DYNAMIC SEARCH ALGORITHM IN UNSTRUCTURED PEER-TO-PEER NETWORKS--PARALLEL AND DISTRIBU
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13-01-2010, 07:44 AM


DYNAMIC SEARCH ALGORITHM IN UNSTRUCTURED PEER-TO-PEER NETWORKS--PARALLEL AND DISTRIBUTED SYSTEMS

Designing efficient search algorithms is a key challenge in unstructured peer-to-peer networks. Flooding and random walk (RW) are two typical search algorithms. Flooding searches aggressively and covers the most nodes. However, it generates a large amount of query messages and, thus, does not scale. On the contrary, RW searches conservatively. It only generates a fixed amount of query messages at each hop but would take longer search time. We propose the dynamic search (DS) algorithm, which is a generalization of flooding and RW. DS takes advantage of various contexts under which each previous search algorithm performs well. It resembles flooding for short-term search and RW for long-term search. Moreover, DS could be further combined with knowledge-based search mechanisms to improve the search performance. We analyze the performance of DS based on some performance metrics including the success rate, search time, query hits, query messages, query efficiency, and search efficiency. Numerical results show that DS provides a good tradeoff between search performance and cost. On average, DS performs about 25 times better than flooding and 58 times better than RW in power-law graphs, and about 186 times better than flooding and 120 times better than RW in bimodal topologies.

Technology to use:JAVA
Use Search at http://topicideas.net/search.php wisely To Get Information About Project Topic and Seminar ideas with report/source code along pdf and ppt presenaion
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varaprasad1237
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03-02-2011, 11:47 AM

in this project and implimentation what is the result analysis.
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mahesh9741
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29-04-2011, 08:49 PM

Hi Some one could send me some detailed documentation of the paper
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11-05-2011, 12:43 PM


.doc   Report.doc (Size: 88 KB / Downloads: 114)
Dynamic Search Algorithm in Unstructured Peer-to-Peer Networks
Abstract

Designing efficient search algorithms is a key challenge in unstructured peer-to-peer networks. Flooding and random walk (RW) are two typical search algorithms. Flooding searches aggressively and covers the most nodes. However, it generates a large amount of query messages and, thus, does not scale. On the contrary, RW searches conservatively. It only generates a fixed amount of query messages at each hop but would take longer search time. We propose the dynamic search (DS) algorithm, which is a generalization of flooding and RW. DS takes advantage of various contexts under which each previous search algorithm performs well. It resembles flooding for short-term search and RW for long-term search. Moreover, DS could be further combined with knowledge-based search mechanisms to improve the search performance. We analyze the performance of DS based on some performance metrics including the success rate, search time, query hits, query messages, query efficiency, and search efficiency. Numerical results show that DS provides a good tradeoff between search performance and cost. On average, DS performs about 25 times better than flooding and 58 times better than RW in power-law graphs, and about 186 times better than flooding and 120 times better than RW in bimodal topologies.
Objective:
In this paper, we propose the dynamic search (DS) algorithm, which is a generalization of flooding and RW. DS overcomes the disadvantages of flooding and RW and takes advantage of different contexts under which each search algorithm performs well. The operation of DS resembles flooding for the short-term search and RW for the long-term search.
Existing System:
Flooding and RW are two typical examples of blind search algorithms by which query messages are sent to neighbors without any knowledge about the possible locations of the queried resources or any preference for the directions to send. Some other blind search algorithms include modified BFS (MBFS) , directed BFS expanding ring and random periodical flooding (RPF).These algorithms try to modify the operation of flooding to improve the efficiency. However, they still generate a large amount of query messages.
DISADVANTAGES:
In the existing system search cost is high.
It produces considerable query messages even when the resource distribution is scarce.
The search is especially inefficient when the target is far from the query source because the number of query messages would grow exponentially with the hop counts.
It’s more time consuming one.
Proposed System:
In this paper, we propose the dynamic search (DS) algorithm, which is a generalization of flooding and RW. DS overcomes the disadvantages of flooding and RW and takes advantage of different contexts under which each search algorithm performs well. The operation of DS resembles flooding for the short-term search and RW for the long-term search. In order to analyze the performance of DS, we apply the random graphs as the models of network topologies and adopt the probability generating functions to model the link degree distribution. We evaluate the performance of search algorithms in accordance with some performance metrics including the success rate, search time, number of query hits, and number of query messages, query efficiency, and search efficiency.
ADVANTAGES:
It reduces a search time.
It takes advantages of Flooding based and random walk technique.
Knowledge-based search algorithms take advantage of the knowledge learned from previous search results and route query messages with different weights based on the knowledge.
System Requirements:
Hardware requirements:

Processor : Any Processor above 500 MHz.
Ram : 128Mb.
Hard Disk : 10 Gb.
Compact Disk : 650 Mb.
Input device : Standard Keyboard and Mouse.
Output device : VGA and High Resolution Monitor.
Software requirements:
Operating System : Windows Family.
Language : JDK 1.5
Data Bases : Microsoft Sql Server
Front End : Java Swing
PROBLEM DEFINATION:
IN unstructured peer-to-peer (P2P) networks, each node does not have global information about the whole topology and the location of queried resources. Because of the dynamic property of unstructured P2P networks, correctly capturing global behavior is also difficult . Search algorithms provide the capabilities to locate the queried resources and to route the message to the target node. Thus, the efficiency of search algorithms is critical to the performance of unstructured P2P networks.
Previous works about search algorithms in unstructured P2P networks can be classified into two categories: breadth first search (BFS)-based methods, and depth first search (DFS)-based methods. These two types of search algorithms tend to be inefficient, either generating too much load on the system, or not meeting users’ requirements. Flooding, which belongs to BFS-based methods, is the default search algorithm for Gnutella network. By this method, the query source sends its query messages to all of its neighbors. When a node receives a query message, it first checks if it has the queried resource. If yes, it sends a response back to the query source to indicate a query hit. Otherwise, it sends the query messages to all of its neighbors, except for the one the query message comes from. The drawback of flooding is the search cost. It produces considerable query messages even when the resource distribution is scarce. The search is especially inefficient when the target is far from the query source because the number of query messages would grow exponentially with the hop counts. Fig. 1 illustrates the operation of flooding. The link degree of each vertex in this graph is 4. If the network grows unlimited from the query source, the number of query messages generated by flooding at each hop would be 4, 12, 36, . . . , respectively. If the queried resource locates at one of the third neighbors, it takes 4, 12, 36, 52 query messages to get just one query hit.
On the other hand, random walk (RW) is a conservative search algorithm, which belongs to DFS-based methods. By RW, the query source just sends one query message (walker) to one of its neighbors. If this neighbor does not own the queried resource, it keeps on sending the walker to one of its neighbors, except for the one the query message comes from, and thus, the search cost is reduced. The main drawback of RW is the long search time. Since RW only visits one node for each hop, the coverage of RW grows linearly with hop counts, which is slow compared with the exponential growth of the coverage of flooding. Moreover, the success rate of each query by RW is also low due to the same coverage issue. Increasing the number of walkers might help improve the search time and success rate, but the effect is limited due to the link degree and redundant path.
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mayu9741
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#5
08-06-2011, 11:42 PM

Hello sir can any one send the detailed code and documentation for the project and implimentation
Sir i'm very thankful if any body provides the details
my mail id mahesh.tp49@gmail.com[/color]
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rajmohan29
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#6
29-12-2011, 04:50 PM

i need data base query fo this project and implimentation
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seminar paper
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#7
20-02-2012, 02:54 PM

to get information about the topic DYNAMIC SEARCH ALGORITHM IN UNSTRUCTURED PEER-TO-PEER NETWORKS full report ppt and related topic refer the link bellow

topicideashow-to-dynamic-search-algorithm-in-unstructured-peer-to-peer-networks-parallel-and-distribu

topicideashow-to-dynamic-search-algorithm-in-unstructured-peer-to-peer-networks

topicideashow-to-dynamic-search-algorithm-in-unstructured-peer-to-peer-networks--14433
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#8
28-03-2012, 11:49 AM

DYNAMIC SEARCH ALGORITHM IN UNSTRUCTURED PEER-TO-PEER NETWORKS--PARALLEL AND DISTRIBU


.pdf   D94942014a.pdf (Size: 443.12 KB / Downloads: 73)


I. INTRODUCTION
The design of search algorithms is critical to the performance of
unstructured peer-to-peer (P2P) networks. In the unstructured P2P
networks, each node does not have the global information about the
whole topology and the location of queried resources. Therefore, it
depends on the search algorithms to help locating the queried resource
and routing the message to the target node.
Related works about the search issue in unstructured P2P networks
can be classified into two categories: breadth first search (BFS)-based
methods, and depth first search (DFS)-based methods. Flooding,
which belongs to the BFS-based methods, is the default search
algorithm for Gnutella network [1]. In this method, the query source
sends the query message to all of its neighbors. When a node receives
a query message, it first checks if it has the queried resource.



II. DYNAMIC SEARCH ALGORITHM
In this section we provide a detailed description of DS. DS is a
generalization of flooding, MBFS, and RW. There are two phases in
DS algorithm, and each phase has different searching strategy. The
choice of search strategy at each phase depends on the hop count h of
the query messages and the decision threshold n of DS.
Phase 1. When h ≦ n:
At this phase, the DS acts as flooding or MBFS. The number of
neighbors that the query source sends the query messages to depends
on the pre-defined transmission probability p. If the link degree of this
query source is d, it would only send the query messages to pd
neighbors. When p is equal to 1, the DS resembles flooding. Otherwise
it operates as MBFS with transmission probability p.



III. PERFORMANCE ANALYSIS
In this section we present the performance analysis of DS. We apply
Newman’s power-law random graph as the network topology, adopt
the generating functions to model the link degree distribution [11], and
analyze the DS based on some performance metrics, including the
guaranteed search time, query hits, query messages, success rate, and
search efficiency.



V. CONCLUSION
In this paper we propose the DS algorithm which is a generalization
of flooding, MBFS, and RW. The DS algorithm overcomes the
different disadvantages of flooding and RW, and takes advantage of
different contexts under which each search algorithm performs well.
The operation of DS resembles flooding or MBFS for the short-term
search, and RW for the long-term search. We analyze the performance
of DS based on some metrics including the average search time,
guaranteed search time, number of query hits, number of query
messages, success rate, and search efficiency. The main objective is to
obtain the effects of the parameters of DS. Numerical results show that
proper setting of the parameters of DS can obtain short guaranteed
search time and provide a good tradeoff between the search
performance and the cost.
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Rajaramachandran
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#9
20-07-2012, 09:51 PM

Hello Sir, Can you pls send me the code!!
Advance in Thanks!!
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