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Resources NeuroSearch in Peer-to-Peer networks
By: Corbalan, L.; De Giusti, A.; Lanzarini, L.;
2009 / IEEE / 978-953-7138-15-8
Description
This item was taken from the IEEE Conference ' Resources NeuroSearch in Peer-to-Peer networks ' Unstructured Peer-to-Peer (P2P) networks as Gnutella are dynamic, distributed systems without any centralizing point favoring failure tolerance and strength. However, resource search in these systems is an important problem. Gnutella's breadth-first search algorithm is flooding-based and generates a large amount of traffic thus making scalability difficult. This paper proposes a new search algorithm in which nodes, assisted by their local neuronal networks, selectively send the query to the most appropriate subsets of neighbors only. Hence, Gnutella algorithm is significantly improved and provides a greater percentage of findings with less amount of traffic generated on P2P network.
Related Topics
Peer-to-peer Computing
Neural Network
Resources Neurosearch
Unstructured Peer-to-peer Network
Distributed System
Breadth-first Search Algorithm
Gnutella Algorithm
Biological Neural Networks
Telecommunication Traffic
Computer Networks
Network Servers
Delay
Scalability
Neural Networks
Large-scale Systems
Broadcasting
Neural Networks
Distributed Systems
Peer-to-peer Networks
Gnutella-like Systems
Resource Discovery
Neural Nets
Distributed Processing
Tree Searching
Engineering
Peer To Peer Computing