Analysis and design of algorithms : double hashing and parallel graph searching

The following is in two parts, corresponding to the two separate topics in the dissertation.Probabilistic Analysis of Double HashingIn [GS78], a deep and elegant analysis shows that double hashing is asymptotically equivalent to the ideal uniform hashing up to a load factor of about 0.319. In this paper we show how a resampling technique can be used to develop a surprisingly simple proof of the result that this equivalence holds for load factors arbitrarily close to 1.Parallel Depth First Search of Planar Directed Acyclic GraphsIn 1988, Kao [Kao88] presented the first NC algorithm for the depth first search of a directed planar graph. Recently, Kao and Klein [KK90] reduced the number of processors required from O(n^4) to linear, but the time bound is O(log^8 n).We present an algorithm for the depth first search of a planar directed acyclic graph with k sources using O(n) processors and O(log k log n) time on a CRCW PRAM model. For planar dags with a single source and a single sink, we present a simple optimal algorithm which gives the depth first search in O(log n) time with O(n/log n) processors on an EREW PRAM. For a single-source multiple-sink planar dag, we have an O(log n) time O(n) processor EREW algorithm. The EREW algorithms assume that the embedding is given. A simplified variant of the depth first search of a multisource planar dag can be used to solve the single source reachability problem for a planar directed acyclic graph in O(log^2 n) time and O(n) processors on an CRCW PRAM. Since an O(log^4 n) algorithm for this problem is used as a subroutine by Kao and Klein in their depth first search for the general planar directed graph, this will lower their time bound by a factor of log^2 n. Our work uses the concept of a planar Euler tour depth first search, a depth first search in which the Euler tour around the tree is planar and crosses no tree edge. This concept may prove to be of use in other parallel algorithms for planar graphs