CN101360319A - Resource reservation method and apparatus based on traffic - Google Patents
Resource reservation method and apparatus based on traffic Download PDFInfo
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- CN101360319A CN101360319A CNA2007101196936A CN200710119693A CN101360319A CN 101360319 A CN101360319 A CN 101360319A CN A2007101196936 A CNA2007101196936 A CN A2007101196936A CN 200710119693 A CN200710119693 A CN 200710119693A CN 101360319 A CN101360319 A CN 101360319A
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Abstract
The invention discloses a resource reserving method based on service volume, which includes following steps: establishes at least one set according to the prior D day`s service volume before the nth time span of the (D+1)th day to be forecasted and the prior (n-1)th time span`s service volume of the (D+1)th day; and then divides all the service volume in each set into at least one category; then forecasts the resource needed in the nth time span of the (D+1)th day to be forecasted according to the category; and finally, reserves the resource according to the forecasted result. The invention also discloses a resource reserving device based on service volume, which includes a construction module, a classification module and a forecast module. Through the method and the device, the invention can realize reasonable resource reservation, therefore can reduce the session switch dropping rate and farthest improve the throughput of the system.
Description
Technical field
The present invention relates to the communications field, the resource reservation technology in the communications field refers in particular to a kind of method for obligating resource and device based on traffic carrying capacity.
Background technology
Method for obligating resource is a kind ofly to be suggested very early, uses also access control scheme the most widely.Single business network environment in early days promptly only transmits in the network in a kind of network environment of business, and system need reserve certain resource and give the switching session, is lower than certain level with the switching session cutting off rate of guaranteeing system.
In traditional resource reservation policy, the number of resource reservation determines before system starts working, and do not change with the fluctuation of network traffic, thereby this strategy is also referred to as the static resource reservation policy, can abbreviate static policies as.Although static policies is easy to realize that along with the development of mobile service, this strategy has been difficult to effectively distribute the air interface resource of growing tension, can't satisfy the Quality of Service demand of multiple business.Therefore, the resource reservation number can be considered to one of important technology in the future broadband wireless communication systems RRM with the dynamic resource reservation strategy of network environment dynamic change, and the various access control schemes of reserving based on resource dynamic are also proposed in succession.
The dynamic resource reservation strategy that proposes is broadly divided into two classes at present: cooperation policy and non-cooperation policy.Wherein, cooperation policy also can be referred to as distributed strategy, and non-cooperation policy also can be referred to as local policy.
The basic thought of cooperation policy is: when ongoing business in the home cell may move to the sub-district adjacent with home cell or other sub-districts on user's mobile alignment, for avoiding user's dropped calls, sub-district in the system each other can be by exchanging cell business information (as the business load situation, user's mobility information etc.) determine the number of resource reservation, to realize optimum access control.
Compare with cooperation policy, each sub-district in the non-cooperation policy does not need to collect the business information of other sub-districts, and the business information of only gathering this sub-district is used for determining the number of resource reservation.Generally speaking, non-cooperation policy can be divided into two classes again: interactive strategy and prediction type strategy.Interactive strategy is dynamically adjusted the number of resource reservation mainly according to result's (as cutting off rate, the changing condition of blocking rate) of nearest access control.Early stage dynamic resource reservation technology belongs to interactive strategy mostly.The number of resource reservation is obtained and adjusted in advance to the prediction type strategy then mainly by supposition business model or utilization forecast model,, to satisfy professional QoS demand.But in the existing prediction type strategy, the model of being supposed just proposes for the ease of mathematical analysis usually, and there is a big difference with application scenarios in the real system, so these prediction type strategies effect in actual applications is all undesirable.
Summary of the invention
In view of this, having proposed a kind of method for obligating resource and device based on traffic carrying capacity in the embodiments of the invention, is that new business is reserved rational resource thereby can make system.
For achieving the above object, the technical scheme in the embodiment of the invention is achieved in that
A kind of method for obligating resource based on traffic carrying capacity, this method may further comprise the steps:
A, construct at least one set according to preceding D days traffic carrying capacity before D+1 days n the time period to be predicted; Described D, n are natural number;
B, with above-mentioned each the set in all traffic carrying capacitys be divided at least one class;
C, n required resource of time period predicting to be predicted D+1 days according to described class;
D, according to the reserved resource that predicts the outcome.
Embodiments of the invention also provide a kind of device of the resource reservation based on traffic carrying capacity, and this device comprises: constructing module, sort module, prediction module and resource reservation module;
Described constructing module is used for according to received traffic information construction set, and the set of constructing is sent to described sort module;
Described sort module is used for the traffic carrying capacity of received set is classified, and will gather with classification results to send to described prediction module;
Described prediction module is used for calculating and predicting according to received set and classification results the resource of time period to be predicted, and will predict the outcome sends to described resource reservation module;
Described resource reservation module is exported the information of reserved resource according to the reserved resource that predicts the outcome that receives.
In summary, a kind of method for obligating resource and device based on traffic carrying capacity is provided in the embodiments of the invention, this method can be according to preceding D days traffic carrying capacity, determine the reserved resource quantity of D+1 days n time period, thereby by rational resource reservation, reduce and switch the session cutting off rate, improve throughput of system to greatest extent.
The method for obligating resource method based on traffic carrying capacity that is provided in the embodiment of the invention does not rely on concrete business generation Mathematical Modeling, is easy to application of practical project; And pattern classification related in this method is calculated, and can carry out during as morning in system's free time, can make full use of the computational resource of system; In addition, owing to also used clustering algorithm in this method with self-learning function, so this method has self-learning function, can follow the tracks of the slow variation of professional emergence pattern.
Description of drawings
Fig. 1 is the flow chart based on the method for obligating resource of traffic carrying capacity in the embodiment of the invention.
Fig. 2 is the resource reservation schematic representation of apparatus based on traffic carrying capacity in the embodiment of the invention.
Embodiment
For making the purpose, technical solutions and advantages of the present invention express clearlyer, the present invention is further described in more detail below in conjunction with drawings and the specific embodiments.
A kind of method for obligating resource and device based on traffic carrying capacity is provided in the embodiments of the invention, and this method can be determined the reserved resource quantity of D+1 days n time period according to preceding D days traffic carrying capacity.Affiliated traffic carrying capacity comprises data messages such as data traffic, channel utilization rate or traffic load; Described resource comprises the resource of various physics such as air interface resource in bandwidth resources, channel resource, code channel resource or the wireless system in the wired system, time interval resource or non-physics.
Fig. 1 is the flow chart based on the method for obligating resource of traffic carrying capacity in the embodiment of the invention.As shown in Figure 1, the method for obligating resource in the embodiment of the invention may further comprise the steps:
Specifically, can be with the minor time slice Δ t=24/N that all was divided into N equal in length in 24 hours of every day, and the traffic carrying capacity that system produced in i days j time period is designated as x
I, j(i=1,2 ..., D+1; J=1,2 ..., N), wherein D is the known fate that business takes place.Under the situation of all traffic carrying capacitys before n the known D+1 days time period, can be with all traffic carrying capacity x of preceding D days
I, jBe divided into N set, and with the traffic carrying capacity that takes place of time period of synchronization every day, promptly above-mentioned before all traffic carrying capacity x of D days
I, jIn the identical traffic carrying capacity x of subscript j
I, jForm a set.For example, when j=5, then can gather Y
5={ x
I, 5}={ x
1,5, x
2,5, x
3,5..., x
D, 5, be total to D element (being traffic carrying capacity).The rest may be inferred, can obtain N set, is designated as:
Y
j＝{x
i，j|1≤i≤D}，j＝1，2，…，N
Wherein, above-mentioned D, N, n is natural number.
Specifically, can use some clustering algorithms, k-means clustering algorithm etc. for example is respectively with each set Y
jInterior all elements x
I, jBe divided into C
jIndividual class, and use Z
J, cExpression set Y
jInterior C
jC class in the individual class, j=1 wherein, 2 ..., N, c=1,2 ..., C
jFor example, can be with the set Y that forms by the traffic carrying capacity that is taken place in every day the 3rd time period
3Interior all elements x
I, 3Be divided into C
3Individual class, wherein Z
3,1Expression set Y
3Interior C
3The 1st class in the individual class.
After the classification in the step 102, the time period to be predicted, promptly D+1 days n time period is interior with the traffic carrying capacity x that takes place
D+1, nBelong to set Y
nInterior C
nC class Z in the individual class
N, cProbability p
N, cCan calculate with following formula:
Wherein, | Z
N, c| represent above-mentioned C
nC class Z in the individual class
N, cIn the number of contained element.
In addition, can also use the k nearest neighbor algorithm in the clustering algorithm to calculate above-mentioned class Z
N, cIn the probability density function f that distributes of each element (being traffic carrying capacity)
N, c(x), c=1,2 ..., C
nWherein, x is set Y
nIn be divided into class Z
N, cIn element, i.e. traffic carrying capacity; Probability density function f
N, c(x) expression traffic carrying capacity x is at set Y
nC class Z
N, cThe middle probability that occurs.
Owing to exist relatedly between the traffic carrying capacity of current time and next traffic carrying capacity constantly, therefore can gather and set up this association, thereby carry out the study of service feature by constructing the period time delay.So, to each set Z
N, c, can construct corresponding period time delay set H
N, cThe definition element x
I, nPeriod time delay operator T as follows: Tx
I, n=x
I, n-1, H then
N, c={ Tx
I, n| x
I, n∈ Z
N, c}=Z
N-1, c, that is to say H
N, cIn element belong to Z by all
N, cThe element of element in the pairing previous period constitute.Wherein, time delay operator T is the function of n, changes along with the variation of n; In addition, when n=1, x
I, n-1=x
I, 0The traffic carrying capacity of representing last time period of i-1 days.
Use the k nearest neighbor algorithm to estimate H
N, cIn data distribute, can obtain H
N, cThe probability density function g that middle element distributes
N, c(x), c=1,2 ..., C
nWith Z
N, cProbability density function f
N, c(x) similar, g
N, c(x) expression traffic carrying capacity x is at set H
N, cThe middle probability that occurs.
Therefore, can be to contingent traffic carrying capacity x in D+1 days n time period
D+1, nThe class that may belong to is predicted, promptly judges traffic carrying capacity x
D+1, nMay belong to which class Z
N, cWhen carrying out above-mentioned prediction, can adopt different criterions, for example the minimum error probability criterion is carried out, and therefore can get:
Wherein, x
D+1, n-1Be illustrated in the traffic carrying capacity of generation of D+1 days n-1 time period,
Expression is from C
nSelect in the individual class and make p
N, cg
N, c(x
D+1, n-1) the class of numerical value maximum, arg is a kind of oeprator, expression satisfies condition
The set of numbering c of class.Because above-mentioned condition is to get maximum numbering c, therefore have only the numbering c of a class in this set, and the value of this c can be given the variable on the equal sign left side by the equal sign assignment
Therefore, according to following formula as can be known, traffic carrying capacity x
D+1, nBelong to class
Learning traffic carrying capacity x
D+1, nAffiliated class is
After, can be according to the probability density function in such
And the maximum that the session call drop takes place allows probability r
Drop, obtain the premeasuring x of D+1 days n time period resource requirement
D+1, n p, the value of this premeasuring can be calculated by following formula:
Wherein,
Expression: select the numerical value a of a minimum, make this numerical value a to satisfy condition:
Therefore, above-mentioned numerical value a is and can makes that the session probability of call takes place to be lower than the maximum that the session call drop takes place and to allow probability r
DropThe minimal service amount; In addition, arg is a kind of oeprator, and expression satisfies condition
The set of a.Because above-mentioned condition is to get minimum numerical value a, therefore has only an a in this set, and the value of this a can be given the premeasuring x of D+1 days n the time period resource requirement on the equal sign left side by the equal sign assignment
D+1, n p
The method of above-mentioned resource reservation can be at the business with high priority, for example service switchover.Can use the resource of the method for above-mentioned resource reservation as the business reservation respective numbers of high priority.After finishing above-mentioned resource reservation, if new service needed connecting system is arranged, judge at first then whether this new business is high-priority service, if high-priority service, then as long as have enough resources can satisfy the demand of this new business in the system, then will this new service access, otherwise refusal will this new service access; If this new business is low priority traffice, then except reserved resource, as if also having enough resources can satisfy the demand of this new business in the system, then will this new service access, otherwise refusal will this new service access.
Certainly, the method for above-mentioned resource reservation can be used for the business of non-high priority too, and the method that promptly also can use above-mentioned resource reservation is the resource that the business of non-high priority is reserved respective numbers.
Fig. 2 is the resource reservation schematic representation of apparatus based on traffic carrying capacity in the embodiment of the invention.As shown in Figure 2, the resource reservation device 200 in the embodiment of the invention comprises: constructing module 201, sort module 202, prediction module 203 and resource reservation module 204.Described constructing module 201 is connected with sort module 202, is used to receive the traffic information of extraneous input, and according to received traffic information construction set, will construct good set then and send to sort module 202; Sort module 202 is connected with 203 with constructing module 201 respectively, is used to receive the set that constructing module sends, and the element in the received set (being traffic carrying capacity) is classified, and will gather and classification results sends to prediction module 203; Prediction module 203 is connected with resource reservation module 204 with sort module 202 respectively, is used for calculating and predicting according to received set and classification results the resource of time period to be predicted, and will predict the outcome sends to resource reservation module 204; Resource reservation module 204 is used for according to the reserved resource that predicts the outcome that receives, the information of output reserved resource, and system finishes resource reservation according to the information of reserved resource.
Wherein, above-mentioned constructing module 201 also comprises: the time period is divided module 205 and set constructing module 206.The described time period is divided module 205, is used for the time period that was divided into N equal in length in 24 hours with every day, will divide the result time period and send to described set constructing module 206; Described set constructing module 206 is used for dividing result and traffic information construction set according to the received time period, and the set of constructing is sent to described sort module 202.
Above-mentioned sort module 202 also comprises: cluster module 207 and time delay module 208.Described cluster module 207, all traffic carrying capacitys of each set that is used for will receiving according to clustering method are divided at least one class, described time delay module 208 and prediction module 203 when classification results is sent to; Described time delay module 208, be used for according to the classification results that receives with the set under the previous time period of time period to be predicted carry out with the time period to be predicted under the identical classification of set, classification results is sent to prediction module 203.
Above-mentioned prediction module 203 also comprises: computing module 209, class prediction module 210 and resources module 211.Described computing module 209, be used for calculating the time period to be predicted the traffic carrying capacity that takes place is belonged to second probability that each traffic carrying capacity occurs in first probability of each class in the set under time period to be predicted and each class in the pairing set of previous time period of time period to be predicted according to the classification results that receives; First probability and second probability are sent to described class prediction module 210; Described class prediction module 210 is used for according to the class under first probability that receives and the traffic carrying capacity of second probabilistic forecasting time period to be predicted; To predict the outcome and send to resources module 211; Described resources module 211 is used for needing reserved resource according to the forecasting institute that predicts the outcome that receives, and the required reserved resource of predicting is sent to resource reservation module 204.
The above is preferred embodiment of the present invention only, is not to be used to limit protection scope of the present invention.Within the spirit and principles in the present invention all, any modification of being done, be equal to replacement, improvement etc., all should be included within protection scope of the present invention.
Claims (11)
1, a kind of method of the resource reservation based on traffic carrying capacity is characterized in that this method may further comprise the steps:
A, construct at least one set according to preceding D days traffic carrying capacity before D+1 days n the time period to be predicted; Described D, n are natural number;
B, with above-mentioned each the set in all traffic carrying capacitys be divided at least one class;
C, n required resource of time period predicting to be predicted D+1 days according to described class;
D, according to the reserved resource that predicts the outcome.
2, method according to claim 1 is characterized in that, described steps A comprises:
A1, will be divided into every day, described N is a natural number time period of N equal in length;
A2, with preceding D days traffic carrying capacity x before D+1 days n the time period to be predicted
I, jBe divided into N set, i=1 wherein, 2 ..., D, j=1,2 ..., N; With above-mentioned all traffic carrying capacity x
I, jIn, the identical same time period traffic carrying capacity of subscript j is as same set.
3, method according to claim 1 is characterized in that, described step B comprises:
According to clustering method all traffic carrying capacitys in each set are divided at least one class; According to clustering method with the set under n-1 time period carry out with n time period under the identical classification of set.
4, method according to claim 1 is characterized in that, described step C comprises:
The class that the traffic carrying capacity of C1, prediction n time period of D+1 days to be predicted is affiliated;
C2, according to the affiliated class of described prediction, predict to be predicted D+1 days n required reserved resource of time period.
5, method according to claim 4 is characterized in that, described step C1 comprises:
C11, calculate D+1 days n the time period to be predicted and the traffic carrying capacity that takes place is belonged to first probability of gathering each interior class under n time period;
C12, calculating are gathered second probability that each traffic carrying capacity occurs in each interior class under n-1 time period;
C13, according to the class under described first probability and second probabilistic forecasting traffic carrying capacity of D+1 days n time period to be predicted.
6, method according to claim 4 is characterized in that, to be predicted D+1 days n required reserved resource of time period of prediction described in the step C2 is:
Satisfy condition
The traffic carrying capacity a of minimum; Wherein, r
DropFor the maximum that the session call drop takes place allows probability;
The affiliated class of traffic carrying capacity of representing D+1 days n the time period to be predicted
In the probability density function of each traffic carrying capacity.
7, method according to claim 5 is characterized in that, step C13 comprises:
C131, according to described first probability and second probability, calculate the product of two probability;
C132, the pairing class of maximum product that step C131 is calculated are as the class under the traffic carrying capacity of D+1 days n time period to be predicted.
8, a kind of device of the resource reservation based on traffic carrying capacity is characterized in that this device comprises: constructing module, sort module, prediction module and resource reservation module;
Described constructing module is used for according to received traffic information construction set, and the set of constructing is sent to described sort module;
Described sort module is used for the traffic carrying capacity of received set is classified, and will gather with classification results to send to described prediction module;
Described prediction module is used for calculating and predicting according to received set and classification results the resource of time period to be predicted, and will predict the outcome sends to described resource reservation module;
Described resource reservation module is exported the information of reserved resource according to the reserved resource that predicts the outcome that receives.
9, device according to claim 8 is characterized in that, described constructing module comprises: the time period is divided module and set constructing module;
The described time period is divided module, is used for and will be divided into the time period of N equal in length every day, will divide the result time period and send to described set constructing module;
Described set constructing module is used for dividing result and traffic information construction set according to the received time period, and the set of constructing is sent to described sort module.
10, device according to claim 8 is characterized in that, described sort module comprises: cluster module and time delay module;
Described cluster module, all traffic carrying capacitys of each set that is used for will receiving according to clustering method are divided at least one class, described time delay module and prediction module when classification results is sent to;
Described time delay module, be used for according to the classification results that receives with the set under the previous time period of time period to be predicted carry out with the time period to be predicted under the identical classification of set, classification results is sent to prediction module.
11, device according to claim 8 is characterized in that, described prediction module comprises: computing module, class prediction module and resources module;
Described computing module, be used for calculating the time period to be predicted the traffic carrying capacity that takes place is belonged to second probability that each traffic carrying capacity occurs in first probability of each class in the set under time period to be predicted and each class in the pairing set of previous time period of time period to be predicted according to the classification results that receives; First probability and second probability are sent to described class prediction module;
Described class prediction module is used for according to the class under first probability that receives and the traffic carrying capacity of second probabilistic forecasting time period to be predicted; To predict the outcome and send to the resources module;
Described resources module is used for needing reserved resource according to the forecasting institute that predicts the outcome that receives, and the required reserved resource of predicting is sent to the resource reservation module.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2013004013A1 (en) * | 2011-07-06 | 2013-01-10 | Empire Technology Development Llc | Data usage forecast of mobile network |
| CN105472631A (en) * | 2014-09-02 | 2016-04-06 | 中兴通讯股份有限公司 | Service data quantity and/or resource data quantity prediction method and prediction system |
| CN109934657A (en) * | 2017-12-19 | 2019-06-25 | 中国移动通信集团河北有限公司 | Processing method, device, equipment and the medium of business datum |
| CN111147395A (en) * | 2019-12-25 | 2020-05-12 | 中国联合网络通信集团有限公司 | Network resource adjusting method and device |
| CN112737798A (en) * | 2019-10-14 | 2021-04-30 | 中国移动通信集团四川有限公司 | Host resource allocation method and device, scheduling server and storage medium |
| WO2021147717A1 (en) * | 2020-01-20 | 2021-07-29 | 维沃移动通信有限公司 | Resource reservation method and terminal |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| EP1124950B1 (en) * | 1998-10-26 | 2006-07-12 | Avi Biopharma, Inc. | Morpholino based p53 antisense oligonucleotide, and uses thereof |
| KR100424651B1 (en) * | 2002-04-11 | 2004-03-25 | 삼성전자주식회사 | Data communication method using resource reservation |
| CN100384299C (en) * | 2005-05-10 | 2008-04-23 | 北京交通大学 | Resource reservation intelligent call admission control method and apparatus |
| EP1884086B1 (en) * | 2005-05-24 | 2018-11-21 | Cisco Technology, Inc. | System and method for providing bandwidth reservations in a resource reservation setup protocol, rsvp, environment |
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Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2013004013A1 (en) * | 2011-07-06 | 2013-01-10 | Empire Technology Development Llc | Data usage forecast of mobile network |
| US8600346B2 (en) | 2011-07-06 | 2013-12-03 | Empire Technology Development Llc | Data usage forecast of mobile network |
| CN103650555A (en) * | 2011-07-06 | 2014-03-19 | 英派尔科技开发有限公司 | Data usage forecast of mobile network |
| CN103650555B (en) * | 2011-07-06 | 2015-05-06 | 英派尔科技开发有限公司 | Data usage forecast of mobile network |
| CN105472631A (en) * | 2014-09-02 | 2016-04-06 | 中兴通讯股份有限公司 | Service data quantity and/or resource data quantity prediction method and prediction system |
| CN109934657A (en) * | 2017-12-19 | 2019-06-25 | 中国移动通信集团河北有限公司 | Processing method, device, equipment and the medium of business datum |
| CN112737798A (en) * | 2019-10-14 | 2021-04-30 | 中国移动通信集团四川有限公司 | Host resource allocation method and device, scheduling server and storage medium |
| CN112737798B (en) * | 2019-10-14 | 2022-09-27 | 中国移动通信集团四川有限公司 | Host resource allocation method and device, scheduling server and storage medium |
| CN111147395A (en) * | 2019-12-25 | 2020-05-12 | 中国联合网络通信集团有限公司 | Network resource adjusting method and device |
| CN111147395B (en) * | 2019-12-25 | 2022-05-24 | 中国联合网络通信集团有限公司 | Network resource adjusting method and device |
| WO2021147717A1 (en) * | 2020-01-20 | 2021-07-29 | 维沃移动通信有限公司 | Resource reservation method and terminal |
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| CN101360319B (en) | 2011-07-20 |
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