TY - JOUR
T1 - Adaptive peer-to-peer routing with proximity
AU - Liau, Chu Yee
AU - Hidayanto, Achmad Nizar
AU - Bressan, Stephane
PY - 2003
Y1 - 2003
N2 - In this paper, we presented a routing strategy for requests in unstructured peer-to-peer networks. The strategy is based on the adaptive routing Q-routing. The strategy uses reinforcement learning to estimate the cost of routing a request. Such a strategy is scalable only if the routing indices are of reasonable size. We proposed and comparatively evaluated three methods for the pruning for the pruning of the routing indices. Our experiments confirm the validity of the adaptive routing and the scalability of a pruning approach based on a pruning strategy considering the popularity of the resources.
AB - In this paper, we presented a routing strategy for requests in unstructured peer-to-peer networks. The strategy is based on the adaptive routing Q-routing. The strategy uses reinforcement learning to estimate the cost of routing a request. Such a strategy is scalable only if the routing indices are of reasonable size. We proposed and comparatively evaluated three methods for the pruning for the pruning of the routing indices. Our experiments confirm the validity of the adaptive routing and the scalability of a pruning approach based on a pruning strategy considering the popularity of the resources.
UR - http://www.scopus.com/inward/record.url?scp=35248829663&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-45227-0_45
DO - 10.1007/978-3-540-45227-0_45
M3 - Article
AN - SCOPUS:35248829663
SN - 0302-9743
VL - 2736
SP - 454
EP - 463
JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ER -