``Fast and low-cost search schemes by exploiting localities in P2P networks" 

Lei Guo, Song Jiang, Li Xiao, and Xiaodong Zhang

Journal of Parallel and Distributed Computing, Vol. 65, Issue 6, pp. 729-742. 

Abstract

Existing peer-to-peer (P2P) search algorithms generally target either the 
performance objective of improving search quality from a client's perspective, 
or the objective of reducing search cost from an Internet management 
perspective. Most existing work of designing and optimizing search algorithms 
in unstructured P2P networks addresses the trade-off between the two 
performance objectives. In contrast, our goal in this study is to attempt 
to achieve both objectives. Motivated by our observations on the content 
locality in the peer community and the localities of search interests of 
individual peers, we propose content-abundant cluster-selectively 
prefetching indices from responding peers (CAC-SPIRP), a fast and low-cost 
P2P searching algorithm. Our algorithm consists of two components. The 
first component aims to reduce the search cost by constructing a CAC, where 
content-abundant peers self-identify, and self-organize themselves into an 
inter-connected cluster providing a pool of popular objects to be frequently 
accessed by the peer community. A query will be first routed to the CAC, 
and most likely to be satisfied there, significantly reducing the amount of 
network traffic and the search scope. The second component in our algorithm 
is client oriented and aims to improve the quality of P2P search, called 
SPIRP. A client individually identifies a small group of peers who have 
the same interests as itself to prefetch their entire file indices of the 
related interests, minimizing unnecessary outgoing queries and significantly 
reducing query response time. Building SPIRP on the CAC Internet 
infrastructure, our algorithm combines both merits of the two components 
to achieve both performance objectives. Our trace-driven simulations show 
that CAC-SPIRP significantly improves the overall performance from both 
client's perspective and Internet management perspective.