Worst-case Analysis of Set Union Algorithms
Journal of the ACM (JACM)
LH: Linear Hashing for distributed files
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Distributing a search tree among a growing number of processors
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Distributed searching of multi-dimensional data: a performance evaluation study
Journal of Parallel and Distributed Computing - Parallel and distributed data structures
Efficiency of a Good But Not Linear Set Union Algorithm
Journal of the ACM (JACM)
Chorochronos: a research network for spatiotemporal database systems
ACM SIGMOD Record
An improved equivalence algorithm
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VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
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ADST: An Order Preserving Scalable Distributed Data Structure with Constant Access Costs
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DEXA '01 Proceedings of the 12th International Conference on Database and Expert Systems Applications
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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.