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A Very Efficient Order Preserving Scalable Distributed Data Structure
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A Very Efficient Order Preserving Scalable Distributed Data Structure
Adriano Di Pasquale8 and Enrico Nardelli8, 9 
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Dipartimento di Matematica Pura ed Applicata, Univ. of L’Aquila, Via Vetoio, Coppito, I, 67010, Italia |
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Istituto di Analisi dei Sistemi ed Informatica, Consiglio Nazionale delle Ricerche, Viale Manzoni 30, I, 00185 Roma, Italia |
Abstract
SDDSs (Scalable Distributed Data Structures) are access methods specifically designed to satisfy the high performance requirements
of a distributed computing environment made up by a collection of computers connected through a high speed network. In this
paper we present and discuss performances of ADST, a new order preserving SDDS with a worst-case constant cost for exact-search
queries, a worst-case logarithmic cost for update queries, and an optimal worst-case cost for range search queries of O(k) messages, where k is the number of servers covering the query range. Moreover, our structure has an amortized almost constant cost for any
single-key query. Finally, our scheme can be easily generalized to manage k-dimensional points, while maintaining the same costs of the 1-dimensional case.
We report experimental comparisons between ADST and its direct competitors (i.e., LH*, DRT, and RP*) where it is shown that
ADST behaves clearly better. Furthermore we show how our basic technique can be combined with recent proposals for ensuring
high-availability to an SDDS. Therefore our solution is very attractive for network servers requiring both a fast response
time and a high reliability.
Keywords Scalable distributed data structure - message passing environment - multi-dimensional search
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