CN101179497A - Method of establishing novel Ad hoc network node model - Google Patents

Abstract

The invention relates to an establishment method of a novel Ad hoc network node mode. The method includes the following steps: a novel network node mode with a better utilization rate of node is tablished, and according to relevant characteristics of a queuing theory, obedience index distributions of a transmission rate and a receiving rate are obtained, and a reasonable arrangement with restrict condition is carried out for a plurality of parameters of the mode. According to that a utilziaiton rate of a buffer queue for the node is in a good state according to the restrict condition, the mode of the network node is determined. The invention considers an effect on the speed of receiving a data packet by the node as well as on the speed of transferring the data packet by the node caused by the size of the buffer queue. When the transmission rate and the receiving rate meet certain limited conditions, the utilization efficiency of the node buffer queue is best, and an ability of transmitting data packet is also the best state. The mode has significance in researching the effect on data packet processing caused by the characteristics of the node.

Description

A kind of method for building up of new A d hoc network node model

Technical field

The invention belongs to network calculations, communication technical field, is specifically on the basis of analyzing existing Adhoc network model, and proposes a kind of method for building up of new A d hoc network node model.

Background technology

Ad hoc network (MANET) is a kind of dynamic multi-hop wireless network, is made up of the mobile node of one group of sharing wireless channel.In recent years, because its self-organizing characteristic quickly and easily and do not need to preset characteristics such as network infrastructure, wireless Ad hoc network has obtained extensive concern, and obtaining more and more widely application, become the important directions that mobile communication technology advances, and will in the communication technology in future, occupy critical role.In Ad hoc network, when two mobile hosts were in communication coverage each other, they can direct communication.But,, the main frame of two apart from each others needs to realize by the forwarding of the mobile host between them if will communicating because the communication coverage of mobile host is limited.Therefore in Ad hoc network, each main frame still is a router simultaneously, is undertaking the work of seeking route and E-Packeting.In Ad hoc network, the communication range of each main frame is limited, so route generally all is made up of multi-hop, and packet could arrive the destination by the forwarding of a plurality of main frames, so Ad hoc network is also referred to as multi-hop wireless network.Arrive the process of destination node from sending node at packet, will be through the forwarding of many intermediate nodes, and packet is when arriving each intermediate node, this node is all wanted earlier it to be stored in the buffer queue of node, then after after a while, again this packet is forwarded, up to destination node.From the repeating process of packet as can be seen, the size of node self characteristics such as buffer queue is influential to the forwarding of packet, therefore set up proper A d hoc network node model, make this model adapt to the storage and the forwarding of packet, and to make the self-characteristic of node perform to optimum degree be necessary.

Summary of the invention

When the purpose of this invention is to provide a kind of length and being a fixed value, guarantee that packet in the buffer queue neither loses and make the method for building up of the novel Ad hoc network node model that buffer queue is fully used at buffer queue.

To achieve these goals, the method applied in the present invention is:

First step: analysis node sends packet and receives the process of packet, point out that node sends the influence of the size of the transmission rate of packet and the receiving velocity that receives packet to the node buffer queue, thereby set up a kind of new network nodal analysis method, in this model, the utilization ratio of node is better;

Second step: by the analysis of packet procedures that node is transmitted and receive data, this model is equal to queueing theory opinion system, according to the related properties of queueing theory, draws transmission rate and receiving velocity obeys index distribution, thereby provide fundamental basis for setting up model;

Third step: for drawing the general conclusion of tool, some parameters in this model are done reasonably supposition, think the equal in length of storage intransit buffering formation of each node in the network, the transmission rate U of node is less than fixed value M ₀, receiving velocity V is less than a fixed value M ₁And other constraints;

The 4th step: because the transmission rate U of node is less than fixed value M ₀, receiving velocity V is less than fixed value M ₁Thereby, obtain the scope that transmission rate and receiving velocity are satisfied, draw first constraints between the two;

The 5th step:, find out transmission rate and second constraints accepting speed when node buffer queue utilization ratio P reaches the best according to the character of exponential distribution and queueing theory;

The 6th step: according to T and T ₁The hypothesis of being done when data wrap in stand-by period T in the formation when surpassing a fixed value, is thought this data-bag lost, works as T ₁When surpassing certain fixed value, also think this data-bag lost, thereby draw transmission rate and accept the 3rd constraints of speed;

The 7th step: three constraintss according to above transmission rate and receiving velocity draw in this case, the buffer queue utilization ratio of node is in better state, thereby determine a kind of new network nodal analysis method, in this model, utilization ratio the best of the buffer queue of node, the transmission performance of corresponding the whole network also reaches state preferably.

The present invention is on the basis of the characteristics of analyzing Ad hoc network, the nodal analysis method that a kind of suitable packet is transmitted has been proposed, this model has considered that the size of node self buffer queue receives the speed of packet to node, the influence of the speed of node for data forwarding bag, drawn in the buffer queue size fixing, transmission rate and receiving velocity satisfy under the situation of certain qualifications, the relation between two kinds of speed.When transmission rate and receiving velocity satisfied this relation, it is best that the utilization ratio of node buffer queue reaches, and the ability of transmitting packet also is in optimum state.This model has important value for the self-characteristic of research node to the influence of handle packet, simultaneously, has also improved important reference frame for the transmission performance that improves the Adhoc network.

Description of drawings

Fig. 1 is queue theory model figure.

The nodal analysis method figure that Fig. 2 sets up for the present invention.

Fig. 3 is a flow chart of the present invention.

Embodiment

Be described in further detail below in conjunction with the present invention of accompanying drawing team

In Ad hoc network, when packet is delivered to data link layer from network layer, be stored in the buffer queue of node, after in buffer queue, staying for some time, be forwarded away from data link layer again, when packet when network layer delivers to that the speed of data link layer is very big to be had little time to transmit, will certainly cause losing of packet, and the speed that is forwarded away from data link layer when packet is when very little, the buffer queue of node is in idle condition again, can not be fully utilized, therefore by someway, when the length of buffer queue was a fixed value, the packet in the assurance buffer queue is neither lost and made buffer queue be fully used was the efficient maximum, therefore be necessary the relation between definite these two kinds of speed, thereby set up a kind of new Ad hoc network node model.

Queuing is the phenomenon that people often run in daily life, does shopping to the shop as client, and patient sees a doctor to hospital, people's getting on-off automobile, and the fault machine down is waited to repair etc. and usually all will be lined up.The persons or things of queuing is referred to as client, for the persons or things of customer service is called service organization's (waiter or information desk etc.).Client lines up and requires the process or the phenomenon of service to be called queuing system or service system.Because in general the moment that client arrives all is at random with the time of serving, so service system claims stochastic service system again, that summarizes says, queueing theory is exactly by the service object being arrived and the statistical research of service time, draw the statistical law of these quantitative indexes (stand-by period, queue length, busy period length etc.), improve the structure of service system or reorganize serviced object according to these rules then, make service system can satisfy service object's needs, can make most economical or some index optimum of expense of mechanism again.Queue theory model as shown in Figure 1.

Three elements of queuing system:

(1) input process: client arrives according to the rule that distributes according to certain mathematical statistics.

(2) queue discipline: client waits in line service according to certain rule.

(3) service organization: comprise the setting of handling service organization, the quantity of information desk, service manner service times such as distributing.

Before further describing, at first some symbols are described:

System mode S ₀: i.e. queuing system client's quantity;

N (t): client's quantity in time t queuing system;

Queue length L: the quantity of waiting for the client of service;

Pn (t):, n client's probability is arranged just in the queuing system at time t;

S: the number of information desk;

λ n: the average arrival rate when there be n client in system (client's number that the unit interval on average arrives is an average arrival rate);

μ _n: the average arrival rate when there be n client in system;

λ: to any n all is the average arrival rate of constant;

U: to any n all is the average arrival rate of constant;

1/ λ: expectation interarrival time;

1/ μ: expected service time;

ρ: service intensity, or claim usage factor.

Be client's the behavior table and the classification chart of formation and service organization below

Client's behavior table: table 1

The client source	Customer quantity	Client's behaviour assumption is
			Limited	Limited	Can not leave before the service
Infinitely	Infinitely	When seeing that formation is very long, leave

The classification chart of formation and service organization: table 2

Capacity of queue	Queue discipline	Service organization
			Limited	Service earlier first	Information desk quantity
Infinitely	Service at random	Distribute service time (index, constant)

Client's arrival rate and leave the speed obeys index distribution, the probability of exponential distribution is:

p(T≤t)＝1-e ^-at…………………………………………………………………(1)

Wherein a is the parameter of exponential distribution, and t is a stochastic variable, and p is the probable value of stochastic variable when the T≤t.

f _T(t)=ae ^-at, when t 〉=0 ... (2)

f _T(t)=0, when t≤0 ... (3)

Desired value E is:

$E\left(t\right)=\frac{1}{a}......\left(4\right)$

The classification of formation in the queueing theory:

(1) M/M/1 model: an information desk, arrival rate λ and service rate μ be obeys index distribution.

(2) M/M/1/N/ ∞ model: single information desk, regular length, arrival rate λ and service rate μ be obeys index distribution.

(3) M/M/c model: a plurality of information desks, arrival rate λ and service rate μ be obeys index distribution.

When specifying the method for building up of model, at first some symbols are defined:

(1) u: node sends the speed of packet.V: node receives the speed of packet;

(2) L _q: the total length of buffer queue;

(3) L: buffer queue on average to length;

(4) L ₀: the average length of the formation that the packet that sends over formed before entering buffer queue;

(5) L ₁: when the utilization ratio of buffer queue reaches the best, the packet number that wherein comprises;

(5) P _n(t): at time t constantly, the probability of n packet is arranged just in the formation;

(6) ρ: the busy degree of formation is the ratio of u and v;

(7) T: the time that the wait of each packet in formation transmitted;

(8) T ₁: after packet arrives some nodes, enter the buffer queue stand-by period before.

Preceding some condition enactments of carrying out of the foundation of model to model:

(1) length of the storage intransit buffering formation of each node in the network all equates;

(2) hardware configuration of each node itself is identical with device, thereby thinks that the performance of each node is roughly the same;

(3) total length of buffer queue is the maximum packet number that can hold, and average queue length is the average data bag number in the formation in the ordinary course of things;

(4) transmission rate of each node and receiving velocity are subjected to the Effect on Performance of node own, and its value can not be arbitrarily, suppose that the transmission rate U of node is less than fixed value M ₀, receiving velocity V is less than a fixed value M ₁

(5) T and T ₁Value can not be arbitrarily, the stand-by period T that wraps in the formation when data surpasses a fixed value, is assumed to be T ₀The time, then think this data-bag lost, no longer transmit this packet, same, work as T ₁Surpass certain fixed value such as T ₂The time, also think and need transmit this packet again by this data-bag lost.

(6) 80 percent of the maximum packet number that can hold for it of the number of supposing packet in the buffer queue is L ₁=0.8L _qThe time, it is best that the utilization ratio of buffer queue reaches.

The method for building up of model:

Relevant knowledge by queuing theory can know, when a node when the another one node sends packet and this node when other node is accepted packet, can think the obeys index distribution that transmission rate u and receiving velocity v are approximate.Its distribution function is respectively:

p(U≤u)＝1-e ^-at，………………………………………………………(5)

p(V≤v)＝1-e ^-at…………………………………………………………(6)

Wherein a is the parameter of exponential distribution, and t is a stochastic variable.

Then have

L＝u×T……………………………………………………………………(7)

L ₀＝u×T ₁…………………………………………………………………(8)

$T=T_1+\frac{1}{u}......\left(9\right)$

Have the character of queuing theory and exponential distribution to get:

$L=\frac{\mathrm{\ρ}}{1-\mathrm{\ρ}}......\left(10\right)$

$L_0=\frac{{\mathrm{\ρ}}^2}{1-\mathrm{\ρ}}......\left(11\right)$

Can get by formula 7 and formula 10

$T=\frac{1}{u(1-\mathrm{\ρ})}......\left(12\right)$

As a same reason, can get by formula 8 and formula 11

$T_1=\frac{\mathrm{\ρ}}{u(1-\mathrm{\ρ})}......\left(13\right)$

Property of probability by exponential distribution can get

p _n(t)＝(1-ρ)ρ ⁿ……………………………………………(14)

According to setting, T is less than M ₀, T ₁Be less than M ₁That is:

$T=\frac{1}{u(1-\mathrm{\ρ})}......\left(15\right)$

$T_1=\frac{\mathrm{\ρ}}{u(1-\mathrm{\ρ})}......\left(16\right)$

Work as n=L ₁The time, can get by formula 14:

p _n(t)＝(1-ρ)ρ ^L1……………………………………………………(17)

Definition according to ρ:

$\mathrm{\ρ}=\frac{u}{v}......\left(18\right)$

By formula 15 and 16 and formula 18 can get:

$T=\frac{1}{\mathrm{\μ}(1-\frac{\mathrm{\μ}}{v})}......\left(19\right)$

$T_1=\frac{1}{\mathrm{\υ}(1-\frac{\mathrm{\μ}}{\mathrm{\υ}})}......\left(20\right)$

By T and T ₁The value that the constraints that is satisfied can obtain u and v should satisfy:

$\frac{1}{\mathrm{\μ}(1-\frac{\mathrm{\μ}}{v})}\≤T_0......\left(21\right)$

$\frac{1}{\mathrm{\υ}(1-\frac{\mathrm{\μ}}{\mathrm{\υ}})}\≤T_2......\left(22\right)$

For formula 17, the length when formation is L certainly ₁Probable value be the bigger the better.

Comprehensive above the analysis, by formula 17, formula 21 and formula 22 and u≤M ₀, v≤M ₁, can be met under these qualificationss, the ratio relation of transmission rate u and receiving velocity v makes in this case the utilization ratio P of the buffer queue of node _n(t) be in optimum state.

The content that is not described in detail in this specification belongs to this area professional and technical personnel's known prior art.

Claims (1)

1. the method for building up of a new A d hoc network node model, the method that is adopted is:

First step: analysis node sends packet and receives the process of packet, point out that node sends the influence of the size of the transmission rate of packet and the receiving velocity that receives packet to the node buffer queue, thereby set up a kind of network node model, in this model, the utilization ratio of node is better;

Second step: by the analysis of packet procedures that node is transmitted and receive data, this model is equal to queueing theory opinion system, according to the related properties of queueing theory, draws transmission rate and receiving velocity obeys index distribution, thereby provide fundamental basis for setting up model;

Third step: for drawing the general conclusion of tool, some parameters in this model are done reasonably to set, think the equal in length of storage intransit buffering formation of each node in the network, the transmission rate U of node is less than fixed value M ₀, receiving velocity V is less than a fixed value M ₁And other constraints;

The 4th step: because the transmission rate U of node is less than fixed value M ₀, receiving velocity V is less than fixed value M ₁Thereby, obtain the scope that transmission rate and receiving velocity are satisfied, draw first constraints between the two;

The 5th step:, find out transmission rate and second constraints accepting speed when node buffer queue utilization ratio P reaches the best according to the character of exponential distribution and queueing theory;

The 6th step: according to T and T ₁The setting of being done when data wrap in stand-by period T in the formation when surpassing a fixed value, is thought this data-bag lost, works as T ₁When surpassing certain fixed value, also think this data-bag lost, thereby draw transmission rate and accept the 3rd constraints of speed;

The 7th step: three constraintss according to above transmission rate and receiving velocity draw in this case, the buffer queue utilization ratio of node is in better state, thereby determine network node model, in this model, utilization ratio the best of the buffer queue of node, the transmission performance of corresponding the whole network also reaches state preferably.

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