An Improved Upper Bound for Scalable Distributed Search Trees
نویسندگان
چکیده
In this paper we analyze the amortized cost of inserts and exact searches in a DRT*, an order preserving scalable distributed data structure able to manage both mono-dimensional and multi-dimensional data. We show that by adding to the DRT* strategy a correction algorithm after split operations, a sequence of m requests of intermixed exact-searches and insertions over a DRT* starting with one empty server and ending with n servers has a cost of O m α m n messages, where α m n is the classic inverse of the Ackermann function, thus improving the previous O m log 1 m n n bound.
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