CN113159463A - Traffic monitoring method and device - Google Patents
Traffic monitoring method and device Download PDFInfo
- Publication number
- CN113159463A CN113159463A CN202110579803.7A CN202110579803A CN113159463A CN 113159463 A CN113159463 A CN 113159463A CN 202110579803 A CN202110579803 A CN 202110579803A CN 113159463 A CN113159463 A CN 113159463A
- Authority
- CN
- China
- Prior art keywords
- transaction amount
- transaction
- time period
- traffic monitoring
- expected
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 109
- 238000012544 monitoring process Methods 0.000 title claims abstract description 61
- 238000012806 monitoring device Methods 0.000 claims abstract description 51
- 230000008859 change Effects 0.000 claims abstract description 22
- 238000012545 processing Methods 0.000 claims description 17
- 238000004364 calculation method Methods 0.000 claims description 13
- 238000004590 computer program Methods 0.000 claims description 11
- 238000004891 communication Methods 0.000 claims description 9
- 230000000875 corresponding effect Effects 0.000 description 43
- 238000010276 construction Methods 0.000 description 13
- 230000000694 effects Effects 0.000 description 10
- 230000006870 function Effects 0.000 description 9
- 238000010586 diagram Methods 0.000 description 8
- 238000012423 maintenance Methods 0.000 description 4
- 230000003287 optical effect Effects 0.000 description 4
- 230000008569 process Effects 0.000 description 4
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 238000013461 design Methods 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- 230000002159 abnormal effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000001788 irregular Effects 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 230000000630 rising effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation; Time management
- G06Q10/103—Workflow collaboration or project management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/02—Banking, e.g. interest calculation or account maintenance
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/04—Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Human Resources & Organizations (AREA)
- General Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Accounting & Taxation (AREA)
- Marketing (AREA)
- Physics & Mathematics (AREA)
- Finance (AREA)
- General Physics & Mathematics (AREA)
- Development Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Technology Law (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- Data Mining & Analysis (AREA)
- Game Theory and Decision Science (AREA)
- Data Exchanges In Wide-Area Networks (AREA)
Abstract
The embodiment of the application provides a traffic monitoring method and device, relates to the technical field of computers, and is used for improving the early warning accuracy of a service system. The method comprises the following steps: the method comprises the steps that a business volume monitoring device obtains first transaction data of a business system; the first transaction data is used for indicating the change of the transaction quantity of a first time period, and the first time period is a historical time period; the traffic monitoring device determines an expected transaction amount interval according to the first transaction data and a three-point estimation method; if the business volume monitoring device determines that the target transaction volume is larger than the first transaction volume or smaller than the second transaction volume, early warning information is sent to a business system; the first transaction amount is the upper limit of the expected transaction amount interval, the second transaction amount is the lower limit of the expected transaction amount interval, and the target transaction amount is the real-time transaction amount of the current time period. The method and the device are used for early warning of possible faults of the service system.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a method and an apparatus for monitoring traffic.
Background
With the development of banking business, the amount of business involved is more and more huge. Because the bank uses the business system to process various businesses, the probability of the business system breaking down is also continuously improved under the condition of the sudden increase of the business volume. In order to solve the fault in the service system in time, the service system can be monitored through the service monitoring system so as to send out early warning to the possible fault.
At present, a business monitoring system used by a bank usually adopts a mode of setting a transaction amount threshold value to predict possible faults, and when the transaction amount of the bank is not within the transaction amount threshold value, the business system of the bank possibly fails. Since the transaction amount threshold is a fixed value set empirically by the service person, there is no dynamic adjustment feature. The daily business transaction volume of the bank actually changes according to the trend of the dual-wave-peak curve, and the business transaction volume of the bank continuously changes, for example, the business transaction volume of the bank comprises a peak period and a valley period, and holidays also have great influence on the business transaction volume of the bank. Therefore, when the fixed transaction amount threshold is used for early warning of a service system at present, the problems of inaccurate early warning such as false alarm, missing report and the like can occur.
Disclosure of Invention
The embodiment of the application provides a traffic monitoring method and a traffic monitoring device, which are used for improving the early warning accuracy of a service system.
In order to achieve the above purpose, the embodiment of the present application adopts the following technical solutions:
in a first aspect, a traffic monitoring method is provided, including: the method comprises the steps that a business volume monitoring device obtains first transaction data of a business system; the first transaction data is used for indicating the change of the transaction quantity of a first time period, and the first time period is a historical time period; the traffic monitoring device determines an expected transaction amount interval according to the first transaction data and a three-point estimation method; if the business volume monitoring device determines that the target transaction volume is larger than the first transaction volume or smaller than the second transaction volume, early warning information is sent to a business system; the first transaction amount is the upper limit of the expected transaction amount interval, the second transaction amount is the lower limit of the expected transaction amount interval, and the target transaction amount is the real-time transaction amount of the current time period.
With reference to the first aspect, in some possible implementations, the first transaction data includes a third transaction amount, a fourth transaction amount and a fifth transaction amount, the third transaction amount is used to indicate a maximum value of the transaction amount in the first time period, the fourth transaction amount is used to indicate a minimum value of the transaction amount in the first time period, and the fifth transaction amount is used to indicate an average value of the transaction amounts in the first time period; the traffic monitoring device determining the expected transaction amount interval according to the first transaction data and a three-point estimation method comprises the following steps:
determining a transaction amount expected value according to a three-point estimation method, a third transaction amount, a fourth transaction amount and a fifth transaction amount; determining a standard deviation of the transaction amount according to a three-point estimation method, the third transaction amount and the fourth transaction amount; and determining an expected transaction amount interval according to a three-point estimation method, a transaction amount expected value and a transaction amount standard deviation.
With reference to the first aspect, in some possible implementations, after the traffic monitoring apparatus determines the expected transaction amount interval according to the first transaction data and a three-point estimation method, the method further includes:
and if the target transaction amount is larger than the third transaction amount or smaller than the fourth transaction amount, updating the third transaction amount, the fourth transaction amount and the fifth transaction amount.
With reference to the first aspect, in some possible implementations, before the obtaining, by the traffic monitoring apparatus, the first transaction data of the business system, the method further includes:
setting initial data by a traffic monitoring device; the initial data includes an initial third transaction amount, an initial fourth transaction amount, and an initial fifth transaction amount.
In a second aspect, a traffic monitoring apparatus is provided, which includes: the acquisition module is used for acquiring first transaction data of the business system; the first transaction data is used for indicating the change of the transaction quantity of a first time period, and the first time period is a historical time period; the processing module is used for determining an expected transaction amount interval according to the first transaction data acquired by the acquisition module and a three-point estimation method; the early warning module is used for sending early warning information to the service system when the processing module determines that the target transaction amount is larger than the first transaction amount or smaller than the second transaction amount; the first transaction amount is the upper limit of the expected transaction amount interval, the second transaction amount is the lower limit of the expected transaction amount interval, and the target transaction amount is the real-time transaction amount of the current time period.
With reference to the second aspect, in some possible implementations, the first transaction data includes a third transaction amount, a fourth transaction amount and a fifth transaction amount, the third transaction amount is used for indicating a maximum value of the transaction amount in the first time period, the fourth transaction amount is used for indicating a minimum value of the transaction amount in the first time period, and the fifth transaction amount is used for indicating an average value of the transaction amounts in the first time period; the processing module comprises a first calculation submodule, a second calculation submodule and a third calculation submodule.
And the first calculation submodule is used for determining the expected value of the transaction amount according to the three-point estimation method, the third transaction amount, the fourth transaction amount and the fifth transaction amount.
And the second calculation submodule is used for determining the standard deviation of the transaction amount according to the three-point estimation method, the third transaction amount and the fourth transaction amount.
And the third calculation submodule is used for determining an expected transaction amount interval according to a three-point estimation method, a transaction amount expected value and a transaction amount standard deviation.
With reference to the second aspect, in some possible implementations, the traffic monitoring apparatus further includes an update module.
And the updating module is used for updating the third transaction amount, the fourth transaction amount and the fifth transaction amount when the target transaction amount is larger than the third transaction amount or smaller than the fourth transaction amount.
With reference to the second aspect, in some possible implementations, the traffic monitoring apparatus further includes an assignment module.
The assignment module is used for setting initial data; the initial data includes an initial third transaction amount, an initial fourth transaction amount, and an initial fifth transaction amount.
In a third aspect, a traffic monitoring apparatus is provided, including: a memory, a processor, a bus, and a communication interface; the memory is used for storing computer execution instructions, and the processor is connected with the memory through a bus; when the traffic monitoring apparatus is operating, the processor executes computer-executable instructions stored in the memory to cause the traffic monitoring apparatus to perform the traffic monitoring method as provided by the first aspect.
In a fourth aspect, a computer program product is provided, the computer program product comprising computer instructions which, when run on a traffic monitoring apparatus, cause the traffic monitoring apparatus to perform the traffic monitoring method as provided in the first aspect.
The embodiment of the application provides a method and a device for monitoring the traffic, wherein the method comprises the following steps: the method comprises the steps that a business volume monitoring device obtains first transaction data of a business system; the first transaction data is used for indicating the change of the transaction quantity of a first time period, and the first time period is a historical time period; the traffic monitoring device determines an expected transaction amount interval according to the first transaction data and a three-point estimation method; if the business volume monitoring device determines that the target transaction volume is larger than the first transaction volume or smaller than the second transaction volume, early warning information is sent to a business system; the first transaction amount is the upper limit of the expected transaction amount interval, the second transaction amount is the lower limit of the expected transaction amount interval, and the target transaction amount is the real-time transaction amount of the current time period. In the embodiment of the application, the traffic monitoring device can determine the expected transaction volume interval according to a three-point estimation method and the historical traffic volume change condition of the service system; since the three-point estimation method is a common method for determining a construction period in project management, in the application, the maximum traffic of a service system in a historical time period is used as the optimistic traffic, the minimum traffic is used as the pessimistic traffic, the average value of the traffics is used as the most probable traffic, and further, a transaction expected value and a transaction standard deviation can be determined according to the three-point estimation method; in the three-point estimation method, the business transaction volume interval of the business system can be determined according to the construction period required by completing the activity in a certain probability interval; in the embodiment of the application, the business transaction volume interval of the business system is determined according to the historical business volume change condition, so that different business transaction volume intervals can be determined according to the business volume prediction of different time periods, and the early warning accuracy of the business system is improved.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flow chart of a traffic monitoring method according to an embodiment of the present application;
fig. 2 is a schematic diagram illustrating a transaction amount variation of a service system according to an embodiment of the present disclosure;
fig. 3 is a second schematic flow chart of a traffic monitoring method according to an embodiment of the present application;
fig. 4 is a probability normal distribution diagram corresponding to a desired value and a standard deviation in a three-point estimation method provided in the embodiment of the present application;
fig. 5 is a third schematic flow chart of a traffic monitoring method according to an embodiment of the present application;
fig. 6 is a fourth schematic flowchart of a traffic monitoring method according to an embodiment of the present application;
fig. 7 is a schematic structural diagram of a traffic monitoring apparatus according to an embodiment of the present application;
fig. 8 is a second schematic structural diagram of a traffic monitoring apparatus according to an embodiment of the present application;
fig. 9 is a third schematic structural diagram of a traffic monitoring apparatus according to an embodiment of the present application;
fig. 10 is a fourth schematic structural diagram of a traffic monitoring apparatus according to an embodiment of the present application;
fig. 11 is a schematic structural diagram of another traffic monitoring apparatus according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described herein as "exemplary" or "e.g.," is not necessarily to be construed as preferred or advantageous over other embodiments or designs. Rather, use of the word "exemplary" or "such as" is intended to present concepts related in a concrete fashion.
For the convenience of clearly describing the technical solutions of the embodiments of the present application, in the embodiments of the present application, the terms "first", "second", and the like are used for distinguishing the same items or similar items with basically the same functions and actions, and those skilled in the art can understand that the terms "first", "second", and the like are not limited in number or execution order.
To facilitate an understanding of the present application, the relevant elements referred to in the present application are described below.
Three-point estimation method
The three-point estimation method is a method for calculating a construction period in the field of project management, and particularly when the construction period is calculated, the three-point estimation method is provided with the most pessimistic time, the most optimistic time and the most probable time, the corresponding activity duration mean value and the corresponding activity duration standard deviation can be determined according to the three times, and then the probability of completion within a certain construction period or the construction period required for completing the activity within a certain probability interval can be determined according to the normal distribution probability characteristic and the activity duration mean value and the activity duration standard deviation. The optimistic time is a time limit for a smooth job, the pessimistic time is a time limit for a smooth job, and the most probable time is a time limit for completing a certain process.
At present, a business system of a bank usually performs early warning on a possible fault according to a transaction amount threshold, and because the transaction amount threshold is fixed and unchanged and the business amount change condition of the bank at different periods is irregular, when the early warning is performed on the possible fault by depending on the fixed transaction amount threshold, missed report, false report and the like may occur.
In view of the above problems, embodiments of the present application provide a traffic monitoring method, which is used to improve accuracy of early warning of a fault of a service system. As shown in fig. 1, the method includes:
s101, a business volume monitoring device acquires first transaction data of a business system.
The first transaction data is used for indicating the change of the transaction quantity of a first time period, and the first time period is a historical time period.
Specifically, the first transaction data herein includes a third transaction amount indicating a maximum value of the transaction amount for the first time period, a fourth transaction amount indicating a minimum value of the transaction amount for the first time period, and a fifth transaction amount indicating an average value of the transaction amount for the first time period.
In specific implementation, the traffic monitoring device may obtain, as needed, business transaction data corresponding to the banking system in different historical time periods, for example, obtain first transaction data in a first time period. Of course, in this embodiment of the application, the traffic monitoring device may obtain the service transaction data according to a preset data obtaining period, for example, the data obtaining period may be one week, one month, and the like, and the traffic monitoring device may obtain the service transaction data of the service system in one week or one month. It should be noted that the service transaction data herein includes information such as service types, client elements of each type of service transaction, service transaction duration, risk levels, and the like, so as to predict transaction amounts of different types of services, and further determine a specific node where a service system may fail. Furthermore, in one day, the business transaction amount of the banking system is gradually increased from the early morning until the peak value is reached in the middle of the day, and after the middle of the day, the business transaction amount of the banking system gradually falls back and rises again in the afternoon working hours, and the process is repeated; similarly, the business transaction amount of the banking business system in each week is continuously changed between rising and falling at different time points, and finally the business transaction amount of the banking business system shows the change trend of a double-peak curve.
The traffic monitoring device can monitor the change of the traffic of the service system, such as the traffic of the first time, the traffic of the second time, and the like, and further can determine the traffic of the corresponding time period according to the traffic of each time. For example, the traffic volume of the service system at the first time is a, the traffic volume at the second time is B, the traffic volume at the third time is C, and the first time period is composed of the first time, the second time, and the third time, then the traffic volume at the first time period is a + B + C. Further, when the first time period includes more traffic volumes, the maximum value of the traffic volumes is the maximum value of the traffic volumes of the first time period, the minimum value of the traffic volumes is the minimum value of the traffic volumes of the first time period, and the average value of the traffic volumes is used as the average value of the traffic volumes of the first time period, that is, the third traffic volume, the fourth traffic volume and the fifth traffic volume in the second time period are determined. For example, if a < B < C, the third transaction amount in the first time period is C, the fourth transaction amount is a, and the fifth transaction amount is (a + B + C)/3.
Exemplarily, as shown in fig. 2, a traffic volume change condition of the traffic system in a first time period is provided, and a maximum value of the traffic volume in the first time period is V1The minimum value of the transaction amount is V2。
The first time period may be one week, if the traffic monitoring device acquires the traffic transaction data with a data acquisition period of days, and the total amount of the traffic in the first time period is V3If the third transaction amount corresponding to the first time period is V1The fourth transaction amount is V2The fifth transaction amount is V3/7。
S102, the traffic monitoring device determines an expected transaction amount interval according to the first transaction data and a three-point estimation method.
Specifically, as shown in the following formulas (1) and (2), the three-point estimation method includes:
E＝(P+4M+O)/6 (1)；
δ＝(P-O)/6 (2)。
since the three-point estimation method is a method for calculating a construction period in project management in which P means the most pessimistic time, O means the most optimistic time, and M means the most probable time, P > O here. When the three-point estimation method is applied to the transaction amount prediction of the present application, since the first transaction data includes the third transaction amount, the fourth transaction amount, and the fifth transaction amount, the third transaction amount is used to indicate the maximum value of the transaction amount in the first time period, the fourth transaction amount is used to indicate the minimum value of the transaction amount in the first time period, and the fifth transaction amount is used to indicate the average value of the transaction amounts in the first time period, the third transaction amount is larger than the fourth transaction amount. Therefore, in the embodiment of the present application, P in the above formulas (1) and (2) is the third transaction amount, O is the fourth transaction amount, and M is the fifth transaction amount. Further, E is the expected value of the transaction amount, and δ is the standard deviation of the transaction amount.
Further, according to the three-point estimation method, as shown in fig. 3, step S102 may include:
and S1021, determining a transaction amount expected value according to a three-point estimation method, a third transaction amount, a fourth transaction amount and a fifth transaction amount.
Specifically, the expected transaction amount value can be determined according to the above formula (1). For example, if the third transaction amount is 10000, the fourth transaction amount is 2000, and the fifth transaction amount is 4000, i.e., P is 10000, O is 2000, and M is 4000, then the transaction amount expected value is:
in some embodiments, since the transaction data acquired by the traffic monitoring device may include information such as a service type, the traffic monitoring device may further determine transaction amounts corresponding to different types of services, where expected transaction amounts corresponding to different types of services may be determined.
For example, if the transaction data acquired by the traffic monitoring device includes second transaction data corresponding to the first type of service, third transaction data corresponding to the second type of service, and fourth transaction data corresponding to the third type of service, the same is true for the first transaction data, where the second transaction data includes a third transaction amount 1 (P)1) Fourth transaction amount 1 (O)1) And a fifth transaction amount 1 (M)1) The third transaction data includes a third transaction amount 2 (P)2) Fourth transaction amount 2 (O)2) And a fifth transaction amount 2 (M)2) The fourth transaction data includes a third transaction amount 3 (P)3) Fourth transaction amount 3 (O)3) And a fifth transaction amount 3 (M)3)。
Here, the expected transaction amount value corresponding to each type of service may be determined according to the above formula (1), for example, the expected first transaction amount value corresponding to the first type of service is:
E1＝(P1+4M1+O1)/6。
the expected value of the second transaction amount corresponding to the second type of service is as follows:
E2＝(P2+4M2+O2)/6。
the expected value of the third transaction amount corresponding to the second type of service is as follows:
E3＝(P3+4M3+O3)/6。
here E1I.e. a first transaction amount expected value, E2I.e. the second transaction amount expected value, E3I.e. the third transaction amount expected value.
And S1022, determining a transaction amount standard deviation according to a three-point estimation method, the third transaction amount and the fourth transaction amount.
Specifically, the transaction amount standard deviation can be determined according to the above formula (2). For example, if the third transaction amount is 10000 and the fourth transaction amount is 2000, i.e. P is 10000 and O is 2000, the standard deviation of the transaction amounts is:
in some embodiments, as in step S1021, the traffic monitoring apparatus may determine the transaction amount corresponding to different types of services, where the standard deviation of the transaction amount corresponding to different types of services may be determined.
For example, if the transaction data acquired by the traffic monitoring device includes second transaction data corresponding to the first type of service, third transaction data corresponding to the second type of service, and fourth transaction data corresponding to the third type of service, the same is true for the first transaction data, where the second transaction data includes a third transaction amount 1 (P)1) And a fourth transaction amount 1 (O)1) The third transaction data includes a third transaction amount 2 (P)2) And a fourth transaction amount 2 (O)2) The fourth transaction data includes a third transaction amount 3 (P)3) And a fourth transaction amount 3 (O)3)。
Here, the standard deviation of the transaction amount corresponding to each type of service may be determined according to the above formula (2), for example, the standard deviation of the first transaction amount corresponding to the first type of service is:
δ1＝(P1-O1)/6。
the standard deviation of the second transaction amount corresponding to the second type of service is as follows:
δ2＝(P2-O2)/6。
the standard deviation of the third transaction amount corresponding to the third type of service is as follows:
δ3＝(P3-O3)/6。
delta here1Is the first transaction amount standard deviation, delta2I.e. the second transaction amount standard deviation, delta3I.e. the third transaction amount standard deviation.
And S1023, determining an expected transaction amount interval according to a three-point estimation method, a transaction amount expected value and a transaction amount standard deviation.
Specifically, since the three-point estimation method is a method for calculating a construction period in project management, as shown in fig. 4, a probability normal distribution diagram corresponding to a desired value and a standard deviation in the three-point estimation method is shown, where μ is used to indicate an average construction period calculated by the three-point estimation method, i.e., E described above; and σ is the number of days of deviation, i.e., δ. Referring to fig. 4, the probability within 1 σ is 68.2%, the probability within 2 σ is 95.4%, and the probability within 3 σ is 99.7%. In the project management, the probability of completing the activity in μ day is 50%, the probability of completing the activity in μ + σ day is 50% + 34.1%, and the probability of completing the activity in μ +2 σ day is 50% + 34.1% + 13.6%. In project management, the probability that the campaign duration falls within the standard deviation range corresponding to fig. 4 is shown in table 1 below:
TABLE 1
| Standard deviation of | Probability of activity period falling within standard deviation range |
| -1δ～1δ | 68.26％ |
| -2δ～2δ | 95.44％ |
| -3δ～3δ | 99.72％ |
| -6δ～6δ | 99.99％ |
In the embodiment of the present application, when the transaction amount of the service system is estimated according to the three-point estimation method, the probability distribution corresponding to the expected value of the transaction amount and the standard deviation of the transaction amount is as shown in table 2 below:
TABLE 2
| Standard deviation of | Probability of transaction amount falling within standard deviation |
| -1δ～1δ | 68.26％ |
| -2δ～2δ | 95.44％ |
| -3δ～3δ | 99.72％ |
| -6δ～6δ | 99.99％ |
Further, in the embodiment of the present application, the expected transaction amount interval is determined according to the maximum expected transaction amount and the minimum expected transaction amount within the 99% probability range. Referring to table 2 above, the maximum expected transaction amount and the minimum expected transaction amount, i.e., the first transaction amount and the second transaction amount, may be determined according to the expected transaction amount value and the standard deviation of the transaction amount determined in steps S1021 and S1022. Specifically, the following equations (3) and (4) are given.
X＝E+3δ (3)；
Y＝E-3δ (4)。
Where X is the first transaction amount and Y is the second transaction amount.
For example, if the expected transaction amount E is 4666.67 and δ is 1333.33, then:
X＝E+3δ＝4666.67+3*1333.33＝8666.66。
Y＝E-3δ＝4666.67-3*1333.33＝666.68。
i.e. the expected transaction amount interval is [8666.66, 666.68 ].
In some embodiments, as in the above steps S1021 and S1022, when the traffic monitoring apparatus obtains the transaction data corresponding to multiple types of services, it may further determine expected transaction amount intervals corresponding to the respective types of services according to the above method.
For example, if the transaction data acquired by the traffic monitoring device includes second transaction data corresponding to the first type of traffic, third transaction data corresponding to the second type of traffic, and fourth transaction data corresponding to the third type of traffic, the expected transaction amount intervals corresponding to the respective types of traffic may be determined according to the above method for determining the expected transaction amount intervals, for example, the first expected transaction amount interval corresponding to the first type of traffic may be determined according to the following formula:
X1＝E1+3δ1；
Y1＝E1+3δ1。
the first expected transaction amount interval is X1，Y1]。
The second expected transaction amount interval corresponding to the second type of traffic may be determined according to the following formula:
X2＝E2+3δ2；
Y2＝E2+3δ2。
the second expected transaction amount interval is X2，Y2]。
The third expected transaction amount interval corresponding to the third type of traffic may be determined according to the following formula:
X3＝E3+3δ3；
Y3＝E3+3δ3。
the second expected transaction amount interval is X3，Y3]。
S103, if the business volume monitoring device determines that the target business volume is larger than the first business volume or smaller than the second business volume, early warning information is sent to a business system.
The first transaction amount is the upper limit of the expected transaction amount interval, the second transaction amount is the lower limit of the expected transaction amount interval, and the target transaction amount is the real-time transaction amount of the current time period.
Specifically, step S1023 determines an expected transaction amount interval of the service system, that is, a transaction amount that the transaction amount of the service system may reach. In this step, when the target transaction amount determined by the traffic monitoring device is greater than the first transaction amount or less than the second transaction amount, it may be determined that the target transaction amount of the traffic system in the target time period is abnormal, and the traffic system may fail. At this time, the traffic monitoring device may send early warning information to the service system to indicate a fault of the service system and remind operation and maintenance personnel to maintain in time.
In some embodiments, since the traffic monitoring device can monitor the transaction amount of different types of traffic, a specific fault module in the traffic system can be further determined.
For example, a business system includes a first business module, a second business module, and a third business module. The first service module is used for processing services of a first type of service, the second service module is used for processing services of a second type of service, and the third service module is used for processing services of a third type of service.
If the first target transaction amount is not in the first expected transaction amount interval, determining that the first service module fails; if the second target transaction amount is in the second expected transaction amount interval, the second service module can be determined to be normal; if the third target transaction amount is not within the third expected transaction amount interval, it may be determined that the third service module is faulty.
In some embodiments, if the traffic monitoring device determines that the service system is faulty, the traffic monitoring device may further determine a target traffic and an expected transaction interval corresponding to each type of service in the service system, and further compare the target traffic and the expected transaction interval corresponding to the different types of services to determine a specific faulty module in the service system. For example, when it is determined that the service system has a fault, if the service system includes the first service module, the second service module, and the third service module, and it is determined that the first service module is normal, the second service module is normal, and the third service module has a fault according to the above method, the operation and maintenance personnel may perform maintenance on the third service module to reduce the workload of the operation and maintenance personnel.
It should be noted that, in this embodiment, the data acquisition cycle of the traffic monitoring device for acquiring the transaction data may be set by a person skilled in the art as needed, and of course, the first time period and the target time period correspond to each other, that is, the time length of the first time period is the same as the time length of the target time period.
In practice, in this embodiment, between steps S102 and S103, the following is further included: the traffic monitoring apparatus acquires the target transaction amount so that the traffic monitoring apparatus acquires the target transaction amount performs step S103.
In the embodiment of the application, the expected transaction amount interval corresponding to the service system can be determined according to a three-point estimation method, and the expected transaction amount interval is determined according to the historical service transaction condition of the service system, so that the expected transaction amount interval can be changed in real time, and the missing report, the false report and the like caused by a fixed transaction amount threshold value in the prior art are avoided.
In some embodiments, as shown in fig. 5, after step S1023, the method further includes:
s201, if the target transaction amount is larger than the third transaction amount or smaller than the fourth transaction amount, updating the third transaction amount or the fourth transaction amount.
Specifically, since the expected transaction amount value and the standard deviation of the transaction amount are both related to the third transaction amount and the fourth transaction amount, the third transaction amount is the maximum transaction amount in the first time period, and the fourth transaction amount is the minimum transaction amount in the first time period. Therefore, when the target transaction amount is greater than the third transaction amount, the target transaction amount may be taken as the maximum value of the transaction amount of the history time period; alternatively, when the target transaction amount is less than the fourth transaction amount, the target transaction amount may be taken as the transaction amount minimum value of the history time period. Of course, the historical time period may refer to the above-mentioned target time period, or the first time period; of course, the historical time period may include both the first time period and the target time period corresponding to the target transaction amount according to the requirement, and the traffic monitoring device may determine a new expected transaction amount interval according to the updated third transaction amount or the updated fourth transaction amount.
For example, if the target transaction amount is greater than the third transaction amount, the expected transaction amount value is:
E＝(Q+4M+O)/6。
the standard deviation of the transaction amount is:
δ＝(Q-O)/6。
wherein Q is the target transaction amount.
For another example, when the target transaction amount is less than the fourth transaction amount, the expected transaction amount value is:
E＝(P+4M+Q)/6。
the standard deviation of the transaction amount is:
δ＝(P-Q)/6。
after the corresponding expected transaction amount value and standard deviation of the transaction amount are determined according to the updated third transaction amount or fourth transaction amount, a new expected transaction amount interval can be determined according to the updated expected transaction amount value and standard deviation of the transaction amount, and then early warning is carried out on the service system according to the new expected transaction amount interval. For example, the transaction amount of the third time period is compared with the new expected transaction amount interval, and whether to send the early warning information to the service system is judged according to the comparison result. The third time period is a later time period of the target time period. For another example, when the target transaction amount is greater than the third transaction amount or less than the fourth transaction amount, the expected transaction amount interval may be updated, and then whether the target transaction amount in the target time period is normal is determined, so as to determine whether to send the warning information to the service system.
It should be noted that, since the transaction volume of the banking system has a certain hyperbolic curve trend, the transaction volume change range generally changes between the third transaction volume and the fourth transaction volume. Therefore, here, when the target transaction amount is greater than the third transaction amount or less than the fourth transaction amount, the third transaction amount or the fourth transaction amount may be updated.
In some embodiments, in this step, M in the above formula (1) may be updated according to the target transaction amount, that is, when the target transaction amount is greater than the third transaction amount or less than the fourth transaction amount, not only the third transaction amount or the fourth transaction amount but also the fifth transaction amount may be updated. Of course, when the target transaction amount is between the third transaction amount and the fourth transaction amount, only the fifth transaction amount may be updated, so as to determine a new expected transaction amount interval according to the above formulas (1), (2), (3) and (4), and further perform early warning on the transaction amount change condition of the subsequent service system.
In some embodiments, as shown in fig. 6, before step S1021, the method further includes:
s100, the traffic monitoring device sets initial data.
Wherein the initial data includes an initial third transaction amount, an initial fourth transaction amount, and an initial fifth transaction amount.
Specifically, since the service system does not perform service processing in the initial state, the traffic monitoring device cannot acquire corresponding transaction data from the service system, and cannot acquire the third transaction amount, the fourth transaction amount, and the fifth transaction amount for determining the expected value and the standard deviation of the transaction amount. Therefore, the initial data is set through the step, so as to set the initial third transaction amount, the initial fourth transaction amount and the initial fifth transaction amount, and further, the traffic monitoring device can perform early warning on the service system in the initial state of the service system according to the expected value of the initial transaction amount and the standard deviation of the initial transaction amount.
The method for monitoring the traffic provided by the embodiment of the application comprises the following steps: the method comprises the steps that a business volume monitoring device obtains first transaction data of a business system; the first transaction data is used for indicating the change of the transaction quantity of a first time period, and the first time period is a historical time period; the traffic monitoring device determines an expected transaction amount interval according to the first transaction data and a three-point estimation method; if the business volume monitoring device determines that the target transaction volume is larger than the first transaction volume or smaller than the second transaction volume, early warning information is sent to a business system; the first transaction amount is the upper limit of the expected transaction amount interval, the second transaction amount is the lower limit of the expected transaction amount interval, and the target transaction amount is the real-time transaction amount of the current time period. In the embodiment of the application, the traffic monitoring device can determine the expected transaction volume interval according to a three-point estimation method and the historical traffic volume change condition of the service system; since the three-point estimation method is a common method for determining a construction period in project management, in the application, the maximum traffic of a service system in a historical time period is used as the optimistic traffic, the minimum traffic is used as the pessimistic traffic, the average value of the traffics is used as the most probable traffic, and further, a transaction expected value and a transaction standard deviation can be determined according to the three-point estimation method; in the three-point estimation method, the business transaction volume interval of the business system can be determined according to the construction period required by completing the activity in a certain probability interval; in the embodiment of the application, the business transaction volume interval of the business system is determined according to the historical business volume change condition, so that different business transaction volume intervals can be determined according to the business volume prediction of different time periods, and the early warning accuracy of the business system is improved.
As shown in fig. 7, an embodiment of the present application provides a traffic monitoring apparatus 30, including:
an obtaining module 301, configured to obtain first transaction data of a service system; the first transaction data is used for indicating the change of the transaction amount of a first time period, and the first time period is a historical time period.
And the processing module 302 is configured to determine an expected transaction amount interval according to the first transaction data acquired by the acquisition module 301 and a three-point estimation method.
The early warning module 303 is configured to send early warning information to the service system when the processing module 302 determines that the target transaction amount is greater than the first transaction amount or less than the second transaction amount; the first transaction amount is the upper limit of the expected transaction amount interval, the second transaction amount is the lower limit of the expected transaction amount interval, and the target transaction amount is the real-time transaction amount of the current time period.
Optionally, the first transaction data includes a third transaction amount, a fourth transaction amount and a fifth transaction amount, the third transaction amount is used for indicating a maximum value of the transaction amount in the first time period, the fourth transaction amount is used for indicating a minimum value of the transaction amount in the first time period, and the fifth transaction amount is used for indicating an average value of the transaction amount in the first time period. As shown in fig. 8, the processing module 302 includes a first computation submodule 3021, a second computation submodule 3022, and a third computation submodule 3033.
A first calculation submodule 3021, configured to determine the expected transaction amount value according to a three-point estimation method, the third transaction amount, the fourth transaction amount, and the fifth transaction amount.
A second calculation submodule 3022, configured to determine a transaction amount standard deviation according to the three-point estimation method, the third transaction amount, and the fourth transaction amount.
A third calculating submodule 3033, configured to determine the expected trading volume interval according to the three-point estimation method, the expected trading volume value determined by the first calculating submodule 3021, and the standard deviation of the trading volume determined by the second calculating submodule 3022.
Optionally, as shown in fig. 9, the traffic monitoring apparatus 30 further includes an updating module 304.
And the updating module 304 is configured to update the third transaction amount or the fourth transaction amount when the target transaction amount is greater than the third transaction amount or less than the fourth transaction amount.
Optionally, as shown in fig. 10, the traffic monitoring apparatus 30 further includes an assigning module 305.
An assignment module 305 for setting initial data; the initial data includes an initial third transaction amount, an initial fourth transaction amount, and an initial fifth transaction amount.
The traffic monitoring device provided by the embodiment of the application comprises: the acquisition module is used for acquiring first transaction data of the business system; the first transaction data is used for indicating the change of the transaction quantity of a first time period, and the first time period is a historical time period; the processing module is used for determining an expected transaction amount interval according to the first transaction data acquired by the acquisition module and a three-point estimation method; the early warning module is used for sending early warning information to the service system when the processing module determines that the target transaction amount is larger than the first transaction amount or smaller than the second transaction amount; the first transaction amount is the upper limit of the expected transaction amount interval, the second transaction amount is the lower limit of the expected transaction amount interval, and the target transaction amount is the real-time transaction amount of the current time period. In the embodiment of the application, the traffic monitoring device can determine the expected transaction volume interval according to a three-point estimation method and the historical traffic volume change condition of the service system; since the three-point estimation method is a common method for determining a construction period in project management, in the application, the maximum traffic of a service system in a historical time period is used as the optimistic traffic, the minimum traffic is used as the pessimistic traffic, the average value of the traffics is used as the most probable traffic, and further, a transaction expected value and a transaction standard deviation can be determined according to the three-point estimation method; in the three-point estimation method, the business transaction volume interval of the business system can be determined according to the construction period required by completing the activity in a certain probability interval; in the embodiment of the application, the business transaction volume interval of the business system is determined according to the historical business volume change condition, so that different business transaction volume intervals can be determined according to the business volume prediction of different time periods, and the early warning accuracy of the business system is improved.
As shown in fig. 11, the embodiment of the present application further provides another traffic monitoring apparatus, which includes a memory 41, a processor 42, a bus 43, and a communication interface 44; the memory 41 is used for storing computer execution instructions, and the processor 42 is connected with the memory 41 through a bus 43; when the traffic monitoring apparatus is operating, the processor 42 executes computer-executable instructions stored in the memory 41 to cause the traffic monitoring apparatus to perform the traffic monitoring method provided in the above-described embodiments.
In particular implementations, processor 42(42-1 and 42-2) may include one or more CPUs, such as CPU0 and CPU1 shown in FIG. 11, for example, as one embodiment. And as an example, the traffic monitoring device may include a plurality of processors 42, such as processor 42-1 and processor 42-2 shown in fig. 11. Each of the processors 42 may be a single-Core Processor (CPU) or a multi-Core Processor (CPU). Processor 42 may refer herein to one or more devices, circuits, and/or processing cores that process data (e.g., computer program instructions).
The memory 41 may be, but is not limited to, a read-only memory 41 (ROM) or other type of static storage device that can store static information and instructions, a Random Access Memory (RAM) or other type of dynamic storage device that can store information and instructions, an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compact disc, laser disc, optical disc, digital versatile disc, blu-ray disc, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. The memory 41 may be self-contained and coupled to the processor 42 via a bus 43. The memory 41 may also be integrated with the processor 42.
In a specific implementation, the memory 41 is used for storing data in the present application and computer-executable instructions corresponding to software programs for executing the present application. The processor 42 may monitor various functions of the device by running or executing software programs stored in the memory 41, as well as invoking data stored in the memory 41.
The communication interface 44 is any device, such as a transceiver, for communicating with other devices or communication networks, such as a control system, a Radio Access Network (RAN), a Wireless Local Area Network (WLAN), and the like. The communication interface 44 may include a receiving unit implementing a receiving function and a transmitting unit implementing a transmitting function.
The bus 43 may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an extended ISA (enhanced industry standard architecture) bus, or the like. The bus 43 may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 11, but this is not intended to represent only one bus or type of bus.
An embodiment of the present application further provides a computer program product, where the computer program product includes computer instructions, and when the computer instructions are run on a traffic monitoring apparatus, the traffic monitoring apparatus is caused to execute the traffic monitoring method provided in the foregoing embodiment.
The embodiment of the present application further provides a computer program, where the computer program may be directly loaded into the memory and contains a software code, and the computer program is loaded and executed by a computer, so as to implement the traffic monitoring method provided by the foregoing embodiment.
Those skilled in the art will recognize that in one or more of the examples described above, the functions described herein may be implemented in hardware, software, firmware, or any combination thereof. When implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a general purpose or special purpose computer.
Through the above description of the embodiments, it is clear to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional modules is merely used as an example, and in practical applications, the above function distribution may be completed by different functional modules according to needs, that is, the internal structure of the device may be divided into different functional modules to complete all or part of the above described functions.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules or units is only one logical function division, and there may be other division ways in actual implementation. For example, various elements or components may be combined or may be integrated into another device, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form. Units described as separate parts may or may not be physically separate, and parts displayed as units may be one physical unit or a plurality of physical units, may be located in one place, or may be distributed to a plurality of different places. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit. The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a readable storage medium. Based on such understanding, the technical solutions of the embodiments of the present application may be essentially or partially contributed to by the prior art, or all or part of the technical solutions may be embodied in the form of a software product, where the software product is stored in a storage medium and includes several instructions to enable a device (which may be a single chip, a chip, or the like) or a processor (processor) to execute all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a U disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present application should be covered within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. A traffic monitoring method, comprising:
the method comprises the steps that a business volume monitoring device obtains first transaction data of a business system; the first transaction data is used for indicating the change of the transaction quantity of a first time period, and the first time period is a historical time period;
the traffic monitoring device determines an expected transaction amount interval according to the first transaction data and a three-point estimation method;
if the business volume monitoring device determines that the target transaction volume is larger than the first transaction volume or smaller than the second transaction volume, early warning information is sent to the business system; the first transaction amount is the upper limit of the expected transaction amount interval, the second transaction amount is the lower limit of the expected transaction amount interval, and the target transaction amount is the real-time transaction amount of the current time period.
2. The traffic monitoring method according to claim 1, wherein the first transaction data includes a third transaction amount, a fourth transaction amount and a fifth transaction amount, the third transaction amount is used for indicating a maximum value of the transaction amount of the first time period, the fourth transaction amount is used for indicating a minimum value of the transaction amount of the first time period, and the fifth transaction amount is used for indicating an average value of the transaction amount of the first time period; the step of determining an expected transaction amount interval by the traffic monitoring device according to the first transaction data and a three-point estimation method comprises the following steps:
determining a transaction amount expected value according to the three-point estimation method, the third transaction amount, the fourth transaction amount and the fifth transaction amount;
determining a transaction amount standard deviation according to the three-point estimation method, the third transaction amount and the fourth transaction amount;
and determining the expected transaction amount interval according to the three-point estimation method, the expected transaction amount value and the standard deviation of the transaction amount.
3. The traffic monitoring method according to claim 2, further comprising, after the traffic monitoring apparatus determines an expected traffic interval based on the first transaction data and a three-point estimation method:
and if the target transaction amount is larger than the third transaction amount or smaller than the fourth transaction amount, updating the third transaction amount or the fourth transaction amount.
4. The traffic monitoring method according to claim 3, further comprising, before the traffic monitoring device obtains the first transaction data of the business system:
the traffic monitoring device sets initial data; the initial data includes an initial third transaction amount, an initial fourth transaction amount, and an initial fifth transaction amount.
5. A traffic monitoring apparatus, comprising:
the acquisition module is used for acquiring first transaction data of the business system; the first transaction data is used for indicating the change of the transaction quantity of a first time period, and the first time period is a historical time period;
the processing module is used for determining an expected transaction amount interval according to the first transaction data acquired by the acquisition module and a three-point estimation method;
the early warning module is used for sending early warning information to the service system when the processing module determines that the target transaction amount is larger than the first transaction amount or smaller than the second transaction amount; the first transaction amount is the upper limit of the expected transaction amount interval, the second transaction amount is the lower limit of the expected transaction amount interval, and the target transaction amount is the real-time transaction amount of the current time period.
6. The traffic monitoring apparatus according to claim 5, wherein the first transaction data includes a third transaction amount, a fourth transaction amount and a fifth transaction amount, the third transaction amount is used for indicating a maximum value of the transaction amount of the first time period, the fourth transaction amount is used for indicating a minimum value of the transaction amount of the first time period, and the fifth transaction amount is used for indicating an average value of the transaction amount of the first time period; the processing module comprises a first calculating submodule, a second calculating submodule and a third calculating submodule;
the first calculation submodule is used for determining a transaction amount expected value according to the three-point estimation method, the third transaction amount, the fourth transaction amount and the fifth transaction amount;
the second calculation submodule is used for determining a transaction amount standard deviation according to the three-point estimation method, the third transaction amount and the fourth transaction amount;
and the third calculation submodule is used for determining the expected transaction amount interval according to the three-point estimation method, the expected transaction amount value determined by the first calculation submodule and the standard deviation of the transaction amount determined by the second calculation submodule.
7. The traffic monitoring apparatus according to claim 6, wherein the apparatus further comprises an update module;
the updating module is used for updating the third transaction amount or the fourth transaction amount when the target transaction amount is larger than the third transaction amount or smaller than the fourth transaction amount.
8. The traffic monitoring apparatus according to claim 7, wherein the apparatus further comprises an assignment module;
the assignment module is used for setting initial data; the initial data includes an initial third transaction amount, an initial fourth transaction amount, and an initial fifth transaction amount.
9. A traffic monitoring apparatus comprising a memory, a processor, a bus and a communication interface; the memory is used for storing computer execution instructions, and the processor is connected with the memory through the bus; the processor executes the computer-executable instructions stored by the memory to cause the traffic monitoring device to perform the traffic monitoring method of any of claims 1-4 when the traffic monitoring device is operating.
10. A computer program product, characterized in that the computer program product comprises computer instructions which, when run on a traffic monitoring apparatus, cause the traffic monitoring apparatus to perform the traffic monitoring method according to any of claims 1-4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110579803.7A CN113159463A (en) | 2021-05-26 | 2021-05-26 | Traffic monitoring method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110579803.7A CN113159463A (en) | 2021-05-26 | 2021-05-26 | Traffic monitoring method and device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113159463A true CN113159463A (en) | 2021-07-23 |
Family
ID=76877610
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110579803.7A Pending CN113159463A (en) | 2021-05-26 | 2021-05-26 | Traffic monitoring method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113159463A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113537617A (en) * | 2021-07-29 | 2021-10-22 | 中国工商银行股份有限公司 | Method, device, equipment and storage medium for predicting data distribution |
| CN113627940A (en) * | 2021-08-27 | 2021-11-09 | 中国银行股份有限公司 | Transaction amount abnormity warning method and device |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109034600A (en) * | 2018-07-20 | 2018-12-18 | 广东电网有限责任公司 | For the evaluation method of Business Process System service, device, equipment and storage medium |
| CN109218062A (en) * | 2017-07-07 | 2019-01-15 | 百度在线网络技术（北京）有限公司 | Internet service alarm method and device based on confidence interval |
| US10445738B1 (en) * | 2018-11-13 | 2019-10-15 | Capital One Services, Llc | Detecting a transaction volume anomaly |
| CN111210225A (en) * | 2020-01-14 | 2020-05-29 | 中国建设银行股份有限公司 | State monitoring method, device, equipment and storage medium of transaction system |
| CN112596996A (en) * | 2020-12-28 | 2021-04-02 | 中国农业银行股份有限公司 | Service monitoring method and device |
-
2021
- 2021-05-26 CN CN202110579803.7A patent/CN113159463A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109218062A (en) * | 2017-07-07 | 2019-01-15 | 百度在线网络技术（北京）有限公司 | Internet service alarm method and device based on confidence interval |
| CN109034600A (en) * | 2018-07-20 | 2018-12-18 | 广东电网有限责任公司 | For the evaluation method of Business Process System service, device, equipment and storage medium |
| US10445738B1 (en) * | 2018-11-13 | 2019-10-15 | Capital One Services, Llc | Detecting a transaction volume anomaly |
| CN111210225A (en) * | 2020-01-14 | 2020-05-29 | 中国建设银行股份有限公司 | State monitoring method, device, equipment and storage medium of transaction system |
| CN112596996A (en) * | 2020-12-28 | 2021-04-02 | 中国农业银行股份有限公司 | Service monitoring method and device |
Non-Patent Citations (1)
| Title |
|---|
| "三点估算法", pages 1, Retrieved from the Internet <URL:https://www.cnblogs.com/OliverQin/p/10517735.html> * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113537617A (en) * | 2021-07-29 | 2021-10-22 | 中国工商银行股份有限公司 | Method, device, equipment and storage medium for predicting data distribution |
| CN113627940A (en) * | 2021-08-27 | 2021-11-09 | 中国银行股份有限公司 | Transaction amount abnormity warning method and device |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109597685B (en) | Task allocation method, device and server | |
| CN103354924B (en) | For monitoring the method and system of performance indications | |
| US8578023B2 (en) | Computer resource utilization modeling for multiple workloads | |
| CN113159463A (en) | Traffic monitoring method and device | |
| CN105979532B (en) | Performance capacity analysis early warning method and device of service processing system | |
| EP3961404A1 (en) | Method, system, and apparatus for monitoring blockchain smart contract | |
| US10282245B1 (en) | Root cause detection and monitoring for storage systems | |
| CN113544647A (en) | Capacity management in cloud computing systems using virtual machine family modeling | |
| CN112565391A (en) | Method, apparatus, device and medium for adjusting instances in an industrial internet platform | |
| CN111966449A (en) | Virtual machine backup management method, system, terminal and storage medium | |
| CN114185675A (en) | Resource management method, device, electronic equipment and storage medium | |
| CN110673973B (en) | Abnormality determination method and device for application programming interface API | |
| CN114244718A (en) | Power transmission line communication network equipment management system | |
| CN111897706A (en) | Server performance prediction method, device, computer system and medium | |
| CN115437793A (en) | System resource allocation prediction method, device, equipment and storage medium | |
| US10223189B1 (en) | Root cause detection and monitoring for storage systems | |
| CN111209333B (en) | Data updating method, device, terminal and storage medium | |
| CN110855484B (en) | Method, system, electronic device and storage medium for automatically detecting traffic change | |
| CN110928748A (en) | Business system operation monitoring method and device | |
| CN111585789B (en) | Data prediction method and device | |
| CN109508356B (en) | Data abnormality early warning method, device, computer equipment and storage medium | |
| CN113612624A (en) | Method and device for processing heartbeat between nodes | |
| CN116303804B (en) | Data comparison method, device, equipment and medium | |
| CN113781092A (en) | Data processing method, device, equipment and storage medium | |
| CN111461559A (en) | Spare part demand determining method and device and electronic equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |