CN103607737B - A kind of heterogeneous-network service shunt method and system - Google Patents

Abstract

The present invention provides a kind of heterogeneous-network service shunt method and system, including: receive the service requesting information of multimode terminal；Each of the links in heterogeneous network is carried out information detection, periodically obtains each of the links buffer area queuing long message and data packet number；According to each of the links buffer area queuing long message being periodically obtaining and data packet number, determine the service distributing ratio of each of the links；Service distributing ratio according to described each of the links, periodically carries out service distributing.The present invention can not only periodically obtain the business feedback in each of the links buffer area, can also be by the information integration that detected to theoretical model, thus the dynamic bind of the shunting decision-making technique of realization theory and engineering practice, improve accuracy and the initiative of shunt method.

Description

A kind of heterogeneous-network service shunt method and system

Technical field

The present invention relates to wireless technical field, particularly relate to a kind of heterogeneous-network service shunt method and system.

Background technology

Along with the blowout formula of multimedia service increases and the diversity change of user's request class of business, rely on unitary system The network of formula provides a user with data, services it cannot be guaranteed that user is in all demands of the aspect such as handling capacity, time delay.Simultaneously Due to the development of radio network technique, the fusion between heterogeneous network and cooperative transmission are no matter in theoretical research or work In journey practice, all have been achieved for some achievements.Isomery merges will become the main trend of next generation wireless communication network, 2G, 3G and 4G network the situation deposited have preliminarily formed, and this will cause same geographic area to be covered by multiple heterogeneous subnet.

Along with the evolution of terminal technology develops, multiple heterogeneous network can be concurrently accessed and receive and send the multimode of data Terminal is the most commercial.Therefore in future soon, in order to promote network efficiency and ensure the business experience of user, network is transported Battalion business is when providing the user business service, it may be necessary to transmit data from multiple heterogeneous networks simultaneously.In this course, The service distributing ratio how distributed between each heterogeneous network will be determined by the Diffluence Algorithm in shunting server, and this is whole The core of separate system, the service quality (QoS) of the efficiency and user that directly affect business transmission is experienced.

In the heterogeneous network separate system currently existed, there are some achievements with in engineering in theory.Theory is ground On studying carefully, Business Stream transmission in a network is modeled as into general queueing theory, minimizing as optimization aim using network delay Set up Optimized model, solve the optimum shunt ratio drawing heterogeneous networks.The method determines whole business from the beginning and passes Shunt ratio in defeated flow process, by trying to achieve the optimal transmission solution of whole transmitting procedure to the abstract approximate modeling of wireless channel； And in engineering, use configuration information collection and feedback node in a network, periodically to shunting server feedback business transmission Situation, including time delay, packet loss etc., for the state of shunting server judgement each heterogeneous network current, and then formulates rational industry Business shunting decision-making.The method does not has strict theoretical foundation, relies on the real-time network information obtained be analyzed and adjudicate.

As can be seen here, heterogeneous network separate system of the prior art, either it is also based on engineering in fact based on theoretical Trample, all come with some shortcomings: separate system based on theoretical research lacks the dynamically adapting to real system, real based on engineering The separate system trampled then lacks certain theoretical foundation, and prior art cannot accomplish the effective combination of the two, it is impossible to meet simultaneously The accuracy of shunting decision-making and the requirement of initiative.

Summary of the invention

(1) to solve the technical problem that

The present invention provides a kind of heterogeneous-network service shunt method and system, to solve in prior art, it is impossible to will be based on The technical problem that in theoretical and based on engineering practice shunting decision-making technique, accuracy and initiative effectively combine.

(2) technical scheme

For solving above-mentioned technical problem, the present invention provides a kind of heterogeneous-network service shunt method, including:

Receive the service requesting information of multimode terminal；

Each of the links in heterogeneous network is carried out information detection, periodically obtains each of the links buffer area queuing long message And data packet number；

According to each of the links buffer area queuing long message being periodically obtaining and data packet number, determine each of the links Service distributing ratio；

Service distributing ratio according to described each of the links, periodically carries out service distributing.

Further, each of the links buffer area queuing long message that described basis is periodically obtaining and data packet number, Determine that the service distributing ratio of each of the links includes:

Queue up long message l by each of the links_nLong threshold value L of queuing up with link compares, and determines the service speed μ of each of the links_n, n For the number of links in heterogeneous network；

Data packet number m according to each of the links being periodically obtaining_n, extract each of the links and be in long threshold value L of queuing Time data packet number m_nL；

Service speed μ according to each of the links_nWith the data packet number m being in when queuing up long threshold value L_nL, obtain every chain The packet delay D on road_n；

According to minimizing the principle of system delay, determine the service distributing ratio of each of the links.

Further, described long message l that each of the links is queued up_nLong threshold value L of queuing up with link compares, and determines each of the links Service speed μ_nIncluding:

Profit determines the service speed μ of each of the links with the following method_n:

${\mathrm{\&mu;}}_n=\left\{\begin{array}{cc}{\mathrm{\&mu;}}_{\mathrm{nl}}& {\mathrm{ifl}}_n<L\\ {\mathrm{\&mu;}}_{\mathrm{nm}}& \mathrm{otherwise}\end{array}\right.;$

Wherein μ_nlFor the service speed higher limit of this link, μ_nmService speed lower limit for this link.

Further, the described service speed μ according to each of the links_nWith the data packet number being in when queuing up long threshold value L m_L, obtain the packet delay D of each of the links_nIncluding:

When this link is long-term evolving network link,Wherein λ_nFor the arrival rate of this link, i.e. It is λ that this link traffic stream obeys parameter_nPoisson flow；

When this link be long-term evolving network through WLAN conversion link time,

$D_n=D_n^{\mathrm{WLAN}}+D_n^{\mathrm{LTE}},$

WhereinFor considering the packet delay that WLAN interference flow causes,Wherein λ ' is the parameter of WLAN interference flow Poisson flow, μ '_nFor considering wireless local The arrival rate of this link after network interferences flow；

The average data packet delay caused for long-term evolving network:

$\begin{array}{c}\begin{array}{c}{D}_n^{\mathrm{LTE}}={(\frac{1-{\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right)}^{m_{\mathrm{nL}}+1}}{1-\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nL}}}\right)}+\frac{{\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right)}^{m_{\mathrm{nL}}}\&CenterDot;\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{um}}}}{1-\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nm}}}\right)})}^{-1}\&CenterDot;\{\frac{\left(\frac{1}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right)(1+(m_{\mathrm{nL}}-1){\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right)}^{m_{\mathrm{nL}}}-m_{\mathrm{nL}}{\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right)}^{m_{\mathrm{nL}}-1})}{{(1-\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right))}^2}\\ +\frac{{\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right)}^{m_{\mathrm{nL}}-1}(m_{\mathrm{nL}}-(m_{\mathrm{nL}}-1)\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nm}}}\right))}{{(1-\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nm}}}\right))}^2}\}\end{array}\end{array}$

Wherein λ_nFor this link arrival rate in long-term evolving network.

Further,

Described basis minimizes the principle of system delay, determines that the service distributing ratio of each of the links includes:

According to minimizing the principle of system delay, solve following optimization problem:MakeAnd it is full 0≤λ in foot long-term evolving network link_n≤μ_n, long-term evolving network is 0≤λ in WLAN conversion link_n<min (μ_n,μ_n')-λ ', wherein λ is the parameter of total service traffics Poisson flow, vector

The described service distributing ratio according to described each of the links, periodically carries out service distributing and includes: according to obtained The service distributing ratio of each of the links, periodically carry out service distributing.

On the other hand, the present invention also provides for a kind of heterogeneous-network service separate system, including: the service request being linked in sequence Receiver module, information detection module, shunting decision-making module and flow-dividing control module, wherein:

Service request receiver module, for receiving the service requesting information of multimode terminal, then solicited message detecting module Carry out information detection；

Information detection module, for each of the links in heterogeneous network carries out information detection, periodically obtains every chain Road buffer area queuing long message and data packet number, be sent to shunt decision-making module；

Shunting decision-making module, for according to each of the links buffer area queuing long message being periodically obtaining and number-of-packet Amount, determines the service distributing ratio of each of the links, and result is sent to flow-dividing control module；

Flow-dividing control module, for the service distributing ratio according to described each of the links, periodically carries out service distributing.

Further, described shunting decision-making module includes:

Parameter adjustment submodule, for the long message l that each of the links queued up_nLong threshold value L of queuing up with link compares, and determines every The service speed μ of bar link_n, n is the number of links in heterogeneous network；

Packet extracts submodule, for the data packet number mn according to each of the links being periodically obtaining, extracts every Bar link is in data packet number m when queuing up long threshold value L_nL；

Delay computing submodule, for the service speed μ according to each of the links_nWith the data being in when queuing up long threshold value L Bag quantity m_L, obtain the packet delay D of each of the links_n；

Decision-making submodule, minimizes the principle of system delay, determines the service distributing ratio of each of the links for basis.

Further, described parameter adjustment submodule includes:

Parameter recommendation unit, for utilizing equation below to determine the service speed μ of each of the links_n:

${\mathrm{\&mu;}}_n=\left\{\begin{array}{cc}{\mathrm{\&mu;}}_{\mathrm{nl}}& {\mathrm{ifl}}_n<L\\ {\mathrm{\&mu;}}_{\mathrm{nm}}& \mathrm{otherwise}\end{array}\right.;$

Wherein μ_nlFor the service speed higher limit of this link, μ_nmService speed lower limit for this link.

Further, described Delay computing submodule includes:

Long-term evolving network unit, is used for utilizing formulaObtain the packet of long-term evolving network link Postpone, wherein λ_nObeying parameter for the arrival rate of this link, i.e. this link traffic stream is λ_nPoisson flow；

WLAN retransmission unit, is used for utilizing formulaObtain long-term evolving network through nothing The packet delay of line LAN conversion link:

WhereinFor considering the packet delay that WLAN interference flow causes,

Wherein λ ' is the parameter of WLAN interference flow Poisson flow, μ '_nFor considering The arrival rate of this link after WLAN interference flow；

The average data packet delay caused for long-term evolving network:

$\begin{array}{c}\begin{array}{c}{D}_n^{\mathrm{LTE}}={(\frac{1-{\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right)}^{m_{\mathrm{nL}}+1}}{1-\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nL}}}\right)}+\frac{{\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right)}^{m_{\mathrm{nL}}}\&CenterDot;\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{um}}}}{1-\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nm}}}\right)})}^{-1}\&CenterDot;\{\frac{\left(\frac{1}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right)(1+(m_{\mathrm{nL}}-1){\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right)}^{m_{\mathrm{nL}}}-m_{\mathrm{nL}}{\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right)}^{m_{\mathrm{nL}}-1})}{{(1-\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right))}^2}\\ +\frac{{\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right)}^{m_{\mathrm{nL}}-1}(m_{\mathrm{nL}}-(m_{\mathrm{nL}}-1)\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nm}}}\right))}{{(1-\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nm}}}\right))}^2}\}\end{array}\end{array}$

Wherein λ_nFor this link arrival rate in long-term evolving network.

Further,

Described decision-making submodule includes: optimize unit, minimizes the principle of system delay for basis, solves following optimization Problem:MakeAnd meet 0≤λ in long-term evolving network link_n≤μ_n, long-term evolving network is through nothing 0≤λ in line LAN conversion link_n<min(μ_n,μ_n')-λ ', wherein λ is the parameter of total service traffics Poisson flow, vector

$\stackrel{\&RightArrow;}{\mathrm{\&lambda;}}=({\mathrm{\&lambda;}}_1,{\mathrm{\&lambda;}}_2,\&CenterDot;\&CenterDot;\&CenterDot;,{\mathrm{\&lambda;}}_n);$

Described flow-dividing control module includes: shunting submodule, for the service distributing ratio according to obtained each of the links ExamplePeriodically carry out service distributing.

(3) beneficial effect

Visible, in a kind of heterogeneous-network service shunt method and system of present invention proposition, can not only be periodically Obtain the business feedback in each of the links buffer area, additionally it is possible to by the information integration that detected to theoretical model, thus real The dynamic bind of the existing theoretical shunting decision-making technique with engineering practice, improves accuracy and the initiative of shunt method.

It addition, invention introduces random disturbances possible in network, according to the periodically variable network information and parameter, Consider the disturbed condition in network, draw according to effective Diffluence Algorithm and reasonably shunt decision-making, further enhancing Adaptability to engineering practice.

Accompanying drawing explanation

In order to be illustrated more clearly that the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing In having technology to describe, the required accompanying drawing used is briefly described, it should be apparent that, the accompanying drawing in describing below is this Some bright embodiments, for those of ordinary skill in the art, on the premise of not paying creative work, it is also possible to root Other accompanying drawing is obtained according to these accompanying drawings.

Fig. 1 is the basic procedure schematic diagram of embodiment of the present invention heterogeneous-network service shunt method；

Fig. 2 is the schematic flow sheet of a preferred embodiment of the invention heterogeneous-network service shunt method；

Fig. 3 is the schematic diagram of embodiment of the present invention heterogeneous network shunting transmitting scene；

Fig. 4 is that embodiment of the present invention heterogeneous network shunts configuration diagram；

Fig. 5 is the basic structure schematic diagram of embodiment of the present invention heterogeneous-network service separate system；

Fig. 6 is the structural representation of a preferred embodiment of the invention heterogeneous-network service separate system；

Fig. 7 is the structural representation of a preferred embodiment of the invention heterogeneous-network service separate system；

Fig. 8 is the sequential chart of embodiment of the present invention heterogeneous-network service separate system agent structure.

Detailed description of the invention

For making the purpose of the embodiment of the present invention, technical scheme and advantage clearer, below in conjunction with the embodiment of the present invention In accompanying drawing, the technical scheme in the embodiment of the present invention is clearly and completely described, it is clear that described embodiment is The a part of embodiment of the present invention rather than whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art The every other embodiment obtained under not making creative work premise, broadly falls into the scope of protection of the invention.

First the embodiment of the present invention proposes a kind of heterogeneous-network service shunt method, sees Fig. 1, including:

Step 101: receive the service requesting information of multimode terminal.

Step 102: each of the links in heterogeneous network carries out information detection, periodically obtains each of the links buffer area row Team leader's information and data packet number.

Step 103: according to each of the links buffer area queuing long message being periodically obtaining and data packet number, determines every The service distributing ratio of bar link.

Step 104: according to the service distributing ratio of described each of the links, periodically carries out service distributing.

Visible, in a kind of heterogeneous-network service shunt method that the embodiment of the present invention proposes, can not only be periodically Obtain the business feedback in each of the links buffer area, additionally it is possible to by the information integration that detected to theoretical model, thus real The dynamic bind of the existing theoretical shunting decision-making technique with engineering practice, improves accuracy and the initiative of shunt method.

In one embodiment of the invention, it is preferable that queue up according to each of the links buffer area being periodically obtaining long Information and data packet number, determine that the service distributing ratio of each of the links may include steps of:

Queue up long message l by each of the links_nLong threshold value L of queuing up with link compares, and determines the service speed μ of each of the links_n, n For the number of links in heterogeneous network；

Data packet number m according to each of the links being periodically obtaining_n, extract each of the links and be in long threshold value L of queuing Time data packet number m_nL；

Service speed μ according to each of the links_nWith the data packet number m being in when queuing up long threshold value L_nL, obtain every chain The packet delay D on road_n；

According to minimizing the principle of system delay, determine the service distributing ratio of each of the links.

In another embodiment of the present invention, when using queueing theory that heterogeneous network separate system is modeled, industry Business flow arrival rate λ represents, network availability bandwidth then utilizes service speed μ to represent.Ratio between λ and μ is referred to as Service intensity ρ, the size of this value directly has relation with the long l that queues up.That is, when network state is the best, μ value is less, causes service Intensity is big, then team leader l is the longest；Otherwise then team leader l is the least.This explanation, can be by detecting in each Long Term Evolution (LTE) link The size of the long l of queuing of business judges that current network state is the best, revises μ value according to different network states, from And realize the improvement to queuing system, make separate system that network state change is accomplished dynamically adapting.

To queuing up in long concrete detection process, can periodically send information detection instruction, according to each LTE link The feedback information of middle buffer area, obtains each of the links queuing long message l_n.As each of the links queuing long message l_nTime known, need Judge that network state corresponding to this team leader is the best, and according to different l_nAdjudicate rational μ value.Preferably, it is possible to use Following method determines the service speed μ of each of the links_n:

${\mathrm{\&mu;}}_n=\left\{\begin{array}{cc}{\mathrm{\&mu;}}_{\mathrm{nl}}& {\mathrm{ifl}}_n<L\\ {\mathrm{\&mu;}}_{\mathrm{nm}}& \mathrm{otherwise}\end{array}\right.;$

Wherein μ_nlFor the service speed higher limit of this link, μ_nmService speed lower limit for this link.

Above formula determines long threshold value L of queuing up based on experience value, if the long l of queuing that detection obtains_nLess than this threshold value, Illustrate that current network state is good, then μ_nCapping value μ_nl, otherwise explanation current network state is bad, then take off limit value μ_nm.Logical Cross this way, so that Queueing Theory Method has a certain degree of adaptability to network time-varying characteristics.It should be noted that The analysis method of formula is also a kind of approximation, and the most accurately description can be greatly increased the complexity of computing, is unfavorable for engineer applied.

In another embodiment of the present invention, it is preferable that sharp can determine the packet of each of the links with the following method Postpone D_n:

For long-term evolving network link, produced packet delay is the packet delay directly transmitted via LTE, This part packet delay can be in the hope of by Li Teer law:

$D_n=\frac{1}{{\mathrm{\&mu;}}_n-{\mathrm{\&lambda;}}_n},$

Wherein λ_nObeying parameter for the arrival rate of this link, i.e. this link traffic stream is λ_nPoisson flow, namely adjacent two Individual packet arrives probability density function f (t) of system interval t, for parameter lambda_nQuantum condition entropy:

$f\left(t\right)={\mathrm{\&lambda;}}_n\&CenterDot;e^{{-\mathrm{\&lambda;}}_{n}t}.$

And for LTE network when the wlan network conversion link, produced packet delay need to consider LTE and The service speed of wlan network, is equivalent to same Business Stream through twice service and the delay of queuing:

Wherein for the delay that wlan network causes,Wherein λ ' is WLAN The parameter of interference flow Poisson flow,For the arrival rate of this link after consideration WLAN interference flow.

And for the delay that LTE network causes, due to its service speed time-varying, therefore the expression formula of average retardation can Think:

$\begin{array}{c}\begin{array}{c}{D}_n^{\mathrm{LTE}}={(\frac{1-{\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right)}^{m_{\mathrm{nL}}+1}}{1-\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nL}}}\right)}+\frac{{\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right)}^{m_{\mathrm{nL}}}\&CenterDot;\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{um}}}}{1-\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nm}}}\right)})}^{-1}\&CenterDot;\{\frac{\left(\frac{1}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right)(1+(m_{\mathrm{nL}}-1){\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right)}^{m_{\mathrm{nL}}}-m_{\mathrm{nL}}{\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right)}^{m_{\mathrm{nL}}-1})}{{(1-\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right))}^2}\\ +\frac{{\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right)}^{m_{\mathrm{nL}}-1}(m_{\mathrm{nL}}-(m_{\mathrm{nL}}-1)\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nm}}}\right))}{{(1-\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nm}}}\right))}^2}\}\end{array}\end{array}$

Wherein λ_nFor this link arrival rate in the lte networks.

Thus, the delay of the most all links all can be calculated.In order to determine the suitable shunt ratio of Business Stream, for For Queueing Theory Method, can be to minimize the main target of optimization postponed as queuing system.Another enforcement in the present invention In example, following optimization problem can be solved according to minimizing the principle of system delay:

$\underset{\underset{\mathrm{\&lambda;}}{\&RightArrow;}}{\min }\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{D}_i,$

MakeAnd meet 0≤λ in LTE network link_n≤μ_n, LTE network is in wlan network conversion link 0 ≤λ_n<min(μ_n,μ_n')-λ ', wherein λ is the parameter of total service traffics Poisson flow, vector

This constraints is that guarantee business arrival rate not can exceed that system service speed, is reflected in real network, i.e. The available total bandwidth of system can not be less than total portfolio, even if otherwise also cannot be ensured the business of user by fractionating system Experience.

Can be in the hope of the solution of the optimum service distributing ratio under current network state by solving above-mentioned optimization problem, Preferably, can be according to the service distributing ratio of obtained each of the links, periodically carry out service distributing.Namely according to This shunt ratio is used to carry out service distributing in next cycle, until carrying out the calculating in next one cycle and again dividing Join.

In below to shunt transmitting scene at a heterogeneous network, as a example by carrying out the concrete grammar shunted, describe in detail The embodiment of the present invention realize process, such as Fig. 2.

Fig. 3 show the basic scene of heterogeneous network shunting transmission, comprises a shunting server, LTE base station and LTE net Network, WLAN AP node and wlan network, multiple multimode terminals and interfered with terminal.Transmitting scene is shunted for this heterogeneous network The process carrying out shunting includes:

Step 201: multimode terminal user 1 is to shunting server application business.

Step 202: shunting server sends confirmation request information to user 1.

Now, shunting server finds that user 1 can be concurrently accessed LTE network and wlan network, then proceed by business Shunting.

Step 203: shunting server carries out information detection to each of the links in heterogeneous network.

Step 204: shunting server periodically obtains each of the links buffer area queuing long message and data packet number.

In the embodiment of the present invention, when using queueing theory to be modeled heterogeneous network separate system, service traffics are used Reaching speed λ to represent, network availability bandwidth then utilizes service speed μ to represent.Ratio between λ and μ is referred to as service intensity ρ, The size of this value directly has relation with the long l that queues up.That is, when network state is the best, μ value is less, causes service intensity big, then team Long l is the longest；Otherwise then team leader l is the least.This explanation, can be come by the size detecting the long l of queuing of business in each LTE link Judge that current network state is the best, according to different network state revision μ values, thus realize queuing system is changed Enter, make separate system that network state change is accomplished dynamically adapting.

Step 205: the long message ln that each of the links queued up compares with long threshold value L of link queuing, determines the clothes of each of the links Business speed μ_n。

In this step, as each of the links queuing long message l_nTime known, need to judge that network state corresponding to this team leader is No well, and according to different l_nAdjudicate rational μ value:

${\mathrm{\&mu;}}_n=\left\{\begin{array}{cc}{\mathrm{\&mu;}}_{\mathrm{nl}}& {\mathrm{ifl}}_n<L\\ {\mathrm{\&mu;}}_{\mathrm{nm}}& \mathrm{otherwise}\end{array}\right.;$

Wherein μ_nlFor the service speed higher limit of this link, μ_nmService speed lower limit for this link.

Above formula determines long threshold value L of queuing up based on experience value, if the long l of queuing that detection obtains_nLess than this threshold value, Illustrate that current network state is good, then μ_nCapping value μ_nl, otherwise explanation current network state is bad, then take off limit value μ_nm.Logical Cross this way, so that Queueing Theory Method has a certain degree of adaptability to network time-varying characteristics.

Step 206: extract each of the links and be in data packet number m when queuing up long threshold value L_nL。

In the embodiment of the present invention, being directed to the shunting transmission of single kind business, i.e. the type of service in system is only A kind of.In this step, when a length of threshold value L of queuing, the data packet length of this class of business acquired in order is l_d, then data Bag quantity m_nLCan directly by L divided by l_dObtain.

Step 207: according to the service speed μ of each of the links_nWith the data packet number m being in when queuing up long threshold value L_nL, Packet delay D to each of the links_n。

For long-term evolving network link, produced packet delay is the packet delay directly transmitted via LTE, This part packet delay D₁Can be in the hope of by Li Teer law:

$D_1=\frac{1}{{\mathrm{\&mu;}}_1-{\mathrm{\&lambda;}}_1},$

Wherein λ₁Arrival rate for this link.

And for LTE network when the wlan network conversion link, produced packet delay D₂To D_nNeeds consider LTE and the service speed of wlan network, be equivalent to same Business Stream through twice service and the delay of queuing:

Wherein for the delay that wlan network causes,Wherein λ ' is WLAN The parameter of interference flow Poisson flow,For the arrival rate of this link after consideration WLAN interference flow.

And for the delay that LTE network causes, due to its service speed time-varying, therefore the expression formula of average retardation can Think:

$\begin{array}{c}\begin{array}{c}{D}_n^{\mathrm{LTE}}={(\frac{1-{\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right)}^{m_{\mathrm{nL}}+1}}{1-\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nL}}}\right)}+\frac{{\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right)}^{m_{\mathrm{nL}}}\&CenterDot;\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{um}}}}{1-\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nm}}}\right)})}^{-1}\&CenterDot;\{\frac{\left(\frac{1}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right)(1+(m_{\mathrm{nL}}-1){\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right)}^{m_{\mathrm{nL}}}-m_{\mathrm{nL}}{\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right)}^{m_{\mathrm{nL}}-1})}{{(1-\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right))}^2}\\ +\frac{{\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right)}^{m_{\mathrm{nL}}-1}(m_{\mathrm{nL}}-(m_{\mathrm{nL}}-1)\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nm}}}\right))}{{(1-\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nm}}}\right))}^2}\}\end{array}\end{array}$

Wherein λ_nFor this link arrival rate in the lte networks.

Step 208: according to minimizing the principle of system delay, determine the service distributing ratio of each of the links.

According to minimizing the principle of system delay, the business of each of the links can be determined by solving following optimization problem Shunt ratio:

$\underset{\mathrm{\&lambda;}}{\underset{\&RightArrow;}{\min }}\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{D}_i$

s.t.

$\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{\mathrm{\&lambda;}}_i=\mathrm{\&lambda;}$

0≤λ_n≤μ_n

0≤λ_n<min(μ_n,μ_n')-λ' i=2,3,…,n

Wherein constraints ensures that business arrival rate not can exceed that system service speed, reaction are i.e. in real network Available total bandwidth of uniting can not be less than total portfolio, even if otherwise also cannot be ensured the business body of user by separate system Test.

Step 209: according to the service distributing ratio of each of the links, periodically carries out service distributing.

Can be in the hope of the solution of the optimum service distributing ratio under current network state by the optimization problem solved above,This shunt ratio is used to carry out service distributing in next cycle, until carrying out next one The calculating in cycle and redistributing.Finally obtained shunting configuration diagram is as shown in Figure 4.

So far, then the process of embodiment of the present invention heterogeneous-network service shunt method is completed.

In addition, it is necessary to explanation, it is heterogeneous-network service shunting side of the present invention that above-mentioned all flow processs based on Fig. 2 describe The one of method preferably realizes process, in the actual realization of heterogeneous-network service shunt method of the present invention, and can be as required On the basis of flow process shown in Fig. 1, carry out random variation, can be to select the arbitrary steps in Fig. 2 to realize, the elder generation of each step Rear order can also adjustment etc. as required.

The embodiment of the present invention also provides for a kind of heterogeneous-network service separate system, as shown in Figure 5, and including:

Service request receiver module 501, for receiving the service requesting information of multimode terminal, then solicited message detection mould Block carries out information detection；

Information detection module 502, for each of the links in heterogeneous network carries out information detection, periodically obtains every Link buffer area queuing long message and data packet number, be sent to shunt decision-making module；

Shunting decision-making module 503, for according to each of the links buffer area queuing long message being periodically obtaining and data Bag quantity, determines the service distributing ratio of each of the links, and result is sent to flow-dividing control module；

Flow-dividing control module 504, for the service distributing ratio according to described each of the links, periodically carries out business and divides Stream.

In one embodiment of the invention, it is preferable that shunting decision-making module 503 may include that

Parameter adjustment submodule 601, as shown in Figure 6, for the long message l that each of the links queued up_nWith the link long threshold of queuing Value L compares, and determines the service speed μ of each of the links_n, n is the number of links in heterogeneous network；

Packet extracts submodule 602, for the data packet number m according to each of the links being periodically obtaining_n, extract Each of the links is in data packet number m when queuing up long threshold value L_nL；

Delay computing submodule 603, for the service speed μ according to each of the links_nWith the number being in when queuing up long threshold value L According to bag quantity m_L, obtain the packet delay D of each of the links_n；

Decision-making submodule 604, minimizes the principle of system delay, determines the service distributing ratio of each of the links for basis Example.

In another embodiment of the present invention, when using queueing theory that heterogeneous network separate system is modeled, industry Business flow arrival rate λ represents, network availability bandwidth then utilizes service speed μ to represent.Ratio between λ and μ is referred to as Service intensity ρ, the size of this value directly has relation with the long l that queues up.That is, when network state is the best, μ value is less, causes service Intensity is big, then team leader l is the longest；Otherwise then team leader l is the least.This explanation, can be by detecting the queuing of business in each LTE link The size of long l judges that current network state is the best, according to different network state revision μ values, thus realizes row The improvement of team's system, makes separate system that network state change is accomplished dynamically adapting.

To queuing up in long concrete detection process, can periodically send information detection instruction, according to each LTE link The feedback information of middle buffer area, obtains each of the links queuing long message l_n.As each of the links queuing long message l_nTime known, need Judge that network state corresponding to this team leader is the best, and according to different l_nAdjudicate rational μ value.Preferably, parameter adjustment Submodule 601 may include that

Parameter recommendation unit 701, such as Fig. 7, is used for the service speed μ utilizing equation below to determine each of the links_n:

${\mathrm{\&mu;}}_n=\left\{\begin{array}{cc}{\mathrm{\&mu;}}_{\mathrm{nl}}& {\mathrm{ifl}}_n<L\\ {\mathrm{\&mu;}}_{\mathrm{nm}}& \mathrm{otherwise}\end{array}\right.;$

Wherein μ_nlFor the service speed higher limit of this link, μ_nmService speed lower limit for this link.

Above formula determines long threshold value L of queuing up based on experience value, if the long l of queuing that detection obtains_nLess than this threshold value, Illustrate that current network state is good, then μ_nCapping value μ_nl, otherwise explanation current network state is bad, then take off limit value μ_nm.Logical Cross this way, so that Queueing Theory Method has a certain degree of adaptability to network time-varying characteristics.It should be noted that The analysis method of formula is also a kind of approximation, and the most accurately description can be greatly increased the complexity of computing, is unfavorable for engineer applied.

In another embodiment of the present invention, it is preferable that Delay computing submodule 603 may include that

Long-term evolving network unit 702, is used for utilizing formulaObtain the data of long-term evolving network link Packet delay, wherein λ_nObeying parameter for the arrival rate of this link, i.e. this link traffic stream is λ_nPoisson flow；

WLAN retransmission unit 703, is used for utilizing formulaObtain long-term evolving network warp The packet delay of WLAN conversion link:

WhereinFor considering the packet delay that WLAN interference flow causes,

Wherein λ ' is the parameter of WLAN interference flow Poisson flow,For considering nothing The arrival rate of this link after line LAN interference flow；

The average data packet delay caused for long-term evolving network:

$\begin{array}{c}\begin{array}{c}{D}_n^{\mathrm{LTE}}={(\frac{1-{\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right)}^{m_{\mathrm{nL}}+1}}{1-\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nL}}}\right)}+\frac{{\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right)}^{m_{\mathrm{nL}}}\&CenterDot;\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{um}}}}{1-\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nm}}}\right)})}^{-1}\&CenterDot;\{\frac{\left(\frac{1}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right)(1+(m_{\mathrm{nL}}-1){\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right)}^{m_{\mathrm{nL}}}-m_{\mathrm{nL}}{\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right)}^{m_{\mathrm{nL}}-1})}{{(1-\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right))}^2}\\ +\frac{{\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nl}}}\right)}^{m_{\mathrm{nL}}-1}(m_{\mathrm{nL}}-(m_{\mathrm{nL}}-1)\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nm}}}\right))}{{(1-\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{\mathrm{nm}}}\right))}^2}\}\end{array}\end{array}$

Wherein λ_nFor this link arrival rate in long-term evolving network.

Thus, the delay of the most all links all can be calculated.In order to determine the suitable shunt ratio of Business Stream, for For Queueing Theory Method, can be to minimize the main target of optimization postponed as queuing system.Another enforcement in the present invention In example, decision-making submodule 604 may include that optimization unit 704, minimizes the principle of system delay for basis, solves following Optimization problem:MakeAnd meet 0≤λ in long-term evolving network link_n≤μ_n, long-term evolving network 0≤λ in WLAN conversion link_n<min(μ_n,μ'_n)-λ ', wherein λ is the parameter of total service traffics Poisson flow, to Amount

And flow-dividing control module 504 may include that shunting submodule 605, for the industry according to obtained each of the links Business shunt ratio, periodically carry out service distributing.Namely according toThis shunt ratio is used to carry out industry in next cycle Business shunting, until carrying out the calculating in next one cycle and redistributing.

It should be noted that the structure of each embodiment of the heterogeneous-network service separate system shown in above-mentioned Fig. 6, Fig. 7 Can be used in any combination.The sequential chart of whole system agent structure is as shown in Figure 8.

Visible, the embodiment of the present invention has the advantages that

In a kind of heterogeneous-network service shunt method and system of embodiment of the present invention proposition, can not only be periodically Obtain the business feedback in each of the links buffer area, additionally it is possible to by the information integration that detected to theoretical model, thus real The dynamic bind of the existing theoretical shunting decision-making technique with engineering practice, improves accuracy and the initiative of shunt method.

It addition, the embodiment of the present invention introduces random disturbances possible in network, according to the periodically variable network information And parameter, consider the disturbed condition in network, draw according to effective Diffluence Algorithm and reasonably shunt decision-making, further Enhance the adaptability to engineering practice.

Last it is noted that above example is only in order to illustrate technical scheme, it is not intended to limit；Although With reference to previous embodiment, the present invention is described in detail, it will be understood by those within the art that: it still may be used So that the technical scheme described in foregoing embodiments to be modified, or wherein portion of techniques feature is carried out equivalent； And these amendment or replace, do not make appropriate technical solution essence depart from various embodiments of the present invention technical scheme spirit and Scope.

Claims (8)

1. a heterogeneous-network service shunt method, it is characterised in that including:

Receive the service requesting information of multimode terminal；

Each of the links in heterogeneous network is carried out information detection, periodically obtains each of the links buffer area queuing long message and number According to bag quantity；

According to each of the links buffer area queuing long message being periodically obtaining and data packet number, determine the business of each of the links Shunt ratio；

Service distributing ratio according to described each of the links, periodically carries out service distributing；

Each of the links buffer area queuing long message that described basis is periodically obtaining and data packet number, determine each of the links Service distributing ratio includes:

Queue up long message l by each of the links_nLong threshold value L of queuing up with link compares, and determines the service speed μ of each of the links_n, n is different Number of links in network forming network；

Data packet number m according to each of the links being periodically obtaining_n, extract each of the links and be in number when queuing up long threshold value L According to bag quantity m_nL；

Service speed μ according to each of the links_nWith the data packet number m being in when queuing up long threshold value L_nL, obtain each of the links Packet delay D_n；

According to minimizing the principle of system delay, determine the service distributing ratio of each of the links.

Heterogeneous-network service shunt method the most according to claim 1, it is characterised in that described length that each of the links is queued up Information l_nLong threshold value L of queuing up with link compares, and determines the service speed μ of each of the links_nIncluding:

Profit determines the service speed μ of each of the links with the following method_n:

${\mathrm{\&mu;}}_n=\left\{\begin{array}{cc}{\mathrm{\&mu;}}_{nl}& if{l}_n<L\\ {\mathrm{\&mu;}}_{nm}& otherwise\end{array}\right.;$

Wherein μ_nlFor the service speed higher limit of this link, μ_nmService speed lower limit for this link.

Heterogeneous-network service shunt method the most according to claim 2, it is characterised in that the described clothes according to each of the links Business speed μ_nWith the data packet number m being in when queuing up long threshold value L_nL, obtain the packet delay D of each of the links_nIncluding:

When this link is long-term evolving network link,Wherein λ_nFor the arrival rate of this link, i.e. this link It is λ that Business Stream obeys parameter_nPoisson flow；

When this link be long-term evolving network through WLAN conversion link time,

WhereinFor considering the packet delay that WLAN interference flow causes,Wherein λ ' is the parameter of WLAN interference flow Poisson flow, μ '_nFor this link after consideration WLAN interference flow Arrival rate；

The average data packet delay caused for long-term evolving network:

$\begin{array}{c}{D}_n^{LTE}={\left(\frac{1-{\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{nl}}\right)}^{m_{nL}+1}}{1-\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{nl}}\right)}+\frac{{\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{nl}}\right)}^{m_{nL}}\&CenterDot;\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{nm}}}{1-\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{nm}}\right)}\right)}^{-1}\&CenterDot;\{\frac{\left(\frac{1}{{\mathrm{\&mu;}}_{nl}}\right)\left(1+\left(m_{nL}-1\right){\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{nl}}\right)}^{m_{nL}}-m_{nL}{\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{nl}}\right)}^{m_{nL}-1}\right)}{{\left(1-\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{nl}}\right)\right)}^2}\\ +\frac{{\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{nl}}\right)}^{m_{nL}-1}\left(m_{nL}-\left(m_{nL}-1\right)\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{nm}}\right)\right)}{{\left(1-\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{nm}}\right)\right)}^2}\}\end{array}$

Wherein λ_nFor this link arrival rate in long-term evolving network.

Heterogeneous-network service shunt method the most according to claim 3, it is characterised in that:

Described basis minimizes the principle of system delay, determines that the service distributing ratio of each of the links includes:

According to minimizing the principle of system delay, solve following optimization problem:MakeAnd meet long-term 0≤λ in evolvement network link_n≤μ_n, long-term evolving network is 0≤λ in WLAN conversion link_n<min(μ_n,μ_n')- λ ', wherein λ is the parameter of total service traffics Poisson flow, vector

The described service distributing ratio according to described each of the links, periodically carries out service distributing and includes: according to obtained every The service distributing ratio of bar linkPeriodically carry out service distributing.

5. a heterogeneous-network service separate system, it is characterised in that including: the service request receiver module that is linked in sequence, letter Breath detecting module, shunting decision-making module and flow-dividing control module, wherein:

Service request receiver module, for receiving the service requesting information of multimode terminal, then solicited message detecting module is carried out Information detection；

Information detection module, for each of the links in heterogeneous network carries out information detection, periodically obtains each of the links and delays Deposit district's queuing long message and data packet number, be sent to shunt decision-making module；

Shunting decision-making module, each of the links buffer area queuing long message being periodically obtaining for basis and data packet number, Determine the service distributing ratio of each of the links, and result is sent to flow-dividing control module；

Flow-dividing control module, for the service distributing ratio according to described each of the links, periodically carries out service distributing；

Described shunting decision-making module includes:

Parameter adjustment submodule, for the long message l that each of the links queued up_nLong threshold value L of queuing up with link compares, and determines every chain The service speed μ on road_n, n is the number of links in heterogeneous network；

Packet extracts submodule, for the data packet number m according to each of the links being periodically obtaining_n, extract each of the links It is in data packet number m when queuing up long threshold value L_nL；

Delay computing submodule, for the service speed μ according to each of the links_nWith the data packet number being in when queuing up long threshold value L m_nL, obtain the packet delay D of each of the links_n；

Decision-making submodule, minimizes the principle of system delay, determines the service distributing ratio of each of the links for basis.

Heterogeneous-network service separate system the most according to claim 5, it is characterised in that described parameter adjustment submodule bag Include:

Parameter recommendation unit, for utilizing equation below to determine the service speed μ of each of the links_n:

${\mathrm{\&mu;}}_n=\left\{\begin{array}{cc}{\mathrm{\&mu;}}_{nl}& if{l}_n<L\\ {\mathrm{\&mu;}}_{nm}& otherwise\end{array}\right.;$

Wherein μ_nlFor the service speed higher limit of this link, μ_nmService speed lower limit for this link.

Heterogeneous-network service separate system the most according to claim 6, it is characterised in that described Delay computing submodule bag Include:

Long-term evolving network unit, is used for utilizing formulaObtain the packet delay of long-term evolving network link, Wherein λ_nObeying parameter for the arrival rate of this link, i.e. this link traffic stream is λ_nPoisson flow；

WLAN retransmission unit, is used for utilizing formulaObtain long-term evolving network through wireless office The packet delay of territory forwarded link:

WhereinFor considering the packet delay that WLAN interference flow causes,Wherein λ ' is the parameter of WLAN interference flow Poisson flow, μ '_nFor this link after consideration WLAN interference flow Arrival rate；

The average data packet delay caused for long-term evolving network:

$\begin{array}{c}{D}_n^{LTE}={\left(\frac{1-{\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{nl}}\right)}^{m_{nL}+1}}{1-\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{nl}}\right)}+\frac{{\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{nl}}\right)}^{m_{nL}}\&CenterDot;\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{nm}}}{1-\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{nm}}\right)}\right)}^{-1}\&CenterDot;\{\frac{\left(\frac{1}{{\mathrm{\&mu;}}_{nl}}\right)\left(1+\left(m_{nL}-1\right){\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{nl}}\right)}^{m_{nL}}-m_{nL}{\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{nl}}\right)}^{m_{nL}-1}\right)}{{\left(1-\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{nl}}\right)\right)}^2}\\ +\frac{{\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{nl}}\right)}^{m_{nL}-1}\left(m_{nL}-\left(m_{nL}-1\right)\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{nm}}\right)\right)}{{\left(1-\left(\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&mu;}}_{nm}}\right)\right)}^2}\}\end{array}$

Wherein λ_nFor this link arrival rate in long-term evolving network.

Heterogeneous-network service separate system the most according to claim 7, it is characterised in that:

Described decision-making submodule includes: optimize unit, minimizes the principle of system delay for basis, solves following optimization and ask Topic:MakeAnd meet 0≤λ in long-term evolving network link_n≤μ_n, long-term evolving network is through wireless 0≤λ in LAN conversion link_n<min(μ_n,μ_n')-λ ', wherein λ is the parameter of total service traffics Poisson flow, vector

Described flow-dividing control module includes: shunting submodule, for the service distributing ratio according to obtained each of the links Periodically carry out service distributing.