CN106528564A - Congestion data processing method and apparatus - Google Patents

Congestion data processing method and apparatus Download PDF

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Publication number
CN106528564A
CN106528564A CN201510578481.9A CN201510578481A CN106528564A CN 106528564 A CN106528564 A CN 106528564A CN 201510578481 A CN201510578481 A CN 201510578481A CN 106528564 A CN106528564 A CN 106528564A
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pending data
classification
data
pending
value
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王慧
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China Mobile Group Hebei Co Ltd
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China Mobile Group Hebei Co Ltd
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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90Details of database functions independent of the retrieved data types
    • G06F16/903Querying
    • G06F16/90335Query processing

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  • Databases & Information Systems (AREA)
  • Theoretical Computer Science (AREA)
  • Computational Linguistics (AREA)
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  • General Engineering & Computer Science (AREA)
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Abstract

The invention discloses a congestion data processing method. The method comprises the steps of setting a safety threshold and a type of to-be-processed data and a priority processing level of each type of to-be-processed data; and when the value of the to-be-processed data exceeds the safety threshold, determining the type of the to-be-processed data according to an attribute of the to-be-processed data, and processing the to-be-processed data subjected to type determination according to the priority processing level of each type of to-be-processed data. The invention furthermore discloses a congestion data processing apparatus.

Description

A kind of congestion data treating method and apparatus
Technical field
A kind of the present invention relates to technical field of data processing, more particularly to congestion data treating method and apparatus.
Background technology
In information service industry, the unit value of telecommunication service is increasing, and user may produce at short notice The a large amount of expenses of life, increase the risk of arrearage.Additionally, operators in co-operation partner will be extended to more areas, Value chain is increasingly complicated, the unlawful practice of some partners, set expense can Jing often occurs, cause consumer's risk, Value chain risk and marketing risk gradually expose.
For solving the above problems, arrearage risk control, Fig. 1 is realized now by way of Intelligent network service Mode for Intelligent network service realizes the network topology composition structural representation of arrearage risk control, such as Fig. 1 institutes Show, wherein:
Service control point (SCP), there is provided monitored protocol conversion between network element and online charging subsystem and preliminary Identify whether the function of being monitored user;
Mobile switching centre (MSC), increases authorizing procedure, and business information is converted to authentication message triggering To online certificate status protocol (Online Certificate Status Protocol, OSCP), drawn by real time billing Whether hold up the inverse business allows user to use;
System (Business&Operation Support System, BOSS) is supported in telecommunication service operation maintenance, Screening targeted customer, sends targeted customer non-supervised business ticket to real time billing engine, receives and counts in real time Ticket preferentially deduct fees and be supplied to user to inquire about after expense engine wholesale price;
Real time billing engine, carries out pre-approved price in real time according to the message of reported by network elements, and compares with remaining sum, greatly In or allow business to continue when being equal to, otherwise, interrupting service produces in real time wholesale price ticket during service ending.
Structure as shown in Figure 1, by supporting network and Low Level Signaling Transfer Point LSTP (Low Signal Transfer Point, LSTP) between increase SCP, the call of real-time control user controls the generation of arrearage.
The Intelligent network service mode increased after SCP for user realizes flow process such as Fig. 2 institutes of arrearage risk control Show, the Intelligent network service mode after SCP is increased realizes owing risk control system, system process per point Clock is obtained and once needs processing data, and obtaining per ten minutes has once increased the use of intelligent network contract signing relationship now Amount, the intelligent network maximum contracted user's number that can be carried specified in system, regulation about 500 in current system Ten thousand.Specifically, it is described to realize that the step of owing risk control system completes control includes:
Step 201, needs increase intelligent network signing by what BOSS sides filtered out under the screening principle of regulation Data and need delete intelligent network signing data, need delete Intelligent network service data with user balance Whether it is criterion less than 10 yuan, when user balance reaches control threshold value, i.e., 10 yuan, sends out to intelligent network Signing instruction, after user pays dues, sends out to intelligent network when remaining sum is more than threshold value and cancels signing instruction;
Whether step 202, the maximum allowable contracted user's number of intelligent network are more than existing contracted user's number, are to hold Row step 203, otherwise execution step 204;
Step 203, when maximum allowable contracted user's number is more than contracted user's number, system allows to be increased Or intelligent network signing is deleted, terminate currently processed flow process;
Step 204, maximum allowable contracted user's number be less than or equal to contracted user's number when, system only allow into Row deletion action.
It can be seen that, when existing contracted user's number is more than maximum allowable contracted user's number, system will not be carried out again Increase signing operation, to need increase intelligent network signing user implement ignore policy, until several ten After minute, when existing contracted user's number that system is obtained is less than maximum allowable contracted user's number, increasing is performed again Plus or delete intelligent network subscribed services;Therefore, system can face such problem:Go what is obtained to show in system There is contracted user's number less than maximum allowable contracted user's number this several in ten minutes, as system is no longer carried out Increase the operation of intelligent network contracted user's number, intelligent network signing can be made to process not in time, cause data to be lost in, Have a strong impact on the arrearage risk control of system.
Also, system is obtaining existing contracted user's number stage, due to the restriction that there is maximum contracted user's number, When existing contracted user's number is closer to maximum contracted user's number, to the Screening Treatment urgency level of data more, And now existing procedure is still to obtain the user for once having increased now intelligent network contract signing relationship per ten minutes Number, when mass data is poured in, it may appear that the confusion of data processing, causes system data to process accuracy drop It is low, so that system can not normally perform arrearage risk control.
The content of the invention
For solving the problems, such as prior art, the embodiment of the present invention provide a kind of congestion data processing method and Device, it is possible to increase during Intelligent network service during data congestion data processing accuracy, so as to preferably Realize arrearage risk control.
What the technical scheme of the embodiment of the present invention was realized in:
A kind of processing method of congestion data is embodiments provided, the safety threshold of pending data is set Value, classification and the priority treatment rank per class pending data;Methods described also includes:
It is when the value of the pending data exceedes the secure threshold, true according to the attribute of the pending data The classification of the fixed pending data, processes described according to the priority treatment rank per class pending data Determine the pending data after classification.
In such scheme, methods described also includes:Arrange described according to the preferential of every class pending data Process the time limit of the pending data after the level reason determination classification;
Treating after the priority treatment rank process determination classification according to every class pending data is located Reason data also include:Untreated pending data in the previous time limit is preserved.
In such scheme, when the value of the pending data exceedes the secure threshold, according to described pending The attribute of data determines the classification of the pending data, according to the priority treatment per class pending data Before pending data after the rank process determination classification, methods described also includes:
Determine the value of the pending data, by the comparison of the value of the pending data and the secure threshold.
In such scheme, methods described also includes:After the previous time limit terminates, this waits to locate to described again When the value of reason data is compared with the secure threshold, if the value of this pending data is less than the peace Full threshold value, then to the untreated pending data that preserves in the previous time limit by into pending program Time sequencing is continued with.
In such scheme, the attribute according to the pending data determines the classification of the pending data Including:The pending data is screened using bayesian algorithm;It is determined that the pending data after screening Classification;
Methods described also includes:The pending data determined after classification is carried out using Bayes classifier Sort out.
The embodiment of the present invention additionally provides a kind of processing meanss of congestion data, and described device includes:
Setting unit, for arranging secure threshold, classification and every class pending data of pending data Priority treatment rank;
Main control unit, for when the value of the pending data exceedes the secure threshold, treating according to described The attribute of processing data determines the classification of the pending data, according to described per the preferential of class pending data Process the pending data after the level reason determination classification.
In such scheme, the setting unit is additionally operable to described in arranging according to every class pending data The time limit of the pending data after the priority treatment rank process determination classification;
Described device also includes:
Memory element, for preserving untreated pending data in the previous time limit.
In such scheme, the main control unit is additionally operable to determine the value of the pending data, treats to described The value of processing data is compared with the secure threshold.
In such scheme, the main control unit is additionally operable to after the previous time limit terminates, and this is again to described When the value of pending data is compared with the secure threshold, if the value of this pending data is less than institute Secure threshold is stated, then to the untreated pending data that preserves in the previous time limit by into pending journey The time sequencing of sequence is continued with.
In such scheme, the main control unit is additionally operable to enter the pending data using bayesian algorithm Row screening, it is determined that the classification of the pending data after screening;
The pending data determined after classification is sorted out using Bayes classifier.
A kind for the treatment of method and apparatus of congestion data provided in an embodiment of the present invention, by arranging pending number According to secure threshold, classification and priority treatment rank per class pending data, for obtaining in each cycle Whether the existing contracted user's quantity for taking exceeds secure threshold, and pending data is screened, classification is determined, Then sort out and priority treatment;In above process, system is by preserving the previous priority of there is no Untreated pending data, also, when the new process cycle of system starts, acquisition it is new pending When the value of data is less than the secure threshold for arranging, by the pending data value of previous preservation according to into pending The time sequencing of program is processed, and ensures that with this review of the data for not obtaining priority treatment power is processed. The setting of the secure threshold for embodiments providing and the dynamic entry/leave control of data, Neng Gouti During high Intelligent network service during data congestion data processing accuracy, and then arrears risk is better achieved Control, and data volume fluctuation is bigger, can more highlight the embodiment of the present invention in intelligent network service arrears risk Effect in control, effectively compensate for the limited deficiency of existing Intelligent network service system maximum load-carrying capacity.
Description of the drawings
Fig. 1 is the network topology composition structural representation that Intelligent network service mode realizes arrearage risk control;
Fig. 2 is that the Intelligent network service mode after user increase SCP realizes that the flow process of arrearage risk control is illustrated Figure;
The flow chart of the congestion data processing method that Fig. 3 is provided for the present embodiment;
A kind of flow chart of congestion data processing method in the preferred embodiment that Fig. 4 is provided for the present embodiment;
The original of data classification is carried out in the preferred embodiment that Fig. 5 is provided for the present embodiment using Bayes classifier Reason schematic diagram;
The congestion data processing meanss schematic diagram that Fig. 6 is provided for the present embodiment.
Specific embodiment
The present invention is described in further detail with reference to the accompanying drawings and examples, and owes with reference to telecommunications industry Expense risk control system is briefly to be introduced to the present invention, at the congestion data that Fig. 3 is provided for the present embodiment The flow chart of reason method, as shown in figure 3, congestion data processing method provided in an embodiment of the present invention includes:
Step 301, arranges the secure threshold of pending data, classification and per the preferential of class pending data Process rank;
Here, methods described also includes:Arrange described according to the priority treatment level per class pending data The time limit of the pending data after the other places reason determination classification;It is described according to described per class pending data The priority treatment rank process pending data determined after classification also includes:To in the previous time limit not The pending data of process is preserved.
In addition, the setting of pending data secure threshold, can be processed according to the specifically used congestion data The conventional working condition of the system of method is determining;The classification can be to need to increase intelligent network signing and need Delete intelligent network signing.
Step 302, when the value of the pending data exceedes the secure threshold, according to the pending number According to attribute determine the classification of the pending data, according to the priority treatment level per class pending data Pending data after the other places reason determination classification.
In addition, the attribute of the pending data can be the personalization of data in system using methods described Mark, such as:Can be the arrearage situation of monitored user, quilt in telecommunications industry owing risk control system Which kind of industry the history arrearage situation of monitoring user, the balance left situation of monitored user, user are needed using Business etc..
Here, when the value of the pending data exceedes the secure threshold, according to the pending data Attribute determines the classification of the pending data, according to the priority treatment level per class pending data Before pending data after the reason determination classification, methods described also includes:Determine the pending data Value, the comparison of the value of the pending data and the secure threshold.
Here, methods described also includes:After the previous time limit terminates, this is again to the pending data Value when comparing with the secure threshold, if the value of this pending data is less than the secure threshold, Then to the untreated pending data that preserves in the previous time limit by the time sequencing into pending program Continue with.
In addition, processing described true according to the priority treatment rank per class pending data described in the setting Determine the time limit of the pending data after classification;Untreated pending data in the previous time limit is protected Deposit;Determine the value of the pending data, the comparison of the value of the pending data and the secure threshold; After the previous time limit terminates, when this is compared with the secure threshold to the value of the pending data again, If the value of this pending data is less than the secure threshold, to what is preserved in the previous time limit Untreated pending data is continued with by the time sequencing into pending program.Said process combines step Rapid 301 and step 302 can complete previous untreated complete pending data review process.
Here, the attribute according to the pending data determines that the classification of the pending data includes: The pending data is screened using bayesian algorithm;It is determined that the classification of the pending data after screening; Methods described also includes:The pending data determined after classification is sorted out using Bayes classifier.
In addition, it is described sort out can for the classification be need to increase intelligent network signing be classified as " moving into " Instruct and need be classified as " the moving out " of deleting intelligent network signing to instruct.
Here, after the utilization bayesian algorithm is screened to the pending data and is determined screening The classification of pending data, including:
The preparation stage, including:Determine the characteristic attribute of pending data;Obtain training sample;
The classifier training stage, including:Prior probability is calculated to each classification;Each characteristic attribute is calculated The conditional probability of all divisions;
Application stage, including:The product of prior probability and class conditional probability is calculated to each classification;With priori Generic of the maximal term of the product of probability and class conditional probability as pending data.
A kind of processing method of congestion data provided in an embodiment of the present invention, by arranging the peace of pending data Full threshold value, classification and the priority treatment rank per class pending data, for showing for obtaining in each cycle Whether there is contracted user's quantity beyond secure threshold, pending data is screened, classification is determined, then Sort out and priority treatment;In above process, system there is no not locating for priority by preservation is previous The pending data of reason, also, when the new process cycle of system starts, the new pending data of acquisition Value less than arrange secure threshold when, by the pending data value of previous preservation according to into pending program Time sequencing processed, the review for ensureing not obtain with this data of priority treatment power is processed.This The setting of the secure threshold that bright embodiment is provided and the dynamic entry/leave control of data, it is possible to increase intelligence Can in net service process during data congestion data processing accuracy, and then arrearage risk control is better achieved, And data volume fluctuation is bigger, can more highlight the embodiment of the present invention in intelligent network service arrearage risk control Effect, effectively compensate for the limited deficiency of existing Intelligent network service system maximum load-carrying capacity.
The invention provides a kind of preferred embodiment, is classified to pending data using Bayes classifier, Bayesian formula calculates the posterior probability values wanted needed for Bayes classifier, below in conjunction with Intelligent network service system The process of system congestion data is briefly introduced to presently preferred embodiments of the present invention, and processing procedure is as shown in Figure 4.
In the present embodiment, the system that Intelligent network service mode realizes arrearage risk control, system process per point Clock obtains a pending data, and obtaining per ten minutes has once increased the use of intelligent network contract signing relationship now Amount, the intelligent network maximum contracted user's number that can be carried specified in system, in addition, specify in system at present Maximum contracted user's number about 5,000,000.
Process B1 obtains pending data, and which performed the cycle for 1 minute;Process A was examined every 10 minutes Survey the current resource occupation capacity of primary system;Process B2 is increased to pending data or is deleted intelligence The operation of net signing, wherein, maximum signing number is set to M, and secure threshold is set to S.
The letter control request queue formed according to raw mode is the unordered queue with regard to " execution action type ", Process B2 is also required to read each director data in queue one by one when letter control request task is processed, by One differentiates " action type " and then gives and respond, the processing method can ensure that the correctness that instruction processes but Be sacrifice it is ageing.
In the present embodiment, the data that B1 processes read are carried out using minimal error rate Bayes classifier Classification in advance is processed, and is drawn the pending director data in the cycle according to " action type " attribute of data It is divided into the instruction of " moving into " class and the instruction of " moving out " class, so that process B2 carries out batch processing to instruction.
According to the conventional working condition of system, there is occupancy ultimate value M in system, once decision-making system is currently provided Source occupancy reaches M, and system will face the catastrophe failure of paralysis of crashing, the operation delay for now occurring and mistake Evolutionary operator probability can be greatly promoted, and cause customer complaint amount to increase sharply.
The system failure, the place in the handling process of Intelligent network service during data congestion are caused for keeping away factor data congestion Reason process optimization is as shown in figure 4, the processing procedure includes:
Step 401:Setting system occupancy secure threshold S, in owing risk control system, process A Every 10 minutes detection current resource occupation capacity of primary system, according to the Business Processing level of system, really System Current resource occupancy P is determined for Current resource occupancy capacity and the ratio of overall system capacity;
Step 402~404:Relatively resources occupation rate P and occupancy secure threshold S, are less than or equal to S in P When, determine that system does not have congestion risk, operation is performed by process B1, B2 according to original mode, held Row step 409;When P is more than S, determine that system has the risk of congestion, read by process B1 pending Instruction, and the pending instruction is screened, determines classification, afterwards, execution step 405;
Step 405:, carry out through screening, determining the pending instruction after classification to from step 404 Judge, complete classification in advance;
Step 406:Make to complete the pending instruction of " moving out " class of classification from step 405, preferentially enter Enter letter control request queue;
Step 407:Believe that to step 406 the pending instruction in control request queue carries out letter control by process B2 Reason;
Step 408:After step 407 terminates, judge whether process B1 enters the next working cycle, such as Fruit is into the next working cycle, then execution step 404, if it is not, then execution step 409;
Step 409:Judge whether process A enters the next working cycle, if it is, execution step 401, If not then execution step 410;
Step 410:Return to step 408, waiting process B2 are performed and are terminated.
Specifically, as shown in figure 5, being carried out to pending data using Bayes classifier in the present embodiment The process of classification, including:
Step 501, determines the characteristic attribute of pending data;
Here, characteristic attribute can be the arrearage situation of monitored user, the history arrearage feelings of monitored user Condition, the balance left situation of monitored user;
Step 502, obtains training sample;
Here, training sample belonged to into certain classification as condition specifically, the characteristic vector value of sample is made For result, then categorised decision process is the reasoning process according to results presumption condition;
Step 503, calculates the prior probability of each classification,
Here, feature space is divided into multiple decision regions by decision boundary, each decision region or multiple Decision region corresponds to certain classification;
Step 504, calculates the conditional probability of all divisions to each characteristic attribute;
Step 505, calculates the product of prior probability and class conditional probability to each classification;
Step 506, using the maximal term of prior probability and the product of class conditional probability as the institute of pending data Category classification;
Here, when sample belongs to certain class, its characteristic vector is necessarily fallen in corresponding decision region, works as sample When being originally not belonging to certain class, its characteristic vector is necessarily will not fall in corresponding decision region, then, in pattra leaves After sample in this grader with characteristic vector value as a result is fallen in certain decision region, then its certain category In corresponding class.
Here, step 501 and step 502 are preparation working stage;Step 503 and step 504 are classification The device training stage;Step 505 and step 506 are the application stage.
Wherein, conditional probability, prior probability, posterior probability etc. can be calculated by Bayesian formula, most Afterwards again by minimal error rate Bayes classifier calculate classification error probability, specifically using Bayesian formula, The process that minimal error rate Bayes classifier is calculated is as follows:
Calculating of the Bayesian formula in the process of the Intelligent network service system congestion data is briefly introduced first Process is as follows:
Carry out the mathematical method of inverse probability reasoning, it is expressed as:If the sample space of test E is S, A For the event of E, B1, B2... ..., BcOne for S divides, and P (A)>0, P (Bi)>0) I=1,2 ... ... c), then:
In formula:
P(Bi| A) it is referred to as posterior probability, after representing that event A (result A) occurs, and incompatible condition BiDeposit Probability, it result appearance after just clearing obtain, therefore be referred to as " posteriority ".
P(A|Bi) it is referred to as class conditional probability, represent each condition BiIn the presence of, the probability that result event A occurs;
P(Bi) it is referred to as prior probability, represent incompatible time BiThe probability of appearance, whether it is gone out with result A It is existing unrelated, only represent and inferred according to priori or main pass, it is believed that the appearance between generally each condition may Property has any difference;
P (A) is calculated by prior probability and class conditional probability, and it expresses result A and goes out under various conditions The full probability of existing overall probability, referred to as result A.
The process of combined with intelligent network service system congestion data, here, event A represents needs plus intelligent network control The signaling of system occurs, and event B represents that the signaling for needing to delete intelligent network control occurs.
Here, using Bayes classifier, the probability occurred for event A and event B is carried out to signaling Classification.
Minimal error rate Bayes classifier is introduced again briefly in the Intelligent network service system congestion data Calculating process in process is as follows:
As the prior probability P (ω that known class occursi) and each apoplexy due to endogenous wind sample distribution class conditional probability it is close Degree P (x | ωi) when, the posterior probability P (ω of every class can be belonged in the hope of a sample to be sortedi| x), will incorporate into That maximum apoplexy due to endogenous wind of posterior probability, this grader is referred to as minimal error rate Bayes classifier, for two Class problem, its categorised decision planning are represented by:
As P (ωi|x)>P(ωj| when x), adjudicate x ∈ ωi
When using maximum a posteriori probability grader, the probability of classification error is:
For realizing said method, the embodiment of the present invention additionally provides a kind of processing meanss of congestion data, such as schemes Shown in 6, described device includes:
Setting unit 601, for arranging secure threshold, classification and the pending number of every class of pending data According to priority treatment rank;
Main control unit 602, for when the value of the pending data exceedes the secure threshold, according to institute The attribute for stating pending data determines the classification of the pending data, according to every class pending data Pending data after the priority treatment rank process determination classification.
Here, the setting unit 601, is additionally operable to arrange described according to the excellent of every class pending data The time limit of the pending data after the level reason determination classification is processed first.
The processing meanss also include:Memory element 603, it is untreated in the previous time limit for preserving Pending data.
Here, the main control unit 602, is additionally operable to determine the value of the pending data, waits to locate to described The value of reason data is compared with the secure threshold.
Here, the main control unit 602, is additionally operable to after the previous time limit terminates, and this is treated to described again When the value of processing data is compared with the secure threshold, if the value of this pending data is less than described Secure threshold, then to the untreated pending data that preserves in the previous time limit by into pending program Time sequencing continue with.
Here, the main control unit 602, is additionally operable to be determined according to the attribute of the pending data described After the classification of the pending data, process described according to the priority treatment rank per class pending data Before determining the pending data after classification, the pending data determined after classification is sorted out.
Here, the main control unit 602, specifically for being entered to the pending data using bayesian algorithm Row screening, it is determined that the classification of the pending data after screening;Using Bayes classifier to the determination classification Pending data afterwards is sorted out.
Here, the main control unit 602, specifically for determining the characteristic attribute of pending data;Obtain instruction Practice sample;Prior probability is calculated to each classification;The conditional probability of all divisions is calculated to each characteristic attribute; The product of prior probability and class conditional probability is calculated to each classification;With taking advantage of for prior probability and class conditional probability Generic of the long-pending maximal term as pending data.
In addition, in order to be able to data are preserved in time, memory element 603 can be used for storing the data Secure threshold, the classification of the data, the priority treatment rank per class data, the pending data, The sorted pending data.
For example, in Telecom Operators owing risk control system in the processing procedure of congestion data, the place The setting unit of reason device arranges the secure threshold of pending data, classification according to the data that system was processed in the past And per the priority treatment rank of class pending data, and the main control unit of the processing meanss is for being The pending data that system is obtained at set intervals, exceedes the secure threshold in the value of the pending data When, the classification of the pending data is determined according to the attribute of the pending data, is treated per class according to described The priority treatment rank of processing data processes the pending data after the determination classification.
A kind of processing method of congestion data provided in an embodiment of the present invention, by arranging the peace of pending data Full threshold value, classification and the priority treatment rank per class pending data, for showing for obtaining in each cycle Whether there is contracted user's quantity beyond secure threshold, pending data is screened, classification is determined, then Sort out and priority treatment;In above process, system there is no not locating for priority by preservation is previous The pending data of reason, also, when the new process cycle of system starts, the new pending data of acquisition Value less than arrange secure threshold when, by the pending data value of previous preservation according to into pending program Time sequencing processed, the review for ensureing not obtain with this data of priority treatment power is processed.This The setting of the secure threshold that bright embodiment is provided and the dynamic entry/leave control of data, it is possible to increase intelligence Can in net service process during data congestion data processing accuracy, and then arrearage risk control is better achieved, And data volume fluctuation is bigger, can more highlight the embodiment of the present invention in intelligent network service arrearage risk control Effect, effectively compensate for the limited deficiency of existing Intelligent network service system maximum load-carrying capacity.
In addition, in actual applications, the setting unit 601, main control unit 602, memory element 603 By the central processing unit (Central Processing Unit, CPU) in terminal, microprocessor (Micro Processor Unit, MPU), digital signal processor (Digital Signal Processor, DSP), or Field programmable gate array (Field Programmable Gate Array, FPGA) etc. is realized.
The above, the only specific embodiment of the present invention, but protection scope of the present invention is not limited to This, any those familiar with the art the invention discloses technical scope in, can readily occur in Change or replacement, should all be included within the scope of the present invention.Therefore, protection scope of the present invention should It is defined by the scope of the claims.

Claims (10)

1. a kind of processing method of congestion data, it is characterised in that arrange pending data secure threshold, Classification and the priority treatment rank per class pending data;Methods described also includes:
It is when the value of the pending data exceedes the secure threshold, true according to the attribute of the pending data The classification of the fixed pending data, processes described according to the priority treatment rank per class pending data Determine the pending data after classification.
2. processing method according to claim 1, it is characterised in that methods described also includes:Arrange It is described to process the pending number determined after classification according to the priority treatment rank per class pending data According to time limit;
Treating after the priority treatment rank process determination classification according to every class pending data is located Reason data also include:Untreated pending data in the previous time limit is preserved.
3. processing method according to claim 1, it is characterised in that the value of the pending data surpasses When crossing the secure threshold, the classification of the pending data is determined according to the attribute of the pending data, According to the priority treatment rank per class pending data process the pending data determined after classification it Before, methods described also includes:
Determine the value of the pending data, by the comparison of the value of the pending data and the secure threshold.
4. the processing method according to Claims 2 or 3, it is characterised in that methods described also includes: After the previous time limit terminates, when this is compared with the secure threshold to the value of the pending data again, If the value of this pending data is less than the secure threshold, to what is preserved in the previous time limit Untreated pending data is continued with by the time sequencing into pending program.
5. processing method according to claim 1, it is characterised in that described according to the pending number According to attribute determine that the classification of the pending data includes:
The pending data is screened using bayesian algorithm;
It is determined that the classification of the pending data after screening;
Methods described also includes:The pending data determined after classification is carried out using Bayes classifier Sort out.
6. a kind of processing meanss of congestion data, it is characterised in that described device includes:
Setting unit, for arranging secure threshold, classification and every class pending data of pending data Priority treatment rank;
Main control unit, for when the value of the pending data exceedes the secure threshold, treating according to described The attribute of processing data determines the classification of the pending data, according to described per the preferential of class pending data Process the pending data after the level reason determination classification.
7. processing meanss according to claim 6, it is characterised in that
The setting unit, is additionally operable to arrange described according to the priority treatment rank per class pending data Process the time limit of the pending data after the determination classification;
Described device also includes:
Memory element, for preserving untreated pending data in the previous time limit.
8. processing meanss according to claim 6, it is characterised in that
The main control unit, is additionally operable to determine the value of the pending data, the value to the pending data It is compared with the secure threshold.
9. processing meanss according to claim 7 or 8, it is characterised in that
The main control unit, is additionally operable to after the previous time limit terminates, and this is again to the pending data When value is compared with the secure threshold, if the value of this pending data is less than the secure threshold, Then to the untreated pending data that preserves in the previous time limit by the time sequencing into pending program Continue with.
10. processing meanss according to claim 6, it is characterised in that
The main control unit, is additionally operable to screen the pending data using bayesian algorithm, it is determined that The classification of the pending data after screening;
The pending data determined after classification is sorted out using Bayes classifier.
CN201510578481.9A 2015-09-11 2015-09-11 Congestion data processing method and apparatus Pending CN106528564A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108399259A (en) * 2018-03-09 2018-08-14 深圳市汗青文化传媒有限公司 A kind of data processing method and system

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1593044A (en) * 2001-09-27 2005-03-09 超级芯片有限公司 Method and system for congestion avoidance in packet switching devices
CN101803311A (en) * 2007-09-17 2010-08-11 高通股份有限公司 Priority scheduling and admission control in a communication network
CN102025617A (en) * 2010-11-26 2011-04-20 中兴通讯股份有限公司 Method and device for controlling congestion of Ethernet
US8756337B1 (en) * 2007-08-03 2014-06-17 Hewlett-Packard Development Company, L.P. Network packet inspection flow management
CN104239100A (en) * 2014-09-11 2014-12-24 浪潮软件集团有限公司 Universal data processing method
CN104902514A (en) * 2014-03-07 2015-09-09 中兴通讯股份有限公司 Load balance method and device

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1593044A (en) * 2001-09-27 2005-03-09 超级芯片有限公司 Method and system for congestion avoidance in packet switching devices
US8756337B1 (en) * 2007-08-03 2014-06-17 Hewlett-Packard Development Company, L.P. Network packet inspection flow management
CN101803311A (en) * 2007-09-17 2010-08-11 高通股份有限公司 Priority scheduling and admission control in a communication network
CN102025617A (en) * 2010-11-26 2011-04-20 中兴通讯股份有限公司 Method and device for controlling congestion of Ethernet
CN104902514A (en) * 2014-03-07 2015-09-09 中兴通讯股份有限公司 Load balance method and device
CN104239100A (en) * 2014-09-11 2014-12-24 浪潮软件集团有限公司 Universal data processing method

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108399259A (en) * 2018-03-09 2018-08-14 深圳市汗青文化传媒有限公司 A kind of data processing method and system

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Application publication date: 20170322