Distributed Searching of k-Dimensional Data with Almost Constant Costs

  • Authors:
  • Adriano Di Pasquale;Enrico Nardelli

  • Affiliations:
  • -;-

  • Venue:
  • ADBIS-DASFAA '00 Proceedings of the East-European Conference on Advances in Databases and Information Systems Held Jointly with International Conference on Database Systems for Advanced Applications: Current Issues in Databases and Information Systems
  • Year:
  • 2000

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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 = 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 dificulties in proving optimal worst case bounds for k-dimensions.