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Abstract:
We generalize Cuckoo Hashing \cite{PagRod01} to \emph{$d$-ary Cuckoo Hashing}
and show how this yields a simple hash table data structure that stores $n$
elements in $(1+\epsilon)\,n$ memory cells, for any constant $\epsilon > 0$.
Assuming uniform hashing, accessing or deleting table entries takes at most $d
= O(\ln\frac{1}{\epsilon})$ probes and the expected amortized insertion time is
constant. This is the first dictionary that has worst case constant access time
and expected constant update time, works with $(1+\epsilon)\,n$ space, and
supports satellite information. Experiments indicate that $d=4$ choices suffice
for $\epsilon \approx 0.03$. We also describe a hash table data structure using
explicit constant time hash functions, using at most $d=
O(\ln^2\frac{1}{\epsilon})$ probes in the worst case.
A corollary is an expected linear time algorithm for finding maximum
cardinality matchings in a rather natural model of sparse random bipartite
graphs.
