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Approximate Matching for Peer-to-Peer Overlays with Cubit
dc.contributor.author | Wong, Bernard | |
dc.contributor.author | Slivkins, Aleksandrs | |
dc.contributor.author | Sirer, Emin Gun | |
dc.date.accessioned | 2008-05-19T13:18:34Z | |
dc.date.available | 2008-05-19T13:18:34Z | |
dc.date.issued | 2008-05-19T13:18:34Z | |
dc.identifier.uri | https://hdl.handle.net/1813/10826 | |
dc.description.abstract | Keyword search is a critical component in most content retrieval systems. Despite the emergence of completely decentralized and efficient peer-to-peer techniques for content distribution, there have not been similarly efficient, accurate, and decentralized mechanisms for content discovery based on approximate search keys. In this paper, we present a scalable and efficient peer-to-peer system called Cubit with a new search primitive that can efficiently find the k data items with keys most similar to a given search key. The system works by creating a keyword metric space that encompasses both the nodes and the objects in the system, where the distance between two points is a measure of the similarity between the strings that the points represent. It provides a loosely-structured overlay that can efficiently navigate this space. We evaluate Cubit through both a real deployment as a search plugin for a popular BitTorrent client and a large-scale simulation and show that it provides an efficient, accurate and robust method to handle imprecise string search in filesharing applications. | en_US |
dc.description.sponsorship | This work was supported in part by NSF-TRUST 0424422 and NSF-CAREER 0546568 grants. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | Peer to peer | en_US |
dc.subject | Keyword search | en_US |
dc.title | Approximate Matching for Peer-to-Peer Overlays with Cubit | en_US |
dc.type | technical report | en_US |