Adaptive Probabilistic Search (APS) for Peer-to-Peer Networks
Adaptive Probabilistic Search (APS) for Peer-to-Peer Networks
Files
Publication or External Link
Date
2003-02-27
Authors
Tsoumakos, Dimitrios
Roussopoulos, Nick
Advisor
Citation
DRUM DOI
Abstract
Peer-to-Peer networks are gaining increasing attention from both the
scientific and the large Internet user community. Popular applications
utilizing this new technology offer many attractive features to a growing
number of users. At the heart of such networks lies the data retrieval
algorithm. Proposed methods either depend on the network-disastrous
flooding and its variations or utilize various indices too expensive to
maintain.
In this report we describe an adaptive, bandwidth-efficient and easy to
deploy search algorithm for unstructured Peer-to-Peer networks, the
Adaptive Probabilistic Search method (APS). Our scheme
utilizes feedback from previous searches to probabilistically guide future
ones. Extensive simulation results show that APS achieves high
success rates, increased number of discovered objects, very low bandwidth
consumption and adaptation to changing topologies.
UMIACS-TR-2003-21