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in routing table. When search resources CAN uses greedy<br />

algorithm and send the messages to the neighbor node<br />

which is nearest to target according the routing table.<br />

Each node has O(d) neighbor nodes, and the hops of<br />

searching is O(dN 1/d )[14]. The topology of CAN is shown<br />

in figure 3.<br />

The biggest problem of DHT structure is that the<br />

mechanism of maintenance is too complex. In particular<br />

while there are nodes always join or quit the system, it<br />

becomes difficult to maintain. The other shortage of<br />

DHT is that it supports exact keywords search only. It<br />

can’t support the content of complex queries.<br />

D Hybrid Structure P2P<br />

Hybrid structure P2P integrates the advantages of the<br />

centralized topology and distributed topology. In this<br />

system, there are some supernodes which have high<br />

performance such as the ability of compute, bandwidth,<br />

memory and so on. These supernodes have stored the<br />

information of other nodes. Discovery algorithm is<br />

carried out between supernodes only and then the<br />

certain supernode forward the query to the specific<br />

bottom nodes. Hybrid structure P2P is a<br />

semi-distributed and hierarchical structure. Super nodes<br />

make up a high-speed forwarding layer and this super<br />

nodes and normal nodes constitute several levels. The<br />

most typical case is KaZaa. This topology is shown in<br />

figure 4.<br />

Figure 4: hybrid structured P2P<br />

The advantages of hybrid structured are that the<br />

performance and scalability of it can reach a preferable<br />

level. Of course it also relies on the supernodes and it is<br />

easy to be attacked. But as a compromising method<br />

although all aspects of its performance has failed to<br />

reach the optimal level of the current structures, it has<br />

more practical value and attracted many researchers.<br />

The company CA’s statistics indicate that there are<br />

more than 250 million times download on KaZaa. Using<br />

KaZaa to transport files consumes 40 percent of the<br />

Internet bandwidth. It was so successful because it<br />

combines the advantages of Napster and Gnutella. It<br />

uses the distributed structure of Gnutella and so it has<br />

high scalability. It selects nodes which have high<br />

peformances and let these nodes become super nodes.<br />

These super nodes store the information about the<br />

bottom nodes nearest to them and they connect together<br />

to make up an overlay network. As the supernodes have<br />

indexing about certain bottom nodes, the performance<br />

of searching has been improved greatly.<br />

Now, many studies are based on hybrid structure. The<br />

focus is using relevant estimate system and specific trust<br />

computing to select right nodes to be supernodes and<br />

how to dispose the problem while supernodes are<br />

attacked or disabled. Literatures[15] is a typical<br />

document about this problem.<br />

Ⅲ AN IMPROVEMENT BASED ON GUETELLA<br />

It is found that searching always focus on a few<br />

popular resources. So there is a model of probabilistic<br />

transmittance based on Guntella been put forward.<br />

In this model, every node in this system builds a<br />

routing table about popular resources on the basis of the<br />

searching which relevant to itself. Nodes send messages<br />

according to the table.<br />

While they echo ping or query the messages of Pong<br />

or Queryhit should take some additional information<br />

such as processing power, bandwidth, current load,<br />

online time, delay of connection and so on. Source node<br />

renews its routing table after received a response from<br />

target node. The additional information make up a<br />

vector Y, and all components can be divided in two<br />

kinds, positive component (bandwidth), negative<br />

component (delay of connection) based on practical<br />

meaning. In order to be easy to dispose we let all<br />

negative components to be inverse to themself and there<br />

a vector X in which all components is positive<br />

components. Routing table has build n item of routing<br />

of most popular resources based on the ability of the<br />

node such as memory. The popular resources are<br />

towards to a certain node. Every keywords has m targets<br />

and it can be controlled to send c request (c ≤ m, while<br />

c=m sends request to all targets directly). With respect<br />

to a certain target i we pull-in a parameter of<br />

transmission k i . it can be compute by iteration shown in<br />

equation 1.<br />

k i n =f(X,ki n −1<br />

) 1<br />

The function f() needs to be able to correctly reflect the<br />

impact to the probability of every component as<br />

accurately as possible. There are two basic conditions<br />

listed as follows.<br />

∂f<br />

Condition 1: ≥ 0<br />

∂xi<br />

2<br />

Condition 2:<br />

∂ f<br />

≤0<br />

2<br />

∂x<br />

i<br />

( x i<br />

is any component of X)<br />

The probability of the target i is :<br />

i<br />

j<br />

⎧⎪<br />

( k × c)/ ∑ k ( Pi<br />

≤1)<br />

⎫⎪<br />

2<br />

Pi<br />

= ⎨ ⎬<br />

⎩⎪<br />

1( else)<br />

⎭⎪<br />

(j∈ N, N is the set of target nodes toward the certain<br />

keywords)<br />

In theory, nodes in this model transmitting messages<br />

are based on the routing tables not using flooding and so<br />

it has these advantages such as reducing the demand of<br />

bandwidth, improving the efficiency of searching and<br />

225

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