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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, in 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
Conference title
Databases, Information Systems, and Peer-to-Peer Computing International Workshops, DBISP2P 2005/2006
Conference date
2006-09
Conference city
Seoul
Conference country
Corée du Sud
Book title
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
Book author
Moro, Gianluca; Bergamaschi, Sonia; Joseph, Sam; Morin, Jean-Henry; Ouksel, Aris M.
Publisher
Springer
Series title
Lecture Notes in Computer Science
Series number
4125
Published in
Berlin
ISBN
978-3-540-71660-0
Number of pages
418
Pages
155-162
Publication identifier
Metadata
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Author(s)
Litwin, Witold
Mokadem, Riad
Schwarz, Thomas
Abstract (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.
Subjects / Keywords
SDDS