CN101478803B - Self-organizing QoS routing method based on ant colony algorithm - Google Patents

Abstract

The invention relates to a ant algorithm-based self-organization QoS routing method and the method comprises the following steps: A. receiving the data message transmitted by a neighborhood router; B. judging whether the message is a unicast message according to the destination address of the data message; C. entering a unicast QoS routing method; D. initializing a router register; E. examining path evaluation value J<path> and finding the path meeting the demand of users; F. passing to the step K; G. entering the multicast QoS routing method; H. initializing the router register and constructing multicast trees; I. multicast tree cost allocation; J. calculating the evaluation value JT of the multicast tree and finding the present feasible multicast trees; K. retransmitting the data message to the next hop router according to the calculated present feasible multicast tree. The method has the advantages of effectively routing and retransmitting the data on the basis of the QoS request, improving routing success rate, and having higher superiority than traditional network models, and the routing method of the design has good performance and practicability.

Description

A kind of self-organizing QoS routing method based on ant algorithm

Technical field

The invention belongs to networking technology area, be specifically related to a kind of self-organizing QoS routing method based on ant algorithm.

Background technology

Along with the progressively maturation of self-organizing network, network organization becomes more diverse, and network size enlarges day by day, and service quality (QoS) assurance problem also becomes more and more important.QoS is exactly the measurable predefined service quality based on end to end performance of a cover that network must satisfy during to end data for the user transmission end, and index comprises time delay, delay variation, available bandwidth and grouping packet loss etc.Because self-organizing network has multi-hop, dynamic topology, distributed, provisional, characteristics such as link bandwidth is limited, energy constraint, till now not the ripe method for routing of a cover can be in self-organizing network stabilizing effective transmission QoS information.

Summary of the invention

Deficiency at prior art exists the invention provides a kind of self-organizing QoS routing method based on ant algorithm.

1. ant group algorithm

In the nineties in 20th century, people such as Italy scholar M.Dorigo, V.Maniezzo and A.Colorni are inspired from the mechanism of biological evolution, seek the behavior in footpath by simulating nature circle ant, a kind of brand-new simulated evolutionary algorithm---ant group algorithm has been proposed, and use this algorithm and find the solution traveling salesman problem, assignment problem, job scheduling problem etc., obtained a series of experimental results preferably.

Studies show that the ant communities of occurring in nature has to use and retains pheromones, chooses the ability in the shortest (optimum) path between its ant cave and food source.When ant advances on a paths, can stay volatile pheromones, attracting other ants, ant afterwards selects the concentration of pheromones on the probability in this path and this paths at that time to be directly proportional.Because the concentration maximum of pheromones has attracted more ant on the shortest (optimum) path, the ant number in selection the shortest (optimum) path is increased.Just because of the effect of this positive feedback method, the shortest (optimum) path will the most ants of very fast quilt be found and is utilized.

Chinese scholars is paid special attention to the research and development of ant group algorithm always, and wherein, ant network (AntNet) algorithm is exactly to develop from ant group algorithm.In the ant network algorithm, defined two classes and moved agent: forward direction agent and back are to agent, and they bear different tasks in the foundation of routing table, refresh process.Forward direction agent is responsible for collecting the state information of record current network, and it preserves the state information of collecting in the pathfinding by suitable data structure, and record path information, and each node comes acquisition of information with certain interval transmission forward direction agent in the network.When forward direction agent arrives destination node, can triggering for generating after one to agent, forward direction agent passes to the back to agent of new generation with the information of collecting simultaneously, this back utilizes the network information of acquisition that routing table is made amendment to agent.

The general procedure of route is as follows:

(1) sends forward direction agent to destination node at certain intervals from source node.

(2) forward direction agent record path is preserved the node that lives through, and writes down relevant network state information simultaneously.

(3) when forward direction agent arrives destination node, one of triggering for generating is inherited the back to agent of forward direction agent relevant information.

(4) back oppositely arrives source node to the information of agent along original route from destination node, upgrades the information in the routing table simultaneously.

(5) through after several agent pathfindings, will write down the optimal path from the source node to the destination node in the routing table.

2. worldlet model

Famous Stanley Milgram experiment is found, just can connect any two people in the society by average 6 person-times acquaintance's transmission, and this phenomenon is called the worldlet phenomenon.The experiment of Milgram has disclosed two discoveries: (1) short chain effect ubiquity; (2) people can find short chain.(2) individual discovery explanation when network presents certain topological structure, only utilizes local message just can find short chain effectively.This is found to be distributed route opportunity is provided.

The model that Watt and Strogatz propose (being called for short the WS model) is a kind of worldlet model commonly used: N node is distributed on the annulus, and during initial condition, each node has k connection, connects respectively to nearest k point.Then, adjust the connection of each node successively, change the terminal of connection randomly with Probability p, but the company of avoiding is to node itself.

Note D (i j) is beeline between node i and the j, and the computing formula of average path distance L is as follows:

$L=\frac{1}{n(n-1)/2}\underset{1\&le;i,j\&le;n}{\mathrm{\&Sigma;}}D(i,j)$

When p ≈ 0, $L\&RightArrow;\frac{n}{2k},$ This moment, network topology was rule state; When 0.001≤p≤0.01, $L\&RightArrow;\frac{\ln n}{\ln k},$ This moment, node not only was connected with the adjacent node existence, had also set up the shortcut (shortcut) of minority with remote node, and these shortcut have effectively shortened L just, make whole network present the worldlet feature.

In the worldlet network model, comparative maturity be tall grace Kleinberg (Jon Kleinberg) model.Two kinds of limits have been defined in this model: a large amount of local limits (neighbour) and a spot of long-range limit (distant relative).In the two-dimensional grid model of n node (

Be one dimension node number), model has proved that the distributed routing algorithm chain length upper bound is

The feature of worldlet network: (1) does not consider network topology structure, and very little average distance is arranged between node; (2) bigger acquaintance coefficient is arranged.Certain node, in its all neighbours, backfence even limit number accounts for the subnet that comprises this node and connects limit sum ratio, is called the acquaintance coefficient.It has reflected the backfence acquaintance degree of certain node, and it and network size have nothing to do and be permanent in 1.In sociology, a people not only can utilize the acquaintance to come acquisition of information in the process of seeking another person, also can collect more information by the attribute of company under the acquaintance or corporations.Such as, someone wishes to look for the people to help to compile a program, and he can inquire whether they can programme to the acquaintance, can inquire also whether they are familiar with the student of (being equivalent to a Virtual Organization) of department of computer science simultaneously.

3. the design of self-organizing QoS routing method

3.1 self organizing network model

Self organizing network model can be expressed as a undirected connected graph G (V, E), wherein V has the biological nature behavior and has to transmit and the set of the intelligent node of disposal ability, represents the router in the network; E is the set on limit, the link in the expression network, as shown in Figure 3.

3.2 Mathematical Modeling

3.2.1 clean culture Mathematical Modeling

In the unicast QoS routing issue, optimization aim is: under the situation that satisfies user QoS constraint, effectiveness and the user and the network provider effectiveness sum of maximization user, Virtual network operator make user and network provider effectiveness reach doulbe-sides' victory.

Then have:

UU _P→max{UU _P}

UN _P→max{UN _P}

UU _P+UN _P→max{UU _P+UN _P}

s.t. $\underset{e_l\&Element;P_{\mathrm{sd}}}{\min }\left\{{\mathrm{abw}}_l\right\}\&GreaterEqual;\mathrm{bw}\_r_l$ (the available bandwidth minimum value on the link l=＞lower band)

$\underset{e_l\&Element;P_{\mathrm{sd}}}{\mathrm{\&Sigma;}}{\mathrm{dl}}_l\&le;\mathrm{dl}\_r_h$ (delay on the link l and＜=postpone the upper limit)

$\underset{e_l\&Element;P_{\mathrm{sd}}}{\mathrm{\&Sigma;}}{\mathrm{jt}}_l\&le;\mathrm{jt}\_r_h$ (delay jitter on the link l and＜=the delay jitter upper limit)

$1-\underset{e_l\&Element;P_{\mathrm{sd}}}{\mathrm{\&Pi;}}(1-{\mathrm{ls}}_l)\&le;\mathrm{ls}\_r_h$ (product of the accuracy on the 1-link l)＜=error rate upper limit)

Pay _P≤ p (the required multicast tree expense ratio＜=user who shares of group membership p is willing to pay and uses the upper limit)

UU _PBe the user's effectiveness on path or the multicast tree, UN _PThen be network provider effectiveness.

3.2.2 multicast Mathematical Modeling

In multicast QoS route, optimization aim is: under the prerequisite that satisfies all group membership's end-to-end QoS constraints, and effectiveness and the user and the network provider effectiveness sum of maximization user, Virtual network operator.

Then have: UU _P→ max{UU _P(UUp level off to UUp maximum)

UN _P→max{UN _P}

UU _P+UN _P→max{UU _P+UN _P}

Make and satisfy $\underset{e_l\&Element;P_{\mathrm{sd}}}{\min }\left\{{\mathrm{abw}}_l\right\}\&GreaterEqual;\mathrm{bw}\_r_l$ (the available bandwidth minimum value on the link l=＞lower band)

$\underset{e_l\&Element;P_{\mathrm{sd}}}{\mathrm{\&Sigma;}}{\mathrm{dl}}_l\&le;\mathrm{dl}\_r_h$ (delay on the link l and＜=postpone the upper limit)

$\underset{e_l\&Element;P_{\mathrm{sd}}}{\mathrm{\&Sigma;}}{\mathrm{jt}}_l\&le;\mathrm{jt}\_r_h$ (delay jitter on the link l and＜=the delay jitter upper limit)

$1-\underset{e_l\&Element;P_{\mathrm{sd}}}{\mathrm{\&Pi;}}(1-{\mathrm{ls}}_l)\&le;\mathrm{ls}\_r_h$ (product of the accuracy on the 1-link l)＜=error rate upper limit)

Pay _P≤ p (the required multicast tree expense ratio＜=user who shares of group membership p is willing to pay and uses the upper limit)

UU _PBe the user's effectiveness on path or the multicast tree, UN _PThen be network provider effectiveness

UU _T→max{UU _T}

UN _T→max{UN _T}

UU _T+UN _T→max{UU _T+UN _T}

s.t. $\underset{e_l\&Element;P_{\mathrm{sd}}}{\min }\left\{\mathrm{ab}{w}_l^d\right\}\&GreaterEqual;\mathrm{bw}\_r_l^d$ (the available bandwidth interval value on the link l=＞the bandwidth interval value)

$\underset{e_l\&Element;P_{\mathrm{sd}}}{\mathrm{\&Sigma;}}{\mathrm{dl}}_l^d\&le;\mathrm{dl}\_r_h^d$ (the delay interval value on the link l and＜=postpone interval value)

$\underset{e_l\&Element;P_{\mathrm{sd}}}{\mathrm{\&Sigma;}}{\mathrm{jt}}_l^d\&le;\mathrm{jt}\_r_h^d$ (the delay jitter interval value interval value on the link l and＜=delay jitter interval value)

$1-\underset{e_l\&Element;P_{\mathrm{sd}}}{\mathrm{\&Pi;}}(1-{\mathrm{ls}}_l^d)\&le;\mathrm{ls}\_r_h^d$ (product of the accuracy interval value on the 1-link l)＜=error rate interval value)

${\mathrm{Pay}}_p^d\&le;p^d$ (the required multicast tree expense interval value ratio＜=user who shares of group membership p is willing to pay and uses interval value)

UU _TUser's effectiveness on path or the multicast tree, UN _TThen be network provider effectiveness.

3.2.3 worldlet behavior

(1) the worldlet behavior has following characteristic

(a) the node number of degrees high changeability of distributing can obtain short path and the height coefficient that clusters;

(b) when node number of degrees changeability when not being very high, it can not cause the worldlet behavior separately;

(c) the local connection of preference can cause the worldlet behavior, especially in the network topology of router level;

Self-organizing network has the biological nature behavior, and node is dynamic, and the limit also can be set up or be removed, so the node number of degrees are variable.In addition, internodal in the self-organizing network all is local alternately, and just so-called preference is local to be connected.But, become the tangible network of worldlet behavior to need a process by network evolution at random, may not directly utilize the worldlet characteristics to carry out route in the meantime.And also have a bit, in the existing worldlet network model, what the connection between the node referred to all is direct connection, that is to say the limit that physical connection is directly arranged with it that the changeability of the node number of degrees also is meant.Here, produce the worldlet behavior and obtain corresponding advantages, the worldlet limit of mentioning in the self-organizing behavior design thereby can serve as direct-connected limit with indirectly connected limit.

For example, the directly continuous node of node A has A ₁, A ₂, A ₃, A ₄, but it is several with A to be that the route of source node has been set up, and its destination node is respectively D ₁, D ₂, D ₃, from A to D ₁, D ₂, D ₃Just there is the worldlet limit respectively.When calculating the number of degrees of A, these three worldlet limits can be counted.When route, also can dynamically worldlet there be the limit optionally to see optional next jumping limit of A as, have so just realized a kind of changeability of the node number of degrees.

Certainly, though directly can produce very favourable outcome to stretch as a limit, also brought some problems simultaneously, the complexity of handling a stretch footpath and an actual limit of processing after all in the process of route is incomplete same.

This mode also can cause another problem sometimes, though the path of finding by the worldlet limit is that through step number seldom the actual jumping figure in path may be a lot, is not a very excellent path just also, as shown in Figure 4.

Have the worldlet limit among Fig. 4 between S and the M, have the worldlet limit between M and the D, then S only needs through twice pathfinding to M to D.In fact but will jump through 8, and S → A → B → D in fact only needs 3 to jump, though will be through three pathfindings.

Cause occurring problem recited above for fear of repeatedly introducing the pathfinding of worldlet limit, will be limited in routing procedure here one time, only can in the end one jump introducing worldlet limit.Just only introduce the worldlet limit that can directly arrive destination node, but also will limit the length on worldlet limit at present node.

Like this, just can reduce the probability that above-described problem takes place greatly.And,, then also can eliminate gradually by optimised algorithm if performance is bad for introducing the path that the worldlet limit obtains.In addition, in the dynamic environment of self-organizing network, it is often more meaningful than optimum to reach suboptimum fast.

(2) in self-organizing network, realize the worldlet behavior

(a) utilize the worldlet limit

Along with the operation of algorithm, node can accumulate down serves the worldlet limit.Along with increasing of worldlet limit, reached at the node that node is known is also just more and more, then in the routing procedure of back, just can directly utilize the reachability information on worldlet limit to accelerate routing procedure.

As shown in table 1 by the worldlet path record that present node sets out.

The tabulation of table 1 worldlet limit

Initialization: each node all has such worldlet routing table, when initial, shows to be sky.

Add: finished by algorithm, the every paths that successfully finds of algorithm just joins this path relevant information in the source node worldlet routing table, and value is 0 wherein " to be used counting ".

Counting: after the arrival destination node was successfully adopted on a worldlet limit, just " being used number of times " value with the worldlet limit added 1.

Upgrade: every time Δ t _SwpScan the value of " being used number of times " in table, delete those values and be 0 row, " being used number of times " value zero clearing of each row that will remain then.

(b) node route success rate

Be meant the shared percentage of number of times successful in the total routing times of node.The node that success rate is higher, more believable when route.

All set two counters at each node, rcs (successful routing times counter), rct (the total routing times counter of node).When node was used in route, rct just increased 1, and after the success of this time route, rcs just increases 1.Here, ageing for guaranteeing, rcs, rct value are every some cycles Δ t _RcWith regard to zero clearing.

The route success rate formula of computing node i is as follows:

$I_i=\frac{{\mathrm{rcs}}_i}{{\mathrm{rct}}_i}$

(c) according to address structure: the node with identical ip addresses prefix probably can be positioned at the zone of closing on, and the same prefix part is long more, may be positioned at nearer zone more, and this specific character with the address is called the phase recency here.For example: 202.118.1.64 and 202.118.1.206, identical prefix part is 202.118.1, so the two is positioned at very near zone, the phase recency of the two is higher.

Calculate the address of optional next-hop node and the recency mutually of this route destination address, the phase recency is high more, and then next-hop node might find destination node more, this also similar familiarity that is next-hop node to this route destination address.

Following method is taked in the calculating of two address phase recencies: 32 bit address are scanned relatively binary digit from left to right by turn, if identical just the continuation scanned, if difference just finishes, write down identical figure place M _Ik, phase recency V then _iFor:

$V_i=\frac{M_{\mathrm{ik}}}{32}$

This method is as follows:

Steps A: receive the data message that neighbor router sends;

Step B: whether the destination address according to data message is that unicast address judges whether type of message is unicast message;

It is characterized in that: according to step B is unicast message, execution in step C then, otherwise execution in step G;

Step C: enter clean culture modeling QoS method for routing;

Step D: the initialization router register, send forward direction ant agent pathfinding, call ant algorithm, wherein agent is responsible for collecting record current network state information;

Step e: examination path evaluation of estimate J _Path, find the path that meets user's request;

Step F: forward step K to;

Step G: enter multicast modeling QoS method for routing, given multicast request: R (v _s, v _d, Δ _Bw ^d, Δ _Dl ^d, Δ _Jt ^d, Δ _Ls ^d, p ^d), be its structure multicast tree, wherein a v _sRepresent source node, v _dRepresent destination node, Δ _Bw ^dRepresent between the bandwidth demand confining region Δ _Dl ^dRepresent between the delay requirement confining region Δ _Jt ^dRepresent between delay jitter demand confining region Δ _Ls ^dRepresent between the error rate desired region p ^dRepresentative of consumer is willing to pay and is used the upper limit;

Step H: the initialization router register makes up multicast tree;

Step I: multicast tree cost allocation;

After forming multicast tree, because selected limit selects for use the user shared, so also naturally by selecting for use the user to share jointly, the principle of sharing is rate: the part that the high more then user of expense that the user takies required pair of this paths alone shares in multicast tree is paid is big more.

The setting source node to the set of each group membership's the required paying in path is:

W _p={ pav ₁, pay ₂..., pay _N-1, pay _nPay in the formula _nBe the required paying in each group membership's path, n=1,2 ..., N, N belongs to natural number, then i group membership v _iRequired multicast tree expense ratio of sharing is:

${\mathrm{per}}_d=\frac{{\mathrm{pay}}_i}{\underset{k\&Element;\{\mathrm{1,2},...\}}{\mathrm{\&Sigma;}}{\mathrm{pay}}_k}$ I ∈ n in the formula, k ∈ n;

Step J: calculate multicast tree evaluation of estimate J _T, find out the present feasible multicast tree;

Step K: data message forwarding is arrived next hop router according to the present feasible multicast tree that calculates.

Calling ant algorithm among the step D comprises:

Step D1: the initialization router register, maximum iterations TIN is set, iterations IN=0, the ant agent quantity AN that the each iteration of initialization sends, the agent that has sent counts an=0, path evaluation of estimate J _Path=∞, feasible path are empty;

Step D2:IN ← IN+1, source node is with interval delta _tSend AN forward direction ant agent pathfinding, agent of every transmission is with regard to an ← an+1, each forward direction agent of initialization, wherein: ant agent sequence number seq=an;

Step D3: forward direction agent record path, the node that lives through is preserved, write down relevant network state information simultaneously, forward direction ant agent is after source node is issued, and the node of each process in network is act of execution by the following step;

Step D31: judge whether current ant agent jumping figure transfinites, if, then ant agent death;

Step D32: if the direct next-hop node of present node has this route destination node, then investigate with this node between the limit whether satisfy the user and ask constraint, as satisfied, then ant agent jumps to destination node, forwards step D35 to;

Step D33: realize worldlet at present node;

Step D34: carry out next at present node and jump selection;

Step D341:, route total degree counter is increased by 1 at present node;

Step D342: realize the worldlet behavior;

Step D343: if next jumping is selected successfully to return, then ant agent proceeds to this node;

Step D344: select failure, ant agent death if next is jumped;

Step D35: forward direction ant agent task is finished;

Step D4: when forward direction agent arrived destination node, one of triggering for generating was inherited the back to agent of forward direction agent relevant information.The back oppositely arrives source node to the information of agent along original route from destination node, upgrades the information in the routing table simultaneously;

Step D41: in destination node, according to forward direction ant agent information, according to formula $J_P=\frac{{\mathrm{\&alpha;}}_{\mathrm{up}}}{{\mathrm{UU}}_P}+\frac{{\mathrm{\&alpha;}}_{\mathrm{np}}}{{\mathrm{UN}}_P}$ (wherein, α _Up, α _NpBe inclination weights to the user, 0＜α _Up, α _Np＜1, α _Up+ α _Np=1) calculating path evaluation of estimate J _P, and give the back of generation to agent; Give the back to ant agent with the path that forward direction ant agent finds;

Step D42: the back by the routing information of preserving, is oppositely jumped to upstream node to agent, then the plain table of lastest imformation; At present node, ant increases by 1 with route number of success counter, if ant agent has introduced the worldlet limit at present node, then upgrades worldlet limit table;

Step D43: judge whether the back arrives source node to ant agent, if no show then jumps to step D42;

Step D44: the back is compared to evaluation of estimate and the current path evaluation of estimate that ant agent carries the path,, then new route is saved as the present feasible path if agent carries the evaluation of estimate in path less than the current path evaluation of estimate;

Step D45: finish to the agent task back, calls ant group algorithm and finish.

Step D33 realizes that at present node the worldlet limit comprises:

Step D331: judge whether current agent is using the worldlet limit, if then directly take out the worldlet limit as next-hop node; Otherwise, jump to step D333;

Step D332: judge that can this next-hop node satisfy the user and ask constraint, if can, ant agent selects this node as next-hop node, preserve the QoS information and the cost information on limit between present node and this node, ant agent finishes in the present node behavior, proceeds to this next-hop node then; Otherwise, ant agent death;

Step D333: investigate the sequence number of ant agent, judge that whether this agent is this iteration last in sending, if not, then jump to step D34;

Step D334: investigate present node worldlet limit table, whether have the worldlet limit that arrives destination node, if there is no, then jump to step D34;

Step D335: deposit the worldlet limit in ant agent, and ant agent use worldlet limit is set, ant agent writes down this node address then, jumps to D331.

Step D342 realizes that the worldlet behavior comprises:

If the sequence number of ant agent is an even number, then select next-hop node at random; Otherwise, calculate and select next to jump, calculate the user satisfaction value computing formula of corresponding sides: $W_l={\mathrm{\&alpha;}}_{\mathrm{bw}}\&CenterDot;g_{\mathrm{bw}}^l+{\mathrm{\&alpha;}}_{\mathrm{dl}}\&CenterDot;g_{\mathrm{dl}}^l+{\mathrm{\&alpha;}}_{\mathrm{jt}}\&CenterDot;g_{\mathrm{jt}}^l+{\mathrm{\&alpha;}}_{\mathrm{ls}}\&CenterDot;g_{\mathrm{ls}}^l$ In the formula, α _Bw, α _Dl, α _JtAnd α _LsBe respectively the weight coefficient of each qos parameter, α _Bwα _Dlα _Jtα _Ls∈ [01], and α _Bw+ α _Dl+ α _Jt+ α _Ls=1, W _lBe the numerical value between 0 and 1, g _Bw ^lExpression bandwidth satisfaction, g _Dl ^lExpression time-delay satisfaction, g _Jt ^lExpression delay jitter satisfaction, g _Ls ^lRepresent the error rate satisfaction, calculate the route success rate of i node: $I_i=\frac{{\mathrm{rcs}}_i}{{\mathrm{rct}}_i},$ Rcs is successfully the routing times counter in the formula, and rct is that the total routing times counter of node is.When node was used in route, rct just increased 1, and after the success of this time route, rcs just increases 1.Here, ageing for guaranteeing, rcs, rct value are every some cycles Δ t _RcWith regard to zero clearing, calculate the progress of thinking of i node and this route destination address: 32 bit address are scanned relatively binary digit from left to right by turn,,, write down identical figure place M if difference just finishes if identical just the continuation scanned _Ik, phase recency then $V_i=\frac{M_{\mathrm{ik}}}{32}:$ Calculate next bar and select probability: pro _j=P _Ij* W _j* I _j* V _jP _IjBe corresponding N in the present node pheromones table _jPheromone concentration, W _jUser satisfaction value, the I of expression node j _jRoute success rate, the V of expression node j _jThe phase recency of expression node j is according to pro _j, select corresponding pro _jThe maximum next-hop node of value is jumped as next and is selected.

Step e examination path evaluation of estimate J _Path, find the path that meets user's request to comprise:

Step e 1: at the source node Δ that waits for a period of time _tAfter, examination path evaluation of estimate J _Path

Step e 2: if J _Path＜∞, then algorithm successfully finds the path that meets user's request, at source node current surviving path is added the worldlet table, goes to step K;

Step e 3: if J _PathWhether=∞ then judges IN less than TIN, if, then go to step D3, otherwise routing failure.

Step H initialization router register makes up multicast tree and comprises:

Step H1: the initialization router register is provided with iterations CN, iterations cn=0, multicast tree evaluation of estimate J _Tree=∞, the present feasible multicast tree is for empty;

Step H2: all group memberships by the descending arrangement of bandwidth request, are set pending group membership and gather W={v ₁, v ₂..., v _N-1, v _n, v _nBe pending group membership, n=1,2 ..., N, N belongs to natural number, processed group member set A=Φ, feasible path set P=Φ, wherein Φ is null set;

Step H3: get v _d∈ W utilizes the singlecast router algorithm based on the ant network, by v _sTo v _dSeek one and satisfy member v _dThe feasible path p of request constraint _dIf, do not find, then this time make up the multicast tree failure, jump to step J3;

Step H4: with node v _dFrom the W deletion, and add A;

Step H5: check feasible path p _dOn whether contain group membership among the hand W, if do not have, then jump to step H7;

Step H6: if p _dOn contain the group membership who is arranged in W, judge that can these group memberships' request constraint at p _dBe met, the node that can be satisfied is deleted from W, and adds A;

Step H7: with feasible path p _dAdd set P;

Step H8:, then jump to step H1 if set W is not empty;

Step H9: the path among the P in the feasible path is combined into a multicast tree, and in the process of Cheng Shu, each group membership's request constraint all will be satisfied, and ring can not occur, otherwise this makes up the multicast tree failure, jumps to step J3.

Step J calculates multicast tree evaluation of estimate J _T, find out the present feasible multicast tree and comprise:

Step J1: calculate multicast tree evaluation of estimate J according to formula _T

Step J2: if J _T＜J _Tree, J _TreeBe the evaluation of estimate of present feasible multicast tree, then replace present feasible multicast tree, J with the multicast tree that calculates _Tree=J _T

Step J3:cn ← cn+1 is if cn＜CN jumps to step H;

Step J4: judge J _TreeWhether＜∞ sets up, if set up, and then algorithm success, otherwise algorithm failure.

The present invention has designed a kind of method for routing, and this method is carried out algorithm design based on a kind of distributed routing algorithm one ant network algorithm.Can effectively ask data are carried out route and forwarding in routing procedure by this method for routing based on QoS.Ant algorithm can be designed as hop-by-hop pathfinding in network, and the present invention has designed next jumping selection strategy of this algorithm, and the QoS route is supported in expansion.In order to reduce route time, improve the route success rate, this paper has introduced the worldlet behavior in algorithm.Introduced the coarse link parameter of fuzzy mathematics knowledge description simultaneously, introduced and to receive that assorted (Nash) is balanced, the most excellent microeconomics method of Pareto (Pareto) is carried out the link policy selection.The present invention carries out emulation to the self organizing network model and the self-organizing QoS routing method of design on the NS2 platform, the route method is realized.By performance evaluation is carried out in emulation and realization, draw self organizing network model and have an enormous advantage than legacy network model tool, the method for routing of this design has good performance and practicality.

Description of drawings

Fig. 1 is the self-organizing QoS routing method step block diagram that the present invention is based on ant algorithm;

Fig. 2 is the self-organizing QoS routing method particular flow sheet that the present invention is based on ant algorithm;

Fig. 3 is the self-organized network topology schematic diagram;

Fig. 4 is a worldlet limit schematic diagram;

Fig. 5 is an implementation platform schematic diagram of the present invention;

Fig. 6 is CERNET network of the present invention (CERNET) topology.

Embodiment

A kind of self-organizing QoS routing method of the present invention based on ant algorithm, ant algorithm is embedded into Quagga, and (Quagga is a route software of increasing income, on Quagga, can move OSPF, Routing Protocols such as BGP) in the source code in the routing program of increasing income, use 24 PCs as the prototype router, wherein 4 as application server; 24 Intel (INTEL) network interface card, 24 Pu Ruier (TP_LINK) network interface card, 26 netting twines.

The configuration of prototype router software is as follows: LinuxFC7 operating system; Use ospf6d and two finger daemons of bgpd in the GNU C expansion Quagga software router under the Linux, GNU C writes the interface module of docking with algorithm under the use Liunx, realizes the self adaptation unicast routing protocol in the self-organizing network; GNU C writes finger daemon under the use Liunx, and expansion realizes the self-adaptive multicast Routing Protocol based on IPv6.Network topology structure as shown in Figure 5,20 prototype routers are disposed with reference to the CERNET2 network configuration, 4 application servers and prototype router are direct-connected.The present invention has realized the needed agreement support of binding algorithm, the obtaining of neighbor information, network state information obtain the forwarding of route agent.(NS2 is meant NetworkSimulator version 2 at NS2, be a kind of at disclosed, the free software simulation platform of the source code of network technology, the researcher uses it can carry out the exploitation of network technology easily, become the widely used a kind of network analog software of academia at present) in the system, the self-organizing network analogue system that operation has realized, carry out real data and send test, obtain following the tracks of (trace) file.The Trace file is the packet trace file that the NS2 system generates according to network operation state, in link or formation, have packet arrive, when leaving or abandoning, the capital goes on record, be communicated with at that time time and the essential information of packet also go on record simultaneously.

Route simulating system is based upon on CERNET (CERNET) topology, and as shown in Figure 6, the parameter setting of topology has certain objectivity substantially with reference to practical situation.

In network model, a given route requests, the method for routing that moves this paper is respectively looked for the road and is added routing table entry, and then sends the packet of a period of time according to the bandwidth value of setting in the route requests, obtains the trace file.Re-use the built-in distance vector of NS2 system (DV) Routing Protocol, send the data of identical time, obtain the trace file by same source, destination node and bandwidth value.Respectively the trace file that obtains is analyzed, obtained throughput, end-to-end delay, shake and the packet loss of data transfer path, calculate the end-to-end transmission satisfaction of user in conjunction with user's request by the satisfaction formula then.

The present invention as depicted in figs. 1 and 2, as follows:

Steps A: receive the data message that neighbor router sends;

Step B: whether the destination address according to data message is that unicast address judges whether type of message is unicast message;

It is characterized in that: according to step B is unicast message, execution in step C then, otherwise execution in step G;

Step C: enter clean culture modeling QoS method for routing;

Step D: the initialization router register, send forward direction ant agent pathfinding, call ant algorithm, wherein agent is responsible for collecting record current network state information;

Step e: examination path evaluation of estimate J _Path, find the path that meets user's request;

Step F: forward step K to;

Step G: enter multicast modeling QoS method for routing, given multicast request: R (v _s, v _d, Δ _Bw ^d, Δ _Dl ^d, Δ _Jt ^d, Δ _Ls ^d, p ^d), be its structure multicast tree, wherein a v _sRepresent source node, v _dRepresent destination node, Δ _Bw ^dRepresent between the bandwidth demand confining region Δ _Dl ^dRepresent between the delay requirement confining region Δ _Jt ^dRepresent between delay jitter demand confining region Δ _Ls ^dRepresent between the error rate desired region p ^dRepresentative of consumer is willing to pay and is used the upper limit;

Step H: the initialization router register makes up multicast tree;

Step I: multicast tree cost allocation;

After forming multicast tree, because selected limit selects for use the user shared, so also naturally by selecting for use the user to share jointly, the principle of sharing is rate: the part that the high more then user of expense that the user takies required pair of this paths alone shares in multicast tree is paid is big more.

The setting source node to the set of each group membership's the required paying in path is:

W _p={ pav ₁, pay ₂..., pay _N-1, pay _nPay in the formula _nBe the required paying in each group membership's path, n=1,2 ..., N, N belongs to natural number, then i group membership v _iRequired multicast tree expense ratio of sharing is:

${\mathrm{per}}_d=\frac{{\mathrm{pay}}_i}{\underset{k\&Element;\{\mathrm{1,2},...\}}{\mathrm{\&Sigma;}}{\mathrm{pay}}_k}$ I ∈ n in the formula, k ∈ n;

Step J: calculate multicast tree evaluation of estimate J _T, find out the present feasible multicast tree;

Step K: data message forwarding is arrived next hop router according to the present feasible multicast tree that calculates.

Calling ant algorithm among the step D comprises:

Step D1: the initialization router register, maximum iterations TIN is set, iterations IN=0, the ant agent quantity AN that the each iteration of initialization sends, the agent that has sent counts an=0, path evaluation of estimate J _Path=∞, feasible path are empty;

Step D2:IN ← IN+1, source node is with interval delta _tSend AN forward direction ant agent pathfinding, agent of every transmission is with regard to an ← an+1, each forward direction agent of initialization, wherein: ant agent sequence number seq=an;

Step D3: forward direction agent record path, the node that lives through is preserved, write down relevant network state information simultaneously, forward direction ant agent is after source node is issued, and the node of each process in network is act of execution by the following step;

Step D31: judge whether current ant agent jumping figure transfinites, if, then ant agent death;

Step D32: if the direct next-hop node of present node has this route destination node, then investigate with this node between the limit whether satisfy the user and ask constraint, as satisfied, then ant agent jumps to destination node, forwards step D35 to;

Step D33: realize worldlet at present node;

Step D34: carry out next at present node and jump selection;

Step D341:, route total degree counter is increased by 1 at present node;

Step D342: realize the worldlet behavior;

Step D343: if next jumping is selected successfully to return, then ant agent proceeds to this node;

Step D344: select failure, ant agent death if next is jumped;

Step D35: forward direction ant agent task is finished;

Step D4: when forward direction agent arrived destination node, one of triggering for generating was inherited the back to agent of forward direction agent relevant information.The back oppositely arrives source node to the information of agent along original route from destination node, upgrades the information in the routing table simultaneously;

Step D41: in destination node, according to forward direction ant agent information, according to formula $J_P=\frac{{\mathrm{\&alpha;}}_{\mathrm{up}}}{{\mathrm{UU}}_P}+\frac{{\mathrm{\&alpha;}}_{\mathrm{np}}}{{\mathrm{UN}}_P}$ (wherein, α _Up, α _NpBe inclination weights to the user, 0＜α _Up, α _Np＜1, α _Up+ α _Np=1) calculating path evaluation of estimate J _P, and give the back of generation to agent; Give the back to ant agent with the path that forward direction ant agent finds;

Step D42: the back by the routing information of preserving, is oppositely jumped to upstream node to agent, then the plain table of lastest imformation; At present node, ant increases by 1 with route number of success counter, if ant agent has introduced the worldlet limit at present node, then upgrades worldlet limit table;

Step D43: judge whether the back arrives source node to ant agent, if no show then jumps to step D42;

Step D44: the back is compared to evaluation of estimate and the current path evaluation of estimate that ant agent carries the path,, then new route is saved as the present feasible path if agent carries the evaluation of estimate in path less than the current path evaluation of estimate;

Step D45: finish to the agent task back, calls ant group algorithm and finish.

Step D33 realizes that at present node the worldlet limit comprises:

Step D331: judge whether current agent is using the worldlet limit, if then directly take out the worldlet limit as next-hop node; Otherwise, jump to step D333;

Step D332: judge that can this next-hop node satisfy the user and ask constraint, if can, ant agent selects this node as next-hop node, preserve the QoS information and the cost information on limit between present node and this node, ant agent finishes in the present node behavior, proceeds to this next-hop node then; Otherwise, ant agent death;

Step D333: investigate the sequence number of ant agent, judge this agent whether for this iteration send in last, if not, then jump to step D34;

Step D334: investigate present node worldlet limit table, whether have the worldlet limit that arrives destination node, if there is no, then jump to step D34;

Step D335: deposit the worldlet limit in ant agent, and ant agent use worldlet limit is set, ant agent writes down this node address then, jumps to D331.

Step D342 realizes that the worldlet behavior comprises:

If the sequence number of ant agent is an even number, then select next-hop node at random; Otherwise, calculate and select next to jump, calculate the user satisfaction value computing formula of corresponding sides: $W_l={\mathrm{\&alpha;}}_{\mathrm{bw}}\&CenterDot;g_{\mathrm{bw}}^l+{\mathrm{\&alpha;}}_{\mathrm{dl}}\&CenterDot;g_{\mathrm{dl}}^l+{\mathrm{\&alpha;}}_{\mathrm{jt}}\&CenterDot;g_{\mathrm{jt}}^l+{\mathrm{\&alpha;}}_{\mathrm{ls}}\&CenterDot;g_{\mathrm{ls}}^l$ In the formula, α _Bw, α _Dl, α _JtAnd α _LsBe respectively the weight coefficient of each qos parameter, α _Bwα _Dlα _Jtα _Ls∈ [01], and α _Bw+ α _Dl+ α _Jt+ α _Ls=1, W _lBe the numerical value between 0 and 1, g _Bw ^lExpression bandwidth satisfaction, g _Dl ^lExpression time-delay satisfaction, g _Jt ^lExpression delay jitter satisfaction, g _Ls ^lRepresent the error rate satisfaction, calculate the route success rate of i node: $I_i=\frac{{\mathrm{rcs}}_i}{{\mathrm{rct}}_i},$ Rcs is successfully the routing times counter in the formula, and rct is that the total routing times counter of node is.When node was used in route, rct just increased 1, and after the success of this time route, rcs just increases 1.Here, ageing for guaranteeing, rcs, rct value are every some cycles Δ t _RcWith regard to zero clearing, calculate the progress of thinking of i node and this route destination address: 32 bit address are scanned relatively binary digit from left to right by turn,,, write down identical figure place M if difference just finishes if identical just the continuation scanned _Ik, phase recency then $V_i=\frac{M_{\mathrm{ik}}}{32}:$ Calculate next bar and select probability: pro _j=P _Ij* W _j* I _j* V _jP _IjBe corresponding N in the present node pheromones table _jPheromone concentration, W _jUser satisfaction value, the I of expression node j _jRoute success rate, the V of expression node j _jThe phase recency of expression node j is according to pro _j, select corresponding pro _jThe maximum next-hop node of value is jumped as next and is selected.

Step e examination path evaluation of estimate J _Path, find the path that meets user's request to comprise:

Step e 1: at the source node Δ that waits for a period of time _tAfter, examination path evaluation of estimate J _Path

Step e 2: if J _Path＜∞, then algorithm successfully finds the path that meets user's request, at source node current surviving path is added the worldlet table, goes to step K;

Step e 3: if J _PathWhether=∞ then judges IN less than TIN, if, then go to step D3, otherwise routing failure.

Step H initialization router register makes up multicast tree and comprises:

Step H1: the initialization router register is provided with iterations CN, iterations cn=0, multicast tree evaluation of estimate J _Tree=∞, the present feasible multicast tree is for empty;

Step H2: all group memberships by the descending arrangement of bandwidth request, are set pending group membership and gather W={v ₁, v ₂..., v _N-1, v _n, v _nBe pending group membership, n=1,2 ..., N, N belongs to natural number, processed group member set A=Φ, feasible path set P=Φ, wherein Φ is null set;

Step H3: get v _d∈ W utilizes the singlecast router algorithm based on the ant network, by v _sTo v _dSeek one and satisfy member v _dThe feasible path p of request constraint _dIf, do not find, then this time make up the multicast tree failure, jump to step J3;

Step H4: with node v _dFrom the W deletion, and add A;

Step H5: check feasible path p _dOn whether contain the group membership who is arranged in W, if do not have, then jump to step H7;

Step H6: if p _dOn contain the group membership who is arranged in W, judge that can these group memberships' request constraint at p _dBe met, the node that can be satisfied is deleted from W, and adds A;

Step H7: with feasible path p _dAdd set P;

Step H8:, then jump to step H1 if set W is not empty;

Step H9: the path among the P in the feasible path is combined into a multicast tree, and in the process of Cheng Shu, each group membership's request constraint all will be satisfied, and ring can not occur, otherwise this makes up the multicast tree failure, jumps to step J3.

Step J calculates multicast tree evaluation of estimate J _T, find out the present feasible multicast tree and comprise:

Step J1: calculate multicast tree evaluation of estimate J according to formula _T

Step J2: if J _T＜J _Tree, J _TreeBe the evaluation of estimate of present feasible multicast tree, then replace present feasible multicast tree, J with the multicast tree that calculates _Tree=J _T

Step J3:cn ← cn+1 is if cn＜CN jumps to step H;

Step J4: judge J _TreeWhether＜∞ sets up, if set up, and then algorithm success, otherwise algorithm failure.

Use the result of the inventive method as shown in table 2,

Load	Lighter	Generally	Heavier	Very heavy
					Use ant group method	?0.61784	?0.573928	?0.624177	?0507299
NS2-DV	?0.631488	?0.510569	?0.49874	?0.455068

Table 2 transfer of data satisfaction

Table 2 has been added up the satisfaction result under the heterogeneous networks load respectively, the transmission satisfaction of two kinds of method for routing was very nearly the same when load was very light, along with increasing the weight of of load, this paper method for routing begins obviously to be better than (DV) method of service range vector, and the transmission satisfaction value of two kinds of method for routing belongs to close again when load is very heavy.

Claims (4)

1. self-organizing QoS routing method based on ant algorithm, as follows:

Steps A: receive the data message that neighbor router sends;

Step B: whether the destination address according to data message is that unicast address judges whether type of message is unicast message;

It is characterized in that: according to step B is unicast message, execution in step C then, otherwise execution in step G;

Step C: enter clean culture modeling QoS method for routing;

Step D: the initialization router register, send forward direction ant agent pathfinding, call ant algorithm, wherein agent is responsible for collecting record current network state information;

Step e: examination path evaluation of estimate J _Path, find the path that meets user's request;

Step F: forward step K to;

Step G: enter multicast modeling QoS method for routing, given multicast request: R (v _s, v _d, Δ _Bw ^d, Δ _Dl ^d, Δ _Jl ^d, Δ _Ls ^d, p ^d), be its structure multicast tree, wherein a v _sRepresent source node, v _dRepresent destination node, Δ _Bw ^dRepresent between the bandwidth demand confining region Δ _Dl ^dRepresent between the delay requirement confining region Δ _Jt ^dRepresent between delay jitter demand confining region Δ _Ls ^dRepresent between the error rate desired region p ^dRepresentative of consumer is willing to pay and is used the upper limit;

Step H: the initialization router register makes up multicast tree;

Step I: multicast tree cost allocation;

After forming multicast tree, because selected limit selects for use the user shared, so also naturally by selecting for use the user to share jointly, the principle of sharing is rate: the part that the high more then user of expense that the user takies required pair of this paths alone shares in multicast tree is paid is big more;

The setting source node to the set of each group membership's the required paying in path is:

W _p={ pay ₁, Pay ₂..., pay _N-1, pay _nPay in the formula _nBe the required paying in each group membership's path, n=1,2 ..., N, N belongs to natural number, then i group membership v _iRequired multicast tree expense ratio of sharing is:

${\mathrm{per}}_d=\frac{{\mathrm{pay}}_i}{\underset{k\&Element;\{\mathrm{1,2},...n\}}{\mathrm{\&Sigma;}}{\mathrm{pay}}_k}$ I in the formula, k ∈ 1,2 ... n};

Step J: calculate multicast tree evaluation of estimate J _TFind out the present feasible multicast tree;

Step K: data message forwarding is arrived next hop router according to the present feasible multicast tree that calculates;

Calling ant algorithm among the described step D comprises:

Step D1: the initialization router register, maximum iterations TIN is set, iterations IN=0, the ant agent quantity AN that the each iteration of initialization sends, the agent that has sent counts an=0, path evaluation of estimate J _Path=∞, feasible path are empty;

Step D2:IN ← IN+1, source node is with interval delta _tSend AN forward direction ant agent pathfinding, agent of every transmission is with regard to an ← an+1, each forward direction agent of initialization, wherein: ant agent sequence number seq=an;

Step D3: forward direction agent record path, the node that lives through is preserved, write down relevant network state information simultaneously, forward direction ant agent is after source node is issued, and the node of each process in network is act of execution by the following step;

Step D31: judge whether current ant agent jumping figure transfinites, if, then ant agent death;

Step D32: if the direct next-hop node of present node has this route destination node, then investigate with this node between the limit whether satisfy the user and ask constraint, as satisfied, then ant agent jumps to destination node, forwards step D35 to;

Step D33: realize the worldlet limit at present node;

Step D34: carry out next at present node and jump selection;

Step D341:, route total degree counter is increased by 1 at present node;

Step D342: realize the worldlet behavior;

Step D343: if next jumping is selected successfully to return, then ant agent proceeds to this node;

Step D344: select failure, ant agent death if next is jumped;

Step D35: forward direction ant agent task is finished;

Step D4: when forward direction agent arrived destination node, one of triggering for generating was inherited the back to agent of forward direction agent relevant information, and the back oppositely arrives source node to the information of agent along original route from destination node, upgrades the information in the routing table simultaneously;

Step D41: in destination node, according to forward direction ant agent information, according to formula Calculating path evaluation of estimate J _p, UU in the formula _pBe the user's effectiveness on path or the multicast tree, UN _pBe network provider effectiveness then, and give the back of generation to agent; α wherein _Up, α _NpBe inclination weights to the user, 0＜α _Up, α _Np＜1, α _Up+ α _Np=1, give the back to ant agent with the path that forward direction ant agent finds;

Step D42: the back by the routing information of preserving, is oppositely jumped to upstream node to agent, then the plain table of lastest imformation; At present node, ant increases by 1 with route number of success counter, if ant agent has introduced the worldlet limit at present node, then upgrades worldlet limit table;

Step D43: judge whether the back arrives source node to ant agent, if no show then jumps to step D42;

Step D44: the back is compared to evaluation of estimate and the current path evaluation of estimate that ant agent carries the path,, then new route is saved as the present feasible path if agent carries the evaluation of estimate in path less than the current path evaluation of estimate;

Step D45: finish to the agent task back, calls ant algorithm and finish;

Described step H initialization router register makes up multicast tree and comprises:

Step H1: the initialization router register is provided with iterations CN, iterations cn=0, multicast tree evaluation of estimate J _Tree=∞, the present feasible multicast tree is for empty;

Step H2: all group memberships by the descending arrangement of bandwidth request, are set pending group membership and gather W={v ₁, v ₂..., v _N-1, v _n, v _nBe pending group membership, n=1,2 ..., N, N belongs to natural number, processed group member set A=Φ, feasible path set P=Φ, wherein Φ is null set;

Step H3: get v _d∈ W utilizes described clean culture modeling QoS method for routing, by v _sTo v _dSeek one and satisfy member v _dThe feasible path P of request constraint _dIf, do not find, then this time make up the multicast tree failure, jump to step J3;

Step H4: with node v _dFrom the W deletion, and add A;

Step H5: check feasible path P _dWhether contain the group membership who is arranged in W,, then jump to step H7 if do not have;

Step H6: if P _dOn contain the group membership who is arranged in W, judge that can these group memberships' request constraint at P _dBe met, the node that can be satisfied is deleted from W, and adds A;

Step H7: with feasible path P _dAdd set P;

Step H8:, then jump to step H1 if set W is not empty;

Step H9: the path among the P in the feasible path is combined into a multicast tree, and in the process of Cheng Shu, each group membership's request constraint all will be satisfied, and ring can not occur, otherwise this makes up the multicast tree failure, jumps to step J3;

Described step J calculates multicast tree evaluation of estimate J _T, find out the present feasible multicast tree and comprise:

Step J1: calculate multicast tree evaluation of estimate J according to formula _T

Step J2: if J _T＜J _Tree, J _TreeBe the evaluation of estimate of present feasible multicast tree, then replace present feasible multicast tree, J with the multicast tree that calculates _Tree=J _T

Step J 3:cn ← cn+1 is if cn＜CN jumps to step H;

Step J4: judge J _TreeWhether＜∞ sets up, if set up, and then algorithm success, otherwise algorithm failure.

2. the described a kind of self-organizing QoS routing method based on ant algorithm of claim 1 is characterized in that described step D33 realizes that at present node the worldlet limit comprises:

Step D331: judge whether current agent is using the worldlet limit, if then directly take out the worldlet limit as next-hop node; Otherwise, jump to step D333;

Step D332: judge that can this next-hop node satisfy the user and ask constraint, if can, ant agent selects this node as next-hop node, preserve the QoS information and the cost information on limit between present node and this node, ant agent finishes in the present node behavior, proceeds to this next-hop node then; Otherwise, ant agent death;

Step D333: investigate the sequence number of ant agent, judge that whether this agent is this iteration last in sending, if not, then jump to step D34;

Step D334: investigate present node worldlet limit table, whether have the worldlet limit that arrives destination node, if there is no, then jump to step D34;

Step D335: deposit the worldlet limit in ant agent, and ant agent use worldlet limit is set, ant agent writes down this node address then, jumps to D331.

3. the described a kind of self-organizing QoS routing method based on ant algorithm of claim 1 is characterized in that described step D342 realizes that the worldlet behavior comprises:

If the sequence number of ant agent is an even number, then select next-hop node at random; Otherwise, calculate and select next to jump, calculate the user satisfaction value computing formula of corresponding sides:

In the formula, α _Bw, α _Dl, α _JtAnd α _LsBe respectively the weight coefficient of each qos parameter, α _Bw, α _Dl, α _Jt, α _Ls∈ [0,1], and α _Bw+ α _Dl+ α _Jt+ α _Ls=1, W _lBe the numerical value between 0 and 1, g _Bw ^lExpression bandwidth satisfaction, g _Dl ^lExpression time-delay satisfaction, g _Jt ^lExpression delay jitter satisfaction, g _Ls ^lRepresent the error rate satisfaction, calculate the route success rate of i node:

Rcs is successfully the routing times counter in the formula, and rct is the total routing times counter of node, and when node was used in route, rct just increased 1, and after the success of this time route, rcs just increases 1, and is ageing for guaranteeing, rcs, rct value are every some cycles Δ t _RcWith regard to zero clearing, calculate the recency mutually of i node and this route destination address:,,, write down identical figure place M if differently just finish if identically just continue scanning with 32 bit address scanning binary digit relatively by turn from left to right _Ik, phase recency then

Calculate next bar and select probability: pro _j=P _Ij* W _j* I _j* V _jP _IjBe corresponding N in the present node pheromones table _jPheromone concentration, N _jRepresent j next hop neighbor, W _jUser satisfaction value, the I of expression node j _jRoute success rate, the V of expression node j _jThe phase recency of expression node j is according to pro _j, select corresponding pro _jThe maximum next-hop node of value is jumped as next and is selected.

4. the described a kind of self-organizing QoS routing method based on ant algorithm of claim 1 is characterized in that described step e examination path evaluation of estimate J _Path, find the path that meets user's request to comprise:

Step e 1: at the source node Δ that waits for a period of time _tAfter, examination path evaluation of estimate J _Path

Step e 2: if J _Path＜∞, then algorithm successfully finds the path that meets user's request, at source node current surviving path is added the worldlet table, goes to step K;

Step e 3: if J _PathWhether=∞ then judges IN less than TIN, if, then go to step D3, otherwise routing failure.

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