12,172 research outputs found
Counting Euler Tours in Undirected Bounded Treewidth Graphs
We show that counting Euler tours in undirected bounded tree-width graphs is
tractable even in parallel - by proving a upper bound. This is in
stark contrast to #P-completeness of the same problem in general graphs.
Our main technical contribution is to show how (an instance of) dynamic
programming on bounded \emph{clique-width} graphs can be performed efficiently
in parallel. Thus we show that the sequential result of Espelage, Gurski and
Wanke for efficiently computing Hamiltonian paths in bounded clique-width
graphs can be adapted in the parallel setting to count the number of
Hamiltonian paths which in turn is a tool for counting the number of Euler
tours in bounded tree-width graphs. Our technique also yields parallel
algorithms for counting longest paths and bipartite perfect matchings in
bounded-clique width graphs.
While establishing that counting Euler tours in bounded tree-width graphs can
be computed by non-uniform monotone arithmetic circuits of polynomial degree
(which characterize ) is relatively easy, establishing a uniform
bound needs a careful use of polynomial interpolation.Comment: 17 pages; There was an error in the proof of the GapL upper bound
claimed in the previous version which has been subsequently remove
Low-distortion embeddings of graphs with large girth
The main purpose of the paper is to construct a sequence of graphs of
constant degree with indefinitely growing girths admitting embeddings into
with uniformly bounded distortions. This result answers the problem
posed by N. Linial, A. Magen, and A. Naor (2002).Comment: Some confusing omissions are corrected in the second versio
Data-Oblivious Graph Algorithms in Outsourced External Memory
Motivated by privacy preservation for outsourced data, data-oblivious
external memory is a computational framework where a client performs
computations on data stored at a semi-trusted server in a way that does not
reveal her data to the server. This approach facilitates collaboration and
reliability over traditional frameworks, and it provides privacy protection,
even though the server has full access to the data and he can monitor how it is
accessed by the client. The challenge is that even if data is encrypted, the
server can learn information based on the client data access pattern; hence,
access patterns must also be obfuscated. We investigate privacy-preserving
algorithms for outsourced external memory that are based on the use of
data-oblivious algorithms, that is, algorithms where each possible sequence of
data accesses is independent of the data values. We give new efficient
data-oblivious algorithms in the outsourced external memory model for a number
of fundamental graph problems. Our results include new data-oblivious
external-memory methods for constructing minimum spanning trees, performing
various traversals on rooted trees, answering least common ancestor queries on
trees, computing biconnected components, and forming open ear decompositions.
None of our algorithms make use of constant-time random oracles.Comment: 20 page
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