirical threshold of the number of service requests per second information may be 30, the empirical threshold of the system success rate per second may be 60%, and the empirical threshold of the communication success rate per second may be 50%. Specifically, the second determination condition may be a determination condition having an empirical threshold as a parameter. Based on the foregoing example, the second determination condition may be TPS > =30 & & (CSS <60% |sys_tss < 50%), and if this condition is satisfied, the dedicated line of service is considered abnormal.

In the above embodiment, the baseline threshold calculated based on the historical business statistics is used to compare with the index information of the corresponding time period of the business special line to obtain the judging information, and the baseline threshold is calculated according to the historical data of the corresponding time period, so that the judging result is more accurate and reliable, and the judging result is more sensitive to the abnormal judgment of the special line. In addition, an experience threshold is used as a standby index threshold, and double insurance of baseline threshold judgment and experience threshold judgment is adopted, so that on the premise of ensuring service effect, the abnormality of a special service line is accurately and rapidly identified.

In the process of data transmission of a service dedicated line, data link jitter may occur due to a network, for example, a service performed according to a certain time sequence, a processing receipt of a service sent first may be later than a processing receipt of a service sent later due to the data jitter, or two service requests sent according to a first time interval, where a second time interval between received processing receipts is different from the first time interval. The second-level decision of the special service line is carried out, and the problem that the jitter deviation of data is increased in the second-level environment is solved.

According to an optional embodiment, the verifying whether the service statistics information meets the service index information calculation condition, to obtain a first verification result may further include: and checking whether the statistical time period corresponding to the service statistical information meets a preset time range or not to obtain a first check result. Specifically, if the first check result is no, exiting the decision process; if the first check result is yes, calculating service index information according to the service statistical information.

Specifically, before calculating the service index information by using the service statistics information, it is further required to check whether the service index information meets a certain data jitter threshold condition, that is, check whether a statistics period corresponding to the service statistics information is within a predetermined time range. More specifically, for example, if the deviation between the corresponding statistical period of the traffic total amount statistical information and the corresponding statistical period of the traffic success-failure statistical information in the traffic statistical information is smaller than a predetermined threshold value, the traffic success rate may be calculated using both. For example, if the deviation between the corresponding statistical period of the traffic total amount statistical information and the corresponding statistical period of the communication success or failure statistical information in the traffic statistical information is smaller than a predetermined threshold value, the communication success or failure rate may be calculated using both. For example, the predetermined threshold may be 30s, that is, when the deviation of the actual statistical periods corresponding to the acquired two or more pieces of traffic statistics from each other is not more than 30s, data alignment may not be required, and the acquired two or more pieces of traffic statistics may be directly used to calculate traffic index information.

According to an embodiment, calculating service index information according to the service statistics information specifically includes: and calculating the service success rate of the preset time period by adopting the service success-failure statistical information of the first time period and the service total amount statistical information of the second time period, wherein the time deviation between the first time period and the preset time period and the time deviation between the second time period and the preset time period are not more than the third time period. Wherein the third duration may be 30s, alternatively the third duration may be 20s, alternatively the third duration may be 10s, alternatively the third duration may be 5s, but is not limited thereto.

Specifically, for example, the state of the special line of the service in the period of 10:00:30-10:00:35 is to be decided, and it is ideal that the statistical information of the total amount of the service and the statistical information of the success or failure of the service in the period of 10:00:30-10:00:35 are obtained, and the system success or failure rate in the period of 10:00:30-10:00:35 is calculated by using the statistical information of the total amount of the service and the statistical information of the success or failure of the service. However, due to reasons such as data jitter, the service statistics information of the period of 10:00:30-10:00:35 may not be accurately counted, at this time, an actual period of service data corresponding to the actually obtained service statistics information needs to be determined, and if the deviation between the actual statistics period and the predetermined statistics period is not greater than the predetermined third duration, the obtained actual statistics period may be directly used to calculate the service index. For example, if the third duration is 30s, when the period of time corresponding to the actually obtained traffic statistics is within a period of time of 10:00:00-10:01:05, for example, the traffic statistics corresponding to the period of time of 10:00:00-10:00:05, 10:00:13-10:00:18, 10:00:40-10:00:45, etc. may be used to calculate the traffic index of the period of time of 10:00:30-10:00:35 to be decided.

When data jitter occurs, but the deviation of the data jitter satisfies a predetermined threshold range, the accuracy of the business index data is not greatly affected, and at the moment, the business index data can be directly calculated by using business statistical data satisfying the predetermined deviation without performing data alignment operation, so that the timeliness of the private line decision is improved.

In order to further reduce the impact on decision results caused by data jitter in a second level decision scenario, the present application uses the following improved data processing method to calculate traffic index information.

According to an alternative embodiment, the calculating the service index information according to the service statistics information may specifically include: calculating service success rate information according to the service abnormal quantity statistical information and the service total quantity statistical information by the following formula: service success rate information= (traffic total amount statistical information-traffic abnormal amount statistical information)/traffic total amount statistical information.

Specifically, when the traffic number information includes a total number of traffic per second and a number of communication failures per second, the communication success rate per second can be calculated by: communication success rate per second= (total number of traffic per second-number of communication failures per second)/total number of traffic per second. When the traffic number information includes a total number of traffic per second and a number of system failures per second, a system success rate per second can be calculated by: system per second success rate= (total number of traffic per second-number of system failures per second)/total number of traffic per second.

In an actual business scenario, for example, in the case of many processing tasks at night, a transaction curve may appear in a steep increase or decrease scenario, for example, the transaction amount per unit time is 2000 beats/second in the last second and 100 beats/second in the next second. Under the condition of tolerating a certain data jitter deviation (for example, 30 s), assuming that the business transaction amount data points as denominators are 00:00:25-00:00:30 and the transaction work amount data points as molecules are 00:00:00-00:00:05, the data dislocation can lead to inaccurate decision values and further lead to erroneous decisions in the process of calculating the success rate. More specifically, assume that the real business transaction amount at 00:00:00-00:00:05 is 10000, wherein the transaction success number is 9980, and the transaction failure number is 20; assuming that the real business transaction amount is 500 in the range of 00:00:25-00:00:30, wherein the transaction success number is 499 and the transaction failure number is 1; then, the true transaction success rates at 00:00:00-00:00:05 and 00:00:25-00:00:30 are 499/500 (0.9998). If the transaction success rate is calculated according to the success rate, assuming that the data jitter occurs, the actual acquired transaction amount of the service from 00:00:00 to 00:00:05 and the transaction success rate of the service from 00:00:25 to 00:00:30 are the transaction success rate of 499/10000=0.0499, which obviously has a larger difference from the actual transaction success rate of 0.9998, and may cause erroneous decision. According to the scheme of the application, the data jitter is calculated according to the failure number, and the service transaction amount of 00:00:00-00:00:05 and the transaction failure number of 00:00:25-00:00:30 are actually obtained, so that the calculated transaction success rate is (10000-1)/10000=9999/10000=0.9999, which is smaller than the actual transaction success rate of 0.9998, and the false decision caused by the data jitter can be effectively avoided.

In the embodiment, the system success rate is calculated based on the system failure number instead of the system success number, and the system success rate is calculated based on the communication failure number instead of the communication success number, so that the influence of data jitter on the accuracy of the calculated decision index can be reduced to a certain extent, and the problem of increased data jitter deviation in a second-level environment is effectively solved.

Based on the embodiment, the data can be directly used for calculating the index without aligning the acquired data under the condition that the acquired data meets the preset deviation threshold, and the index is calculated by utilizing the failure number instead of the success number, so that the decision aging under the second level condition is greatly improved, the data dithering under the second level condition is effectively solved, and the balance of errors and aging is realized under the second level environment.

In summary, in one or more embodiments, the decision method of the service private line provided by the application can realize low-delay (for example, within 30 s) data collection, anomaly identification and accurately make a system decision; meanwhile, stable operation of the decision scheme is ensured in all directions by using multiple data sources and multiple index thresholds.

Fig. 2 shows a schematic diagram of a decision flow of a business specific decision method according to an embodiment to more clearly describe the scheme of the present application. As shown in fig. 2, the decision flow of the business private line decision method may include the following four stages: the method comprises a first stage, a configuration acquisition and statistical information acquisition stage of a business special line to be decided; a second stage, namely a data integrity checking stage; a third stage, a business private line abnormality judging stage; and a fourth stage, a business special line decision removing stage.

The first stage includes acquiring critical configuration information and current private line related data. In one aspect, configuration list information of the special service line to be decided may be obtained, where the configuration list information may include a special service line identifier to be decided, a weight of each special line, and may further include area information, address information, and the like of each special line. The weight information may include a traffic split ratio carried by the private line, for example, under a situation that N private lines are total, m1+m2+l2+ &.+ -. Mn+ln represents total traffic information, where Ln represents a split condition of the nth private line, normal use of the private line is 1, and anomaly of the private line is 0; here, mn represents weight information of the nth dedicated line, and m1=m2= … … =mn=1/N in the case where service information is equally distributed among all service main lines, but is not limited thereto. According to an embodiment, all dedicated lines may be traversed periodically at a predetermined period to query the latest configuration list of all dedicated lines, where the latest splitting and weighting information of the dedicated lines are included. The predetermined period may be, for example, every 20s, every 30s, every 60s, and is not particularly limited herein.

On the other hand, in the first stage, on the basis of the aforementioned acquisition of the current configuration information of the private line, for the private line with the shunt information not being 0, second-level statistical information of the service private line to be decided can be acquired, wherein the acquisition of the information can use a dual data source, preferably a real-time data acquisition data source, and a system log data source is selected under the condition that the real-time data acquisition data source fails, wherein when the data loss rate of the real-time data acquisition reaches a certain threshold (for example, about 20%, about 30%, etc., which is calculated according to historical data or is set according to experience), automatic switching of the data source is performed. The acquired service statistics may refer to service statistics of a unit time, for example, service statistics of each second, and more specifically, may include a total transaction amount per second of a dedicated line, a system transaction failure number per second of a dedicated line, and a system communication failure number per second of a dedicated line, but is not limited thereto. Wherein the corresponding statistics period of each traffic statistics may be selected as the last 5s, the last 10s, etc., typically not more than the last 60s.

And in the second stage, the acquired second-level statistical data and the baseline threshold value are subjected to integrity check, and follow-up operation is performed according to the check result. On the one hand, checking the integrity of the acquired special line service statistical information, for example, when at least one of the transaction request number per second, the system failure number per second and the communication failure number per second in the acquired second-level data is missing, considering that the integrity check is not passed, and exiting the decision process abnormally; for example, when the number of acquired transaction requests per second is zero, the integrity check is also considered to be failed, and the decision process is aborted. In addition, whether the time deviation of the acquired special line service statistical information meets a preset deviation threshold value is checked, if not, the check is considered to be failed, and the decision process is stopped abnormally. For example, the predetermined deviation threshold may be a result of a combination of evaluation of the aging and the error rate, and may be, for example, 30s. For example, the expected acquired data is a data index of 00:00:15 to 00:00:20, but the actual acquired data is 00:00:00 to 00:00:05, within a predetermined deviation threshold, i.e., within an acceptable error range, and the verification passes. It should be noted that, in the case where the actually acquired data satisfies the predetermined deviation threshold, the data alignment operation is not required, and the actually acquired traffic statistics information may be directly used to calculate the traffic index information. If it is required to completely align the acquired data, all the statistics involved in the index calculation need to be determined according to the statistics with worst synchronous aging, resulting in an overall decision link time extension. According to the scheme provided by the application, the acquired data in a certain deviation range can be directly used by setting the preset deviation threshold, so that the time effect of decision making is improved on the premise of accuracy.

In another aspect, the second stage verifies the integrity of the acquired baseline threshold. Specifically, historical business statistics of a business specific line for a predetermined period of time within a date selected according to a predetermined rule may be acquired, and then a baseline threshold value of the business specific line corresponding to the predetermined period of time is calculated based on the historical business statistics. Wherein the calculation of the baseline threshold may be calculated using, for example, a 3-sigma algorithm model, but is not limited thereto, and other methods known in the art that may be used to calculate the baseline threshold based on historical data may be used. Wherein the baseline threshold may include a communication success rate baseline threshold, a system success rate baseline threshold, a transaction amount baseline threshold, a system success amount baseline threshold, and the like.

And in the third stage, the selected judging method can be adopted to judge the special business line. Specifically, in the case where the baseline threshold is successfully acquired, then a determination is made using the baseline threshold. If the baseline threshold is not obtained, the determination is performed by using an empirical threshold, for example, the communication success rate threshold may be 0.5, the system success rate threshold may be 0.5, and the transaction amount threshold may be 30.

And in the fourth stage, judging whether the abnormal special line is eliminated or not, and eliminating and/or alarming according to a judging result. Specifically, risk prevention and control are performed according to the configuration conditions of all the special service lines acquired in the first stage, if the proportion of the abnormal special lines to the total number exceeds a preset proportion threshold value, the special line currently judged to be abnormal is not removed, and optionally, an alarm can be performed; if the proportion of the abnormal special lines in the total number does not exceed the preset proportion threshold value, eliminating the special lines which are judged to be abnormal currently. As an example, the predetermined ratio threshold may be 50%, but is not limited thereto. In addition, the special line to be rejected can be added into an automatic rejection queue to wait for automatic rejection, and can also be sent to maintenance personnel for manual rejection.

Fig. 3 shows a schematic diagram of a decision link of a business specific decision method according to an embodiment to more clearly describe the scheme of the present application.

As shown in fig. 3, the real-time decision link is a platform for carrying out business anomaly identification and decision in real time. The real-time decision link may be scheduled periodically to make decisions on the dedicated line of traffic. Specifically, firstly, inquiring configuration information of a special service line, including information such as a current special service line distribution ratio of a mechanism; then inquiring service statistics information and index threshold information of the service private line, wherein the service statistics information can be acquired through a real-time data acquisition data source, alternatively can be acquired through a system log acquisition data source, wherein the index threshold information can be baseline threshold information obtained through an offline calculation link, alternatively, experience threshold information can be used as index threshold information; calculating service index information based on the acquired service statistics information, and then judging whether the private line is abnormal by combining the service index threshold information, wherein system/communication failure information is used instead of system/communication success number information when calculating the service index information so as to reduce the influence of data jitter on a calculation result; and finally, sending the decision result to a decision platform, and deciding whether to perform special line rejection and/or monitor alarm operation or not by the decision platform according to the decision management plan. And managing the service bearing proportion of the private line according to the private line decision result obtained by the real-time decision link. For example, if the decision result is that dedicated line rejection is performed, that is, the decided dedicated line no longer carries the service, the split ratio of each dedicated line can be reconfigured, and the service can be sent to the corresponding dedicated line according to the ratio through, for example, a super gateway. For example, 10 private lines are shared between the third party transaction mechanism and the internet connection/silver connection, under the condition of peer-to-peer distribution, each private line bears 1/10 transaction amount, and if 1 abnormal private line is removed, the transaction amount borne by the rest private lines is 1/9.

As shown in fig. 3, a baseline threshold value for making an abnormality determination is calculated in advance by calculating a link offline. Specifically, the offline baseline threshold calculation model can be invoked periodically, and historical service data of the service private line can be queried; and then, according to the historical business statistics data of the business special line, calculating a corresponding baseline threshold value, and storing the baseline threshold value for use by a real-time decision link. Specifically, a baseline threshold is calculated as a predicted value of traffic statistics in a target period of time in a future date, based on traffic statistics in a target period of time in a history date selected according to a predetermined rule. For example, the information such as the carrying transaction amount, the communication failure amount, the system failure amount and the like in each minute in the period of 00:00:00-06:00 of each day of 1 day, 2 days, 3 days, 7 days, 14 days, 21 days and 30 days before the current date can be counted, and the baseline threshold value of the information such as the carrying transaction amount, the communication failure amount, the system failure amount and the like in the period of 00:00:00-06:00:00:00 can be calculated as the predicted value of the period of 00:00:00:00-06:00:00 today. In this example, the calculated length of the target period is 6 hours, in which case the baseline threshold may be calculated every 6 hours; however, the length of the target period may be arbitrarily set as needed, for example, may be 2 hours, and then the baseline threshold may be calculated every 2 hours, which is shown here as an example. In addition, in order to ensure that the baseline threshold value can accurately reflect the latest business processing state of the business special line, and further ensure the accuracy of the decision based on the baseline threshold value, each time the baseline threshold value is used is a newly calculated baseline threshold value, namely, the baseline threshold value used for carrying out abnormality judgment on business data in a certain time period of tomorrow is different from the baseline threshold value used for carrying out abnormality judgment on business data in the same time period of today, and the former baseline threshold value is the updated baseline threshold value.

Based on the same thought, the embodiment of the specification also provides a device corresponding to the method. Fig. 4 shows a schematic structural diagram of a decision making device of a dedicated service line according to an embodiment.

As shown in fig. 4, the apparatus may include:

an obtaining module 410, configured to obtain, at a predetermined time interval, service statistics information of a service dedicated line in a predetermined time period based on a message center, where the predetermined time interval is smaller than a first duration, the predetermined time period is smaller than a second duration, and the message center is configured to cache the service information of the service dedicated line;

a calculating module 420, configured to calculate service index information according to the service statistics information;

a determining module 430, configured to determine status information of the dedicated service line based on the service indicator information and a preset service indicator threshold;

and the decision module 440 is configured to make a decision on the dedicated line according to the state information of the dedicated line.

According to an embodiment, the obtaining module 410 is further configured to obtain the service statistics information of the dedicated service line based on the log data of the dedicated service line when the obtaining of the service statistics information of the dedicated service line based on the message center fails.

According to an embodiment, the computing module 420 specifically includes: the first verification unit is used for verifying whether the service statistical information accords with service index information calculation conditions before calculating service index information according to the service statistical information to obtain a first verification result; and the first execution unit is used for exiting the decision process if the first check result is negative, and calculating service index information according to the service statistical information if the first check result is positive.

According to an embodiment, the first execution unit is specifically configured to: if the first verification result is yes, calculating the service success rate of the preset time period by adopting the service success-failure statistical information of the first time period and the service total amount statistical information of the second time period, wherein the time deviation between the first time period and the preset time period and the time deviation between the second time period and the preset time period are not more than the third time period.

According to an embodiment, the calculation module 420 is specifically configured to: calculating service success rate information according to the service abnormal quantity statistical information and the service total quantity statistical information by the following formula: service success rate information= (traffic total amount statistical information-traffic abnormal amount statistical information)/traffic total amount statistical information.

According to an embodiment, the determining module 430 includes: a threshold value obtaining unit, configured to obtain a baseline threshold value of the dedicated line of service corresponding to the predetermined time period, where the baseline threshold value calculated in advance according to historical service information of the dedicated line of service is used as a preset index threshold value; the second checking unit is used for checking whether all required baseline thresholds are acquired or not to obtain a second checking result; and the second execution unit is used for judging whether the business index information meets the first judging condition based on the baseline threshold value as an index threshold value if the second checking result is yes, and judging whether the business index information meets the second judging condition based on the experience threshold value as the index threshold value if the second checking result is no.

According to an embodiment, the decision module 440 comprises: a third checking unit, configured to determine whether the dedicated line meets a dedicated line rejection condition when the state information of the dedicated line indicates that the dedicated line is in an abnormal state; and the third execution unit is used for carrying out the rejection operation on the special business line if the special line rejection condition is met.

It will be appreciated that each of the modules described above refers to a computer program or program segment for performing one or more particular functions. Furthermore, the distinction of the above-described modules does not represent that the actual program code must also be separate.

Based on the same thought, the embodiment of the specification also provides equipment corresponding to the method.

Fig. 5 shows a schematic structural diagram of a decision device of a dedicated service line according to an embodiment. As shown in fig. 5, the apparatus 500 may include:

at least one processor 510; the method comprises the steps of,

a memory 530 communicatively coupled to the at least one processor; wherein,,

the memory 530 stores instructions 520 executable by the at least one processor 510, the instructions being executable by the at least one processor 510 to enable the at least one processor 510 to: acquiring service statistics information of a service private line in a preset time period based on a message center at preset time intervals, wherein the preset time intervals are smaller than a first time period, the preset time period is smaller than a second time period, and the message center is used for caching the service information of the service private line; calculating service index information according to the service statistical information; determining state information of the special service line based on the service index information and a preset service index threshold; and making a decision on the special service line according to the state information of the special service line.

Based on the same thought, the embodiment of the specification also provides a computer readable medium corresponding to the method. The computer readable medium has stored thereon computer readable instructions executable by a processor to implement the business specific line decision method described in any of the above embodiments.

The foregoing describes particular embodiments of the present disclosure, and in some cases, acts or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for the apparatus, device embodiments, since they are substantially similar to the method embodiments, the description is relatively simple, as relevant to see the section description of the method embodiments.

The apparatus, the device, and the method provided in the embodiments of the present disclosure correspond to each other, and therefore, the apparatus, the device, and the method also have similar beneficial technical effects as those of the corresponding method, and since the beneficial technical effects of the method have been described in detail above, the beneficial technical effects of the corresponding apparatus, device are not described here again.

In the 90 s of the 20 th century, improvements to one technology could clearly be distinguished as improvements in hardware (e.g., improvements to circuit structures such as diodes, transistors, switches, etc.) or software (improvements to the process flow). However, with the development of technology, many improvements of the current method flows can be regarded as direct improvements of hardware circuit structures. Designers almost always obtain corresponding hardware circuit structures by programming improved method flows into hardware circuits. Therefore, an improvement of a method flow cannot be said to be realized by a hardware entity module. For example, a programmable logic device (Programmable Logic Device, PLD) (e.g., field programmable gate array (Field Programmable Gate Array, FPGA)) is an integrated circuit whose logic function is determined by the programming of the device by a user. A designer programs to "integrate" a digital system onto a PLD without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Moreover, nowadays, instead of manually manufacturing integrated circuit chips, such programming is mostly implemented by using "logic compiler" software, which is similar to the software compiler used in program development and writing, and the original code before the compiling is also written in a specific programming language, which is called hardware description language (Hardware Description Language, HDL), but not just one of the hdds, but a plurality of kinds, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), lava, lola, myHDL, PALASM, RHDL (Ruby Hardware Description Language), etc., VHDL (Very-High-Speed Integrated Circuit Hardware Description Language) and Verilog are currently most commonly used. It will also be apparent to those skilled in the art that a hardware circuit implementing the logic method flow can be readily obtained by merely slightly programming the method flow into an integrated circuit using several of the hardware description languages described above.

The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer readable medium storing computer readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, application specific integrated circuits (Application Specific Integrated Circuit, ASIC), programmable logic controllers, and embedded microcontrollers, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, atmel AT91SAM, microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic of the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller in a pure computer readable program code, it is well possible to implement the same functionality by logically programming the method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers, etc. Such a controller may thus be regarded as a kind of hardware component, and means for performing various functions included therein may also be regarded as structures within the hardware component. Or even means for achieving the various functions may be regarded as either software modules implementing the methods or structures within hardware components.

The system, apparatus, module or unit set forth in the above embodiments may be implemented in particular by a computer chip or entity, or by a product having a certain function. One typical implementation is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

For convenience of description, the above devices are described as being functionally divided into various units, respectively. Of course, the functions of each element may be implemented in the same piece or pieces of software and/or hardware when implementing the present application.

It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.

Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.

The application may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The application may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.

In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for system embodiments, since they are substantially similar to method embodiments, the description is relatively simple, as relevant to see a section of the description of method embodiments.

The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and variations of the present application will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. which come within the spirit and principles of the application are to be included in the scope of the claims of the present application.

Claims

1. A decision method of a service private line comprises the following steps:

acquiring service statistics information of a service private line in a preset time period based on a message center at preset time intervals, wherein the preset time intervals are smaller than a first time period, the preset time period is smaller than a second time period, and the message center is used for caching the service information of the service private line; the first duration is not greater than 60 seconds and the second duration is not greater than 60 seconds;

Calculating service index information according to the service statistical information;

determining state information of the special service line based on the service index information and a preset service index threshold;

making a decision on the special service line according to the state information of the special service line;

when the acquisition of the service statistics information of the service private line based on the message center fails, the service statistics information of the service private line is acquired based on the log data of the service private line.

2. The method of claim 1, further comprising, prior to calculating traffic metric information from the traffic statistics:

checking whether the service statistical information accords with service index information calculation conditions or not to obtain a first check result;

if the first checking result is no, exiting the decision process;

the calculating the service index information according to the service statistics information specifically includes: if the first check result is yes, calculating service index information according to the service statistical information.

3. The method according to claim 2, wherein the checking whether the traffic statistics meet traffic index information calculation conditions specifically comprises:

checking whether all the required service statistical information is acquired; and/or

And checking whether the statistical time period corresponding to the service statistical information meets a preset time range.

4. The method of claim 2, wherein if the first check result is yes, calculating service index information according to the service statistics information, specifically including:

and calculating the service success rate of the preset time period by adopting the service success-failure statistical information of the first time period and the service total amount statistical information of the second time period, wherein the time deviation between the first time period and the preset time period and the time deviation between the second time period and the preset time period are not more than the third time period.

5. The method according to claim 1 or 4, wherein the calculating business index information according to the business statistics specifically comprises:

calculating service success rate information according to the service abnormal quantity statistical information and the service total quantity statistical information by the following formula: service success rate information= (traffic total amount statistical information-traffic abnormal amount statistical information)/traffic total amount statistical information.

6. The method of claim 1, wherein before the acquiring, at predetermined time intervals, traffic statistics of the traffic profile for a predetermined period of time based on the message center, further comprises:

Acquiring historical service statistical information of a service private line in a preset time period within a date selected according to a preset rule;

and calculating a baseline threshold value corresponding to the business special line and the preset time period based on the historical business statistical information.

7. The method according to claim 1, wherein the preset indicator threshold is a baseline threshold pre-calculated according to historical service information of the dedicated service line, and the determining the status information of the dedicated service line based on the service indicator information and the preset service indicator threshold specifically includes:

acquiring a baseline threshold value of the special service line corresponding to the preset time period;

judging whether the business index information meets a first judging condition or not based on the baseline threshold value;

and if the first judging condition is met, determining the state information of the special service line as an abnormal state.

8. The method of claim 7, wherein before the determining whether the traffic indicator information satisfies the first determination condition based on the baseline threshold value, further comprises:

checking whether all required baseline thresholds are acquired or not to obtain a second checking result;

if the second check result is negative, judging whether the service index information meets a second judging condition or not based on an experience threshold value;

If the second judging condition is met, determining the state information of the special service line as an abnormal state;

the step of judging whether the business index information meets the first judging condition based on the baseline threshold value specifically comprises judging whether the business index information meets the first judging condition based on the baseline threshold value if the second checking result is yes.

9. The method according to claim 1, wherein the deciding the dedicated line according to the state information of the dedicated line specifically includes:

if the state information of the special service line indicates that the special service line is in an abnormal state, judging whether the special service line meets a special line rejection condition or not;

and if the special line rejection condition is met, rejecting the service special line.

10. A decision making device for a dedicated service line, comprising:

the acquisition module is used for acquiring the business statistics information of the business special line in a preset time period based on the message center at preset time intervals, wherein the preset time intervals are smaller than the first time period, the preset time period is smaller than the second time period, and the message center is used for caching the business information of the business special line; the first duration is not greater than 60 seconds and the second duration is not greater than 60 seconds;

The calculating module is used for calculating service index information according to the service statistical information;

the judging module is used for determining the state information of the special service line based on the service index information and a preset service index threshold value;

the decision module is used for deciding the special service line according to the state information of the special service line;

the acquisition module is further configured to acquire the service statistics information of the service dedicated line based on log data of the service dedicated line when the acquisition of the service statistics information of the service dedicated line based on the message center fails.

11. The apparatus of claim 10, wherein the computing module specifically comprises:

the first verification unit is used for verifying whether the service statistical information accords with service index information calculation conditions before calculating service index information according to the service statistical information to obtain a first verification result;

and the first execution unit is used for exiting the decision process if the first check result is negative, and calculating service index information according to the service statistical information if the first check result is positive.

12. The apparatus of claim 11, wherein,

the first execution unit is specifically configured to: if the first verification result is yes, calculating the service success rate of the preset time period by adopting the service success-failure statistical information of the first time period and the service total amount statistical information of the second time period, wherein the time deviation between the first time period and the preset time period and the time deviation between the second time period and the preset time period are not more than the third time period.

13. The device according to claim 10 or 12, wherein,

the computing module is specifically configured to: calculating service success rate information according to the service abnormal quantity statistical information and the service total quantity statistical information by the following formula: service success rate information= (traffic total amount statistical information-traffic abnormal amount statistical information)/traffic total amount statistical information.

14. The apparatus of claim 10, wherein the means for determining specifically comprises:

a threshold value obtaining unit, configured to obtain a baseline threshold value of the dedicated line of service corresponding to the predetermined time period, where the baseline threshold value calculated in advance according to historical service information of the dedicated line of service is used as a preset index threshold value;

the second checking unit is used for checking whether all required baseline thresholds are acquired or not to obtain a second checking result;

and the second execution unit is used for judging whether the business index information meets the first judging condition based on the baseline threshold value as an index threshold value if the second checking result is yes, and judging whether the business index information meets the second judging condition based on the experience threshold value as the index threshold value if the second checking result is no.

15. The apparatus of claim 10, wherein the decision module specifically comprises:

a third checking unit, configured to determine whether the dedicated line meets a dedicated line rejection condition when the state information of the dedicated line indicates that the dedicated line is in an abnormal state;

and the third execution unit is used for carrying out the rejection operation on the special business line if the special line rejection condition is met.

16. A decision making device for a dedicated line of business, comprising:

at least one processor; the method comprises the steps of,

a memory communicatively coupled to the at least one processor; wherein,,

17. A computer readable medium having stored thereon computer readable instructions executable by a processor to implement the business specific line decision method of any of claims 1 to 9.