Similarity Searching: Towards Bulk-loading Peer-to-Peer Networks
| Authors | |
|---|---|
| Year of publication | 2008 |
| Type | Article in Proceedings |
| Conference | 1st International Workshop on Similarity Search and Applications (SISAP 2008) |
| MU Faculty or unit | |
| Citation | |
| Web | http://www.sisap.org/ |
| Field | Informatics |
| Keywords | similarity search; p2p network; peer split; index structure |
| Description | Due to the exponential growth of digital data and its complexity, we need a technique which allows us to search such collections efficiently. A suitable solution is based on the peer-to-peer (P2P) network paradigm and the metric-space model of similarity. When a large volume of data is being inserted, the P2P network must expand to new peers in order to maintain its efficiency. Thus, many peers must be split. During a peer split, the data is halved and one half is migrated to a new peer. In this paper, we study the problem of peer splits and propose a specialized algorithm for speeding it up. In particular, we use the structured P2P network called the M-Chord. Search performance within a single peer is enhanced by the M-tree. In experimental evaluation, we compare the proposed algorithm with several straightforward solutions on a real network organizing 10 million images. Our algorithm provides a significant performance boost. |
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