An Efficient and Scalable Framework for Peer-to-Peer Clustering and Firework Query Model
| Author(s) | : | Bhosale Prachi, Gadve Vaishnavi, Khopade Mayuri, Pawar Kajal |
| Institution | : | Computer Engineering, AISSMS’s IOIT |
| Published In | : | Vol. 4, Issue 12 — December 2017 |
| Page No. | : | - |
| Domain | : | Engineering |
| Type | : | Research Paper |
| ISSN (Online) | : | 2348-4470 |
| ISSN (Print) | : | 2348-6406 |
Efficient and trustworthy file querying is very important to the general performance of peer-to-peer (P2P)file sharing systems. rising strategies area unit setting out to address this challenge by exploiting on-line social networks(OSNs). However, current OSN-based strategies merely cluster common-interest nodes for prime potency or limit theinteraction between social friends for prime trustiness, that provides restricted sweetening or contradicts the open andfree service goal of P2P systems. very little analysis has been undertaken to totally and hand in glove leverage OSNswith integrated thought of proximity and interest. during this work, we tend to analyze a Bit Torrent file sharing trace,that proves the requirement of proximity- and interest-aware bunch. supported the trace study and OSN properties, wetend to propose a social Network integrated P2P file sharing system with increased potency and trustiness (SoNet) tototally and hand in glove leverage the common-interest, proximity-close and trust properties of OSN friends. SoNet usesa ranked distributed hash table (DHT) to cluster common-interest nodes, then any cluster proximity-close nodes intosubcluster, and connects the nodes in an exceedingly subcluster with social links. Thus, once queries move trustablesocial links, they additionally gain higher likelihood of being with success resolved by proximityclose nodes, at the sametime enhancing potency and trustiness. The results of trace-driven experiments on the realworld Planet Lab test beddemonstrate the upper potency and trustiness of SoNet compared with alternative systems..
Bhosale Prachi, Gadve Vaishnavi, Khopade Mayuri, Pawar Kajal, “An Efficient and Scalable Framework for Peer-to-Peer Clustering and Firework Query Model”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 4, Issue 12, pp. -, December 2017.








