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Distributed Searching of k-Dimensional Data with Almost Constant Costs

  • Adriano Di Pasquale
  • EnricoZ Nardelli
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1884)

Abstract

In this paper we consider the dictionary problem in the scalable distributed data structure paradigm introduced by Litwin, Neimat and Schneider and analyze costs for insert and exact searches in an amortized framework. We show that both for the 1-dimensional and the k- dimensional case insert and exact searches have an amortized almost constant costs, namely O (log(1+A-) n) messages, where n is the total number of servers of the structure, b is the capacity of each server, and \( A = \tfrac{b} {2} \). Considering that A is a large value in real applications, in the order of thousands, we can assume to have a constant cost in real distributed structures.

Only worst case analysis has been previously considered and the almost constant cost for the amortized analysis of the general k-dimensional case appears to be very promising in the light of the well known difficulties in proving optimal worst case bounds for k-dimensions.

Keywords

distributed data structure message passing environment multi-dimensional search 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Adriano Di Pasquale
    • 1
  • EnricoZ Nardelli
    • 1
    • 2
  1. 1.Dipartimento di Matematica Pura ed ApplicataUniv. of L’AquilaL’AquilaItalia
  2. 2.Consiglio Nazionale delle RicercheIstituto di Analisi dei Sistemi ed InformaticaRomaItalia

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