On Veracious Search In Unsystematic Networks

Transcription

1 On Veracious Search In Unsystematic Networks K.Thushara #1, P.Venkata Narayana#2 #1 Student Of M.Tech(S.E) And Department Of Computer Science And Engineering, # 2 Department Of Computer Science And Engineering, St.Ann s College Of Engineering & Technology (Sacet),Chirala Abstract: The Unstructure peer-to-peer (P2P) file - sharing networks are popular in the mass markets. As the peers participating in unstructure networks interconnect randomly they rely on flooding query messages to discover objects of interest and thus introduce remarkable network traffic. Empirical measurements to studies indicate that the peers in P2P networks have similar preferences and have recently proposes unstructure P2P networks that organize participating peers by exploiting their similarites. The resultant networks may not perform to searches efficiently because existing overlay topology construction algorithms often creates unstructure P2P networks without performing guarantees. We are proposing a novel overlay formation algorithm for unstructure P2P networks. Based on the file sharing pattern exhibiting the power law property our proposal is unique in that it poses rigorous performance guarante. Theoretical performance results concludes that in a constant probability 1) searching an object in our proposes network efficiently takes hops and 2) the search progressively and effectively exploits the similarity of peers. In addition to the success ratio of discovering an object approximates 100 percent. 1 INTRODUCTION The PEER-TO-PEER (P2P) networks (or overlay networks) have been widely deployed in the Internet and they provide various services such as file sharing and telephony. In P2P applications are popular because they primarily provide low entry barriers and self scaling. Prior studies reveal that P2P applications may dominate up to around 20 percent of Internet traffic. Object search is an essential building block in several P2P applications. Gnutella[3] is a popular P2P search protocol in the mass market. Specifically Gnutella networks are unstructure and the peers participating in networks connect to one another randomly peers search objects in the networks through message flooding. To flood a message an inquiry peer broadcasts the message to its neighbors (by the neighbors of peer i we mean those peers that have end-to-end connections with The broadcast message is associated with a positive integer time-to-live value. Upon receiving a message from the peer decreases the TTL value associate with the message by 1 and then relays the message with the updated TTL value to its neighbors except the one sending the message to j, if the TTL value remains positive. 2. Existing System: Content distribution is a centralized one, where the content is distributed from the centralized server to all clients requesting the document. Clients send request to the centralized server for downloading the file. Server accepts the request and sends the file as response to the request. In most client-server setups; the server is a dedicated computer whose entire purpose is to distribute files. Drawbacks of Existing System Scalability problem arises when multi requests arises at a single time. Servers need heavy processing power Downloading takes hours when clients increases Requires heavy storage in case of multimedia content 3. Proposed System: Page 11

2 Investigating in the file-sharing preference of users and correlation between different resources categories in a real peer-to-peer network. Analytic methods from complex networks theory to investigate the File sharing. Relation between the users and the resources could be described by a bipartite sharing graph, with one subset for the users and the other for the resources. Using weighted user network, users built connections based on their sharing interests to similar resources, and different resources are correlated together due to many users sharing behaviors, with weighted edges indicating their interaction strengths. Advantages of Proposed System: Our proposal clearly outperforms the competing algorithms in terms of 1. The hop count of routing a query message, 2. The successful ratio of resolving a query, 3. The number of messages required for resolving a query, and 4. The message overhead for maintaining and formatting the overlay. 3.1 Peer Similarity Graphs: Let V be the set of peers in a P2P network. Definition 1. The peer similarity function Fig.1 An example of a peer similarity graph G =(V, E). Definition 2. Given G=(V,E), the peer similarity distance between two distinct peers u V and v V, denote by D(u,v) is define as the length of a shortest path in that connects u and v. 3.2 Overlay Formation: Exploiting Similar Peers: As previously mentioned, each peer u will connect to the peers selected among all peers in V- {u} that are most similar to u; that is, u intends to satisfy Property C1. Let Iu be the set of neighbors that u currently maintains in the network G=(V,E). Define Acurrent as By exploiting the peers most similar to u, u seeks a peer w V-Iu {u} and invites w as its neighbor is F(u, v) is define as the inverse of the cosine angle of two summarize latent semantic vectors representing any two peers u and v in a P2P network. Where each element in a summarize vector for any peer i calculates the total frequency of the corresponding keyword appearing in the data items stores in i. We note that designing peer similarity functions is orthogonal but is out of the scope of our study. Our proposal may refer to the peer similarity functions presentes in the literature. As it is possible that there is no neighbor such that (3) can be satisfied, u randomly selects a node w in with a probability. Page 12

3 by s and d respectively. Instead of blindly flooding query messages as in the typical Gnutella protocol [3] our search protocol conceptually operates as follows. Among the neighboring peers in Is and Φs, s selects the peers; each t Is U Φs has F(t,d) > F(s,d). Algorithm 2: Peer t forwards a query message Q Minimizing Semantic Overlay Diameter: To minimize the overlay diameter in our proposal, each peer u V will create a number of extra overlay links. Denote such extra connections for u by Φu. Each t Φu is selected in a probability of Pr(u,t). where Pr(u,t) depends on the peer similarity distance between u and t, that is, D(u,t). We will discuss in detail how we will determine Pr(u,t) in Appendix A.1, available in the online supplemental material. Algorithm 2 details the search protocol. Notably as the peer t which forward the query Q is unaware of the peers hosting the requeste of object t simply broadcasts Q to its neighbors Similar to the naive Gnutella protocol [3] each query message in our proposal can be relaye for a predefine maximum number of times. 3.4 Theoretical Performance Analysis: Empirical Data Set: We have to investigates the empirical data set of that files share by edonkey users and concludes that the data set exhibits the power-law property. Definition 3: The scope of a peer u V in a peer similarity graph G=(V,E) with in a given peer similarity distance d is defined as As Pr(u,t) depends on D(u,t), each peer u estimates D(u,t) for any sampled t. Particularly the biases random walker issued by u maintains the path it travels in the overlay. u then approximates D(u,t) by the length of the path. 3.3 Search Protocol: Consider any query Q requesting an object O. Denote the peer issuing Q and the peer hosting O Analytical Results: We have observe that the empirical data set exhibits the power-law property in terms of the distribution of Su(k). In our analytical model is bases such distribution. Definition 4: Given a peer similarity graph G =(V, E) and two positive constants α and β, the set of nodes, V, follows the α power-law similarity distance Page 13

4 expansion if for each node u V, the number of nodes with a similarity distance no more than d to u is Modules: Server Peer login Upload Search Modules Discription: 1. Server: It maintains all peers information and file searching, Uploading information. 2. Peer login: Each and every peer logined and it performs file uploading,searching,download and it maintains routing table information. 3. Upload: Each and every peer uploads a file. 4. Search: Each peer searches a file from other peers in a networks.it uses following algorithm performs very well as most queries can be forwarded to their destination in no more than 10 hops, validating our analytical results in Theorem 2. In contrast, some queries in GES and SocioNet may take more than 25 and 40 hops, respectively. Notably, GES performs better than SocioNet in terms of the hop count of routing a query message. SocioNet performs poorly, as the resultant overlay quality may trap in a local optimum whereas GES depends on random walks to discover similar peers that may help bypass a local optimum Effects of Varying ns and nl : In the simulations, the default number of similar neighbors is ns = 8 and the default number of dissimilar neighbors is also nl = 8. In this experiment, we investigate the effect of varying the values of ns and nl. Fig. 4 depicts the simulation results for the query hop count averaged over all successful queries with respect to the different numbers of algorithmic rounds, where ns ¼ 8 and nl=4,8,16. That is due to space limitation, we omit the detailed simulation results for the query overhead and the overhead for maintaining and rewiring the overlay. 4. Expermental Results: Comparative Studies: The hop counts of routing the successful queries despite the unsuccessful ones. Fig. 4. The query hop count Fig. 3. The overhead of rewiring and maintaining the network Effects of System Dynamics: We have also investigated the effect of system dynamics for our proposal. In this experiment, each peer connects up to ns ns+ni=8 neighbors, where ns and ni are equal to 4. We first stabilize our system for 100 minutes. Then, peers start to join and Page 14

5 leave such that the lifetime of any peer is 2.5 hours in expectation. Fig. 5 shows the simulation results. In a dynamic system, our proposal performs well in terms of successful query ratio if the expected lifetime of a peer is 2.5 and 1.25 hours. Fig. 5. The successful query ratio against the system dynamics. 5. Conclusion: A similarity-aware overlay topology, the search protocol we have suggested in this project which takes advantage of the similarity of peers exploited by our overlay network, can considerably reduce the search traffic. The resultant networks may not perform searches efficiently and effectively. Enhancement: We propose an file Replication and consistency Maintenance mechanism that integrates the two techniques in a systematic and harmonized manner. It achieves high efficiency in file replication and consistency maintenance at a significantly low cost. Instead of passively accepting replicas and updates, each node determines file replication and update polling by dynamically adapting to time-varying file query and update rates, which avoids unnecessary file replications and updates. It dramatically reduces overhead and yields significant improvements on the efficiency of both file replication and consistency maintenance approaches. 1. IPOQUE, Ipoque Internet Study 2007: P2P File Sharing Still Dominates the Worldwide Internet, S. Sen and J. Wang, Analyzing Peer-to-Peer Traffic Across Large Networks, IEEE/ACM Trans. Networking, vol. 12, no. 2, pp , Apr Gnutella, Y. Liu, J. Han, and J. Wang, Rumor Riding: Anonymizing Unstructured Peer-to-Peer Systems, IEEE Trans. Parallel and Distributed Systems, vol. 22, no. 3, pp , Mar H. Chen, H. Jin, Y. Liu, and L.M. Ni, Difficulty- Aware Hybrid Search in Peer-to-Peer Networks, IEEE Trans. Parallel and Distributed Systems, vol. 20, no. 1, pp , Jan A. Crespo and H. Garcia-Molina, Routing Indices for Peer-to-Peer Systems, Proc. 22th IEEE Int l Conf. Distributed Computing Systems (ICDCS 02), pp , July from 2009 THUSHARA.K is a student of Software Engineering from ST.ANN S COLLEGE OF ENGINEERING & - TECHNOLOGY, CHIRALA, Presently pursuing M.Tech (Software Engineering) from thiscollege. She received B.Tech Achariya Nagarjuna university in the year of P.VENKATA NARAYANA received his m.tech in c.s.e from K.l.C.E vaddeswaram in the year of 2009 Presently his is working as ASSISTANT PROFESSOR in st.ann s engineering college chirala. 4yrs teaching experience 6 REFERENCES: Page 15