CN103260193A - Device and method for strategy control - Google Patents
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Abstract
The invention provides a device and a method for strategy control. The device and method is used for resolving strategy control problems in a mobile internet. The device for the strategy control is respectively connected with an operation support system (OSS) and a network element in the mobile internet and is used for obtaining load data of a base station substation from the OSS, the load data are disposed and then compared with preset strategy trigger conditions, comparing results are obtained, corresponding strategies are obtained according to the comparing results, and flow control processing is carried out on the base station subsystem according to the strategies through the network element. According to the device and the method for the strategy control, intelligent control for a base station is achieved, the intelligent control is based on the load data collected from the base station, and therefore the device and the method have integrity and effectiveness.
Description
Technical field
The invention belongs to the mobile Internet field, relate to the data service technology, more specifically, relate to a kind of policy control apparatus and method.
Background technology
Mobile Internet traffic management and control means mainly comprise bandwidth restriction, priority control, flow compression, content buffering etc. at present, and the use of various management and control means needs collocation strategy to command.Strategy comprises the trigger condition of management and control means, as the specific zone of using in the management and control means, specific period, specific professional and specific terminal etc.; Strategy also comprises the control parameter of management and control means, as the bandwidth upper limit of bandwidth restriction, and the compression ratio of flow compression, URL of content buffering etc.
The scheme of tactful management and control mainly contains following two kinds of schemes in the mobile Internet at present, and a kind of is configuration and management strategy in the device of carrying out the management and control means; A kind of concentrated policy configurations and way to manage of being to use is about to independent being placed in the special device of function of policy configurations and management, and distributing policy is to many devices of carrying out the management and control means.Preceding a kind of scheme representation example is the clauses and subclauses of direct configured port bandwidth restriction on router; The representation example strategy of a kind of scheme in back and the control (PCC that charges, Policy Control and Charging), in the PCC scheme, usage policy and charging rule decision entity (PCRF, Policy Control Rule Function) management and distributing policy, implementation strategy be strategy and charge execution function (PCEF, Policy Control Enforcement Function), the PCEF function is usually located at gateway GGSN (GPRS Gateway Support Node).
The application target of each management and control means mainly contains the following aspects:
The first, network resource optimization as alleviate the flow pressure on port and link by the bandwidth restriction, is alleviated the pressure of Radio Resource in the residential quarter by bandwidth restriction and priority control;
The second, the user experiences lifting, as shortening the time that the user downloads webpage by the flow compression, shortens the time that customer flow transmits by the content buffering in the Internet;
Three, manage to promote, as carrying out the guarantee that the user experiences by the bandwidth that guarantees the high-value user, and then improve high-value user's loyalty; Suppress low value customer flow and resource occupation, thereby promote the unit discharge income.
The present mode of the policy development of each management and control means is artificial static mode, the content (judgment condition and policing parameter) of strategy is formulated according to personal experience, the network information and market management information by the network management personnel, the renewal that the network management personnel manually carries out strategy according to variation and the market management change in information of personal experience, the network information, tactful coming into force and tactful termination.But there is following defective in the tactful management and control mode of manual static:
1) on the time dimension, existing data service flowtube prosecutor case does not utilize the real-time load information of wireless access network side to carry out dynamical feedback to regulating and control strategy, but carry out policy configurations according to artificial experience and BOSS business datum etc. statically, and static policy configurations can make strategy lack ageing and accuracy, thereby influences the effect of management and control.
(2) Data Source of existing management and control scheme is comprehensive inadequately, and the effect that relies on BOSS user data/historical business datum to wait to carry out management and control is a kind of management and control mode of coarseness.
(3) on the management and control target dimension, because choosing of the goal of regulation and control residential quarter that existing management and control scheme selection goal of regulation and control is is non real-time and static, not necessarily transship always in the zone of data service overload in history, thereby can carry out management and control to some unnecessary residential quarters of management and control of taking, influenced the user and experienced and business revenue.Perhaps can't in time carry out effective management and control to some new Hot Spot.
(4) on the management and control means, existing management and control scheme is failed abundant each flow control network element (GGSN/WAP gateway/BSC etc.) that uses in the existing network three-dimensionally and is coordinated three-dimensional orderly traffic management and control, but relatively independently on each network element carry out management and control disorderly, can't reach the excellent results of three-dimensional management and control.
To sum up, there is the undesirable problem of management and control effect in the prior art.
Summary of the invention
The invention provides a kind of policy control apparatus and method, be used for solving the undesirable problem of management and control effect that prior art exists.
For achieving the above object, according to an aspect of the present invention, provide a kind of policy control device, and by the following technical solutions:
The policy control device, be applied to the policy control in the mobile Internet, described policy control device connects OSS OSS and the network element in the mobile Internet respectively, be used for obtaining from described OSS OSS the load data of base station sub-system, described load data is handled the back to be compared with the predetermined strategy trigger condition, draw comparative result, obtain corresponding strategy and by described network element described base station sub-system is implemented the Flow Control processing according to described strategy according to described comparative result.
Further, described policy control device comprises: data processor, connect OSS OSS, be used for carrying out data cleansing and loading index calculates to the load data of the described base station sub-system obtained from described OSS OSS and to described load data, draw the data computation result; Memory is used for the described predetermined strategy of storage and described preset trigger condition; Trigger connects described data processor and described memory, is used for obtaining described strategy after the described data computation result that will receive and described predetermined strategy trigger condition compare, and with described policy distribution; Dispensing device connects described trigger, is used for receiving and described strategy, and the described strategy of book is sent to described network element.
Further, the policy control device also comprises: the user service information database, connect described trigger, be used to described trigger that user service information is provided, described trigger also is used for obtaining described user service information according to described data computation result to described user service data storehouse, and generates the strategy that becomes more meticulous according to described service-user information and described data computation result.
Further, the policy control device also comprises: data-interface, connect input data source, and be used to described policy control device that reference data is provided, described reference data is used to described policy control device to obtain distributing policy basis is provided.
Further, described load data is all indicated acquisition time when being acquired, and this described load data that has time attribute is used for producing described real-time policy according to described trigger condition generation strategy tabulation by described Policy List.
Further, the described described load data that has time attribute also is used for according to prediction result described base station sub-system being carried out strategy adjustment by the load estimation of prediction algorithm realization to the following scheduled time.
According to another aspect of the present invention, provide a kind of policy control method, and by the following technical solutions:
Policy control method comprises: obtain the load data of base station sub-system, and described load data is handled, obtain result; Described result and predetermined strategy trigger condition are compared, obtain comparative result; Trigger corresponding strategy according to described comparative result, and corresponding strategy is implemented Flow Control by network element to described base station sub-system handle.
Further, described load data is all indicated the time of collection when being gathered, and described policy control device obtains the load data of base station sub-system, and described load data is handled, and obtains the result step and comprises; Described load data is carried out data cleansing to described policy control device and loading index calculates, generate the loading index time list, described policy control device compares described load data and predetermined strategy trigger condition, obtaining the comparative result step comprises: described policy control device compares described loading index time list and described predetermined strategy trigger condition, draws the Policy List under each time period.
Further, trigger corresponding strategy at described policy control device according to described comparative result, and with described strategy by network element to described base station sub-system being implemented after the Flow Control treatment step, described policy control method also comprises: described policy control device obtains the load sequence of each historical time according to described loading index time list; Described policy control device is calculated the load information of following identical time in advance according to the load sequence of described historical time, is used for described base station sub-system is carried out strategy adjustment.
Further, trigger corresponding strategy at described policy control device according to described comparative result, and with corresponding strategy by network element to described base station sub-system being implemented after the Flow Control treatment step, described policy control method also comprises: described policy control device judges whether corresponding strategy relates to user's business information, and obtains judged result; Be corresponding strategy when relating to described user's business information in described judged result, described policy control device obtains described user's business information by the user service information database.
Therefore, by technique scheme of the present invention, as can be seen, the present invention has following beneficial effect:
1, proposed to build concentrated management and control intelligent strategy center IPC in network, the flexibility that IPC has and expandability are to realize full use existing network data, the base apparatus of Flow Control and three-dimensional Flow Control in real time;
2, proposed to feed back to the Flow Control mode based on feedback that IPC generates real-time policy and influences the Access Network load from the Access Network load information;
3, on 2 basis, proposed a kind of based on historical and quasi real time data carry out the forecast function node, can adjust in real time the Flow Control strategy according to predicting the outcome.
Except purpose described above, feature and advantage, the present invention also has other purpose, feature and advantage.With reference to figure, the present invention is further detailed explanation below.
Description of drawings
Accompanying drawing is used to provide further understanding of the present invention, constitutes the application's a part, and illustrative examples of the present invention and explanation thereof are used for explaining the present invention, do not constitute improper restriction of the present invention.In the accompanying drawings:
Fig. 1 represents the operation principle schematic diagram of the described policy control device of the embodiment of the invention and base station sub-system and network element;
Fig. 2 represents the described policy control device of embodiment of the invention internal structure schematic diagram;
Fig. 3 represents the connection diagram of the described policy control device of the embodiment of the invention and existing network network element;
Fig. 4 represents the main flow chart of the described policy control method of the embodiment of the invention.
Embodiment
Below in conjunction with accompanying drawing embodiments of the invention are elaborated, but the multitude of different ways that the present invention can be defined by the claims and cover is implemented.
Fig. 1 represents the operation principle schematic diagram of the described policy control device of the embodiment of the invention and base station sub-system and network element.
Referring to shown in Figure 1, policy control device IPC30 connects OSS OSS (not showing among Fig. 1) and the Flow Control network element 50 in the mobile Internet respectively, be used for obtaining from described OSS OSS the load data of described BSS10, described load data is handled the back to be compared with the predetermined strategy trigger condition, get a comparative result, trigger corresponding real-time policy according to described comparative result, according to described real-time policy BSS10 is implemented Flow Control by described Flow Control network element 50 and handle.
In the technique scheme of present embodiment, IPC30 gathers the load data generation Flow Control instruction of BSS10 and carries out the data service Flow Control, thereby has influence on the feedback operation mode of BSS10 load.In particular, the data computation that IPC30 is correlated with data service from OSS collection BSS10 goes out the radio bearers index the Access Network, and these loading index can comprise:
A. the no line use ratio of all residential quarters of existing network;
B. the half rate ratio of residential quarter;
C. data service accounts for the Radio Resource ratio;
D. every PDCH bearer traffic etc.
All above-mentioned indexs are attached free attribute all, indicates the acquisition time of index.All these indexs all are time serieses with complete lock in time of interval so.IPC30 compares with the tactful trigger condition that prestores after the above-mentioned load data that has time attribute is handled, and produces real-time control strategy, and should implement the Flow Control processing by 50 couples of BSS10 of Flow Control network element by real-time control strategy.
The advantage of technique scheme is, the present invention introduces centralized policy control device in mobile Internet traffic management and control scheme, namely intelligent strategy center IPC (Intelligent Policy Centre) equipment is realized the dynamic strategy management and control that becomes more meticulous to management and control time/target/means/customer group etc.The IPC utilization is judged management and control residential quarter, customer group and time from the dynamic load information that the OSS system obtains, and the professional management and control of comprehensive three-dimensional driving multiple network element realization active data, thereby guarantee that finite wireless resources ensures that high-value user's user experiences.
Fig. 2 represents the described policy control device of embodiment of the invention internal structure schematic diagram.
Referring to shown in Figure 2, preferably, described policy control device 30 comprises: data processor 31, connect OSS OSS (not showing among Fig. 2), and be used for the described load data that obtains from described OSS is handled, get a data processed result; Memory 37 is used for the described predetermined strategy of storage and described preset trigger condition; Trigger 33 connects described data processor 31 and described memory 37, and the described data processed result and the described predetermined strategy trigger condition that are used for receiving compare, and issue and described comparative result corresponding strategy; Dispensing device can issue device 35 for processing, connects described trigger 33, is used for receiving and described comparative result corresponding strategy, and will be sent to network element (not showing among Fig. 2) with described comparative result corresponding strategy.
According to the technique scheme of present embodiment, the data computation of following data service to be correlated with that the data processor 31 of IPC is gathered from OSS the radio bearers index the Access Network, and these loading index can comprise:
A. the no line use ratio of all residential quarters of existing network;
B. the half rate ratio of residential quarter;
C. data service accounts for the Radio Resource ratio;
D. every PDCH bearer traffic etc.
All indexs are attached free attribute all, indicates the acquisition time of index.All these indexs all are time serieses with complete lock in time of interval so.The loading index time series that trigger 33 obtains from data processor 31 and the trigger condition in the memory 37 relatively come to determine the Policy List of triggering.
Preferably, the policy control device also comprises user service information database 39, connects described trigger 33, is used to described trigger 33 that user service information is provided.
User service information database 39 provides user service information for described trigger 33, after obtaining the real-time or historical radio bearers initial data of each residential quarter of existing network, initial data is carried out data cleansing and loading index and calculates, and generate according to the Flow Control strategy that loading index calculates and the customer service that obtains from BOSS becomes more meticulous below realizing:
A. at the Flow Control strategy of the whole network or specific cell;
B. at certain groups of users or specific user's Flow Control strategy;
C. at the Flow Control strategy of certain time period;
D. or the combination in any of a, b, c.
If data cleansing mainly is that undesirable data owner is had operations such as the data three major types data of data, the repetition of incomplete data, mistake are revised, filtration, make the data fit instructions for use.
Above-mentioned strategy is issued to PCRF policy control node in the PCC structure by control interface, perhaps WAP/Web gateway, perhaps Web/P2P Cache CDN starts.
Fig. 3 represents the connection diagram of the described policy control device of the embodiment of the invention and existing network network element.
Referring to shown in Figure 3, in the present embodiment, in conjunction with the PCC scheme, by distributing policy to PCRF, (PDP Context Active Request is the signaling title between mobile subscriber and the mobile network by the PDP Context Active Request of the Hot Spot of the PCEF among the GGSN when busy, the user initiates, in order that the user asks access to mobile network to surf the Net) carry out corresponding QoS control, comprise (the Packet Data Protocol to the PDP in specific cell/specific user/special time, the grouping message protocol) Context (PDP Context represents a user subject of access to mobile network) sets priority and maximum up-downgoing speed etc.; Instruction WAP Gateway starts the lossy compression method to picture/video after the busy residential quarter of the whole network reaches some, and the media data flow that reduces the whole network user consumes to save the on-air radio resource; After reaching some, the busy residential quarter of the whole network starts Web Cache CDN, CDN (Content Distribute Network, content distribution network), internet content buffering distributed network, be deployed within the operator, be used for the content of buffer-stored the Internet, user's visit can be direct accessed content provider, but extract content from internet content buffering distributed network, can improve the experience of user's online like this; Control the channel idle time of some always online instant messaging services by GGSN and more effectively utilize channel resource.
Preferably, the policy control device also comprises: the data-interface (not shown), be used for connecting input data source, and be used to described policy control device that described load data or reference data are provided.
In the technique scheme of present embodiment, at the policy control device data-interface is set, this data-interface can be the interface that connects OSS, but this interface can also connect other data sources, can add the input of new data comparatively easily, allow the IPC can be with reference to more data, to formulate more composition flexible strategies, also can add the more control means by this data-interface, make policy control means more horn of plenty and solid.
Preferably, described load data is all indicated acquisition time when being acquired, and is used for generating described real-time policy according to described trigger condition.
Preferably, described load data indicates all that when being acquired acquisition time also is used for according to described load estimation strategy adjustment being carried out in described base station by the load budget of prediction algorithm realization to the following time.
In two above-mentioned embodiment, suppose that the interval set of historical time of sampling is T={t
1, t
2T
i, all index sets are LI={li so
1, li
2, li
3Li
m, wherein, li
m={ li
Mt, t ∈ T}, LI so
T (i)={ li
1t (i), li
2t (i)Li
Mt (i), t (i)=t
i
Wherein, LI
T (i)Represent the set of all indexs under certain timeslice t (i).
Handle LI by above-mentioned data
T (i)Represent the set and predetermined strategy and trigger condition comparison of all indexs under certain timeslice t (i), determine real-time trigger policy tabulation.
And, on the basis of all these historical load time sequences that calculate, can use the load estimation of prediction algorithm realization to following certain time, suppose that prediction algorithm is the g computing, wherein, the g computing can be certain predicting network flow algorithm, can use autoregression (AR), moving average (MA), difference autoregression rolling average (ARMA) and FARIMA etc. linearity or nonlinear model to be the algorithm on basis, and specific algorithm does not launch in this literary composition.
Suppose that the predicted time set is: S={s
1, s
2S
i,
Index LI so
S=g (LI
T), therefore, the trigger condition of certain index is c as a result
nCan be expressed as down at timeslice s (i): { c
Ns (i)=fn{li
1ts (i), li
2s (i)Li
Ms (i), c
Ns (i)=0,1}.
c
Ns (i)Mean and all indexs on s (i) timeslice are done corresponding computing obtain 0 or 1,1 representative and go up loading index at certain time s (i) in the future and make certain tactful trigger condition set up in the identical time in future comprehensively going up, 0 expression is false.If the time interval of S and T is smaller, IPC can realize strategy adjustment quasi real time so.IPC can calculate Hot Spot and the Flow Control time of residential quarter or the Flow Control time of the whole network of needs Flow Control according to prediction data so, carries out Flow Control thereby can dispatch fluidic device targetedly.
Fig. 4 represents the main flow chart of the described policy control method of the embodiment of the invention.
Referring to shown in Figure 4, policy control method comprises:
S401: the policy control device obtains the load data of base station sub-system, and described load data is handled, and gets a result;
S403: described policy control device compares described result and predetermined strategy trigger condition, gets a comparative result;
S405: described policy control device triggers corresponding strategy according to described comparative result, and corresponding strategy is implemented Flow Control by network element to described base station sub-system handle.
In the technique scheme of present embodiment, in step S401, IPC utilizes the dynamic BSC load information that obtains from the OSS system to come for the reference of IPC management and control strategy, and the load data that obtains is all indicated acquisition time, the load data that has time attribute is handled, this processing can comprise: generate the loading index time list and compare with described predetermined strategy trigger condition, draw the Policy List under each time period, compare according to result and preset trigger condition, and comprehensively the multiple network element of three-dimensional driving is carried out effective real-time policy management and control, thereby guarantees that finite wireless resources ensures that high-value user's user experiences.
Preferably, described load data is all indicated the time of collection when being gathered, and described policy control device obtains the load data of base station, and described load data is handled, and gets a result step and comprises;
Described policy control device is handled described load data, generates the loading index time list.
This place can use above-mentioned identical embodiment to illustrate, supposes that the interval set of historical time of sampling is T={t
1, t
2T
i, all index sets are LI={li1 so, li2, li3 ... lim}, wherein, lim={limt, t ∈ T}, Lit (i)={ li so
1t (i), li
2t (i)Li
Mt (i), t (i)=ti; L
It (i)It then is the loading index time list.
By the technical scheme of present embodiment, loading index time series and predetermined strategy and predetermined strategy trigger condition relatively come to determine the Policy List of triggering.Like this, equal corresponding group policy under each timeslice when the loading index of gathering satisfies a certain trigger condition, namely triggers corresponding strategy in real time.
Preferably, trigger corresponding strategy at described policy control device according to described comparative result, and described strategy is implemented after the Flow Control treatment step described base station sub-system by network element, described policy control method also comprises:
Described policy control device obtains the load sequence of each historical time according to described loading index time list;
Described policy control device is calculated the load information of following identical time in advance according to the load sequence of described historical time, is used for strategy adjustment is carried out in described base station.
In the technique scheme of present embodiment, by above-mentioned loading index time list, obtain historical load time sequence, for example acquisition time is the load tabulation of this historical time of 10:00 point, this tabulation can comprise in one period, and for example load of each 10:00 in December in 2000 on December 20th, 10 days 1 this period of history forms the load tabulation then, realize daily load prediction December 21 in 2000 is supposed that prediction algorithm is the g computing by using prediction algorithm.Suppose that the predicted time set is S={s
1, s
2S
i, index LI so
S=g (LI
T), therefore, the trigger condition of certain index is c as a result
nCan be expressed as down at timeslice s (i): c
Ns (i)=f
n{ li
1s (i), li
2s (i)Li
Mts (i), c
Ns (i)=0,1; Mean and all indexs on s (i) timeslice are done corresponding computing obtain 0 or 1,1 representative and go up loading index at certain time s (i) in the future and make that certain tactful trigger condition will be set up in the identical time in future, 0 expression is false comprehensively going up.For example: m=2, li
1Be half rate ratio index, li
2Be data service Radio Resource accounting index, if strategy is set f so
nBe judged as li
1＞33.3% and li
2＞40%, if predict li this moment so
1=40% and li
2=42%, so tactful trigger condition c
nWill be 1, be about to trigger relative strategy control.
Preferably, trigger corresponding strategy at described policy control device according to described comparative result, and corresponding strategy is sent to after the step of described base station by net, described policy control method also comprises:
Described policy control device judges whether corresponding strategy relates to user's business information, and gets a judged result;
Be corresponding strategy when relating to described user's business information in described judged result, described policy control device obtains described user's business information by the user service information database.
By the technique scheme of present embodiment, if the strategy that triggers need relate to user's business information such as service groups, tactful trigger will obtain corresponding information from the BOSS customer data base, and these user profile can comprise:
A. the set meal type under the user,
B. user's set type is as the professional assurance group of data etc.
Therefore, by the above embodiment of the present invention, as can be seen, the present invention has following beneficial effect:
1, proposed to build concentrated management and control intelligent strategy center IPC in network, the flexibility that IPC has and expandability are to realize full use existing network data, the base apparatus of Flow Control and three-dimensional Flow Control in real time;
2, proposed to feed back to the Flow Control mode based on feedback that IPC generates real-time policy and influences the Access Network load from the Access Network load information;
3, on 2 basis, proposed a kind ofly based on forecast function node historical and when quasi real time data are hurried and busy residential quarter, can adjust in real time the Flow Control strategy according to predicting the outcome.
4, a kind of three-dimensional implementation method of planning as a whole data traffic flow prosecutor formula has been proposed, can be more effectively and save Radio Resource targetedly.
The above is the preferred embodiments of the present invention only, is not limited to the present invention, and for a person skilled in the art, the present invention can have various changes and variation.Within the spirit and principles in the present invention all, any modification of doing, be equal to replacement, improvement etc., all should be included within protection scope of the present invention.
Claims (10)
1. policy control device, be applied to the policy control in the mobile Internet, it is characterized in that, described policy control device connects OSS OSS and the network element in the mobile Internet respectively, be used for obtaining from described OSS OSS the load data of base station sub-system, described load data is handled the back to be compared with the predetermined strategy trigger condition, draw comparative result, obtain corresponding strategy and by described network element described base station sub-system is implemented the Flow Control processing according to described strategy according to described comparative result.
2. policy control device as claimed in claim 1 is characterized in that, described policy control device comprises:
Data processor connects OSS OSS, is used for obtaining from described OSS OSS the load data of described base station sub-system, and described load data is carried out data cleansing and loading index calculating, draws the data computation result;
Memory is used for the described predetermined strategy of storage and described preset trigger condition;
Trigger connects described data processor and described memory, is used for obtaining described strategy after the described data computation result that will receive and described predetermined strategy trigger condition compare, and with described policy distribution;
Dispensing device connects described trigger, is used for receiving and described strategy, and described strategy is sent to described network element.
3. policy control device as claimed in claim 2 is characterized in that,
Also comprise the user service information database, connect described trigger, be used to described trigger that user service information is provided;
Described trigger also is used for obtaining described user service information according to described data computation result to described user service data storehouse, and generates described strategy according to described service-user information and described data computation result.
4. as claim 2 or 3 described policy control devices, it is characterized in that, also comprise:
Data-interface connects input data source, is used to described policy control device that reference data is provided, and described reference data is used to described policy control device to obtain distributing policy basis is provided.
5. policy control device as claimed in claim 1, it is characterized in that, described load data is all indicated acquisition time when being acquired, this described load data that has time attribute is used for producing described real-time policy according to described trigger condition generation strategy tabulation by described Policy List.
6. policy control device as claimed in claim 5, it is characterized in that, the described described load data that has time attribute also is used for according to prediction result described base station sub-system being carried out strategy adjustment by the load estimation of prediction algorithm realization to the following scheduled time.
7. a policy control method is characterized in that, comprising:
Obtain the load data of base station sub-system, and described load data is handled, obtain result;
Described result and predetermined strategy trigger condition are compared, obtain comparative result;
Trigger corresponding strategy according to described comparative result, and corresponding strategy is implemented Flow Control by network element to described base station sub-system handle.
8. policy control method as claimed in claim 7 is characterized in that, described load data is all indicated the time of collection when being gathered,
Obtain the load data of base station sub-system, and described load data handled, obtain the result step and comprise:
Described load data is carried out data cleansing and loading index calculating, generate the loading index time list;
Described load data and predetermined strategy trigger condition are compared, obtain the comparative result step and comprise:
Described loading index time list and described predetermined strategy trigger condition are compared, draw the Policy List under each time period.
9. policy control method as claimed in claim 8 is characterized in that, is triggering corresponding strategy according to described comparative result, and described strategy is also comprised after the Flow Control treatment step described base station sub-system is implemented by network element:
Obtain the load sequence of each historical time according to described loading index time list;
Calculate the load information of following identical time in advance according to the load sequence of described historical time, be used for described base station sub-system is carried out strategy adjustment.
10. policy control method as claimed in claim 7 is characterized in that, is triggering corresponding strategy according to described comparative result, and corresponding strategy is also comprised after the Flow Control treatment step described base station sub-system is implemented by network element:
Judge whether corresponding strategy relates to user's business information, and obtain judged result;
Be corresponding strategy when relating to described user's business information in described judged result, obtain described user's business information by the user service information database.
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| CN105099736A (en) * | 2014-05-09 | 2015-11-25 | 中国移动通信集团北京有限公司 | Network control policy adjusting method and apparatus |
| CN107291389A (en) * | 2017-06-16 | 2017-10-24 | 郑州云海信息技术有限公司 | The method and apparatus that a kind of storage strategy intelligent trigger is performed |
| CN112925648A (en) * | 2021-03-25 | 2021-06-08 | 支付宝(杭州)信息技术有限公司 | Service policy issuing method and device |
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| CN105099736A (en) * | 2014-05-09 | 2015-11-25 | 中国移动通信集团北京有限公司 | Network control policy adjusting method and apparatus |
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| CN112925648B (en) * | 2021-03-25 | 2024-01-12 | 支付宝(杭州)信息技术有限公司 | Business strategy issuing method and device |
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| CN103260193B (en) | 2016-08-10 |
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