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Cumulative Algebraic Signatures for Fast String Search, Protection Against Incidental Viewing and Corruption of Data in an SDDS

Litwin, Witold; Mokadem, Riad; Schwarz, Thomas (2007), Cumulative Algebraic Signatures for Fast String Search, Protection Against Incidental Viewing and Corruption of Data in an SDDS, dans Moro, Gianluca; Bergamaschi, Sonia; Joseph, Sam; Morin, Jean-Henry; Ouksel, Aris M., Databases, Information Systems, and Peer-to-Peer Computing International Workshops, DBISP2P 2005/2006, Trondheim, Norway, August 28-29, 2005, Seoul, Korea, September 11, 2006, Revised Selected Papers, Springer : Berlin, p. 155-162. http://dx.doi.org/10.1007/978-3-540-71661-7_14

Type
Communication / Conférence
Date
2007
Titre du colloque
Databases, Information Systems, and Peer-to-Peer Computing International Workshops, DBISP2P 2005/2006
Date du colloque
2006-09
Ville du colloque
Seoul
Pays du colloque
Corée du Sud
Titre de l'ouvrage
Databases, Information Systems, and Peer-to-Peer Computing International Workshops, DBISP2P 2005/2006, Trondheim, Norway, August 28-29, 2005, Seoul, Korea, September 11, 2006, Revised Selected Papers
Auteurs de l’ouvrage
Moro, Gianluca; Bergamaschi, Sonia; Joseph, Sam; Morin, Jean-Henry; Ouksel, Aris M.
Éditeur
Springer
Titre de la collection
Lecture Notes in Computer Science
Numéro dans la collection
4125
Ville d’édition
Berlin
Isbn
978-3-540-71660-0
Nombre de pages
418
Pages
155-162
Identifiant publication
Métadonnées
Afficher la notice complète
Auteur(s)
Litwin, Witold
Mokadem, Riad
Schwarz, Thomas
Résumé (EN)
Scalable Distributed Data Structures (SDDS) are a class of data structures for multicomputers (a distributed system of networked computers) that allow data access by key in constant time (independent of the number of nodes in the multicomputer) and parallel search of the data. In order to speed up the parallel search of the data fields of the records, we propose to encode the records of a Scalable Distributed Data Structure (SDDS) using pre-computed algebraic signatures. The encoding / decoding overhead is linear in the size of the records. It speeds up prefix searches, longest prefix matches, and string searches. In addition, the encoding protects the privacy of the SDDS data against the owners of the workstations that make up the multicomputer. Additional encoding protects the integrity of the data against malfunctions.
Mots-clés
SDDS