scholarly journals A Reliable Peer-to-Peer Platform for Adding New Node Using Trust Based Model

Author(s):  
Vimal S. ◽  
Srivatsa S K.

In order to evaluate the trustworthiness of participating peers in unstructured peer-to-peer networks, Reputation aggregation methods are used in this method. Each and every peer of the network will collect the local scores of each transaction and will compute global scores by aggregating all the local scores with the help of global scores, each individual peer can interact with its suitable peers. But the existing method will not consider the score of the new peer. In this condition, requests are handled by existing peers who leads to failure in downloading process. To rectify this, NP-TRUST model is used to distribute the request to all peers including the newly joined peers. The proposed method is compared with gossip and DFR-TRUST model in Transaction Success rate and variation in file request.

2010 ◽  
Vol 33 (2) ◽  
pp. 345-355 ◽  
Author(s):  
Chun-Qi TIAN ◽  
Jian-Hui JIANG ◽  
Zhi-Guo HU ◽  
Feng LI

2011 ◽  
Vol 211-212 ◽  
pp. 295-299 ◽  
Author(s):  
Ya Dong Gong ◽  
He Ping Deng ◽  
Zhan Ran Gu ◽  
Ji Ye Hu ◽  
Yong Xiang Wen

In peer-to-peer (P2P) networks, nodes are quite different from each other in many aspects, such as sharing resources, online time and bandwidth. Some approaches have been introduced to take advantage of the query forwarding and answering heterogeneity such that the high bandwidth and query answering capability of nodes can be fully utilized to improve the system performance. In this paper, we suggest using the online time heterogeneity to improve the search efficiency of P2P networks. In our proposed Differentiated Index (Diff-Index) algorithm, the nodes with long online time will have higher priority to be queried. Because the online time is quite different among nodes, much search traffic can be saved by querying only a small portion of a network. The query success rate can be kept high because the nodes sharing a great amount of resources tend to have long online time. Our simulation results show that the Diff-Index algorithm can save 66 percent of search traffic.


2017 ◽  
Vol 18 (4) ◽  
pp. 559-569
Author(s):  
Mei-juan Jia ◽  
Hui-qiang Wang ◽  
Jun-yu Lin ◽  
Guang-sheng Feng ◽  
Hai-tao Yu

2010 ◽  
Vol 33 (9) ◽  
pp. 1725-1735 ◽  
Author(s):  
Zhen-Hua TAN ◽  
Xing-Wei WANG ◽  
Wei CHENG ◽  
Gui-Ran CHANG ◽  
Zhi-Liang ZHU

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