258 research outputs found
2-Vertex Connectivity in Directed Graphs
We complement our study of 2-connectivity in directed graphs, by considering
the computation of the following 2-vertex-connectivity relations: We say that
two vertices v and w are 2-vertex-connected if there are two internally
vertex-disjoint paths from v to w and two internally vertex-disjoint paths from
w to v. We also say that v and w are vertex-resilient if the removal of any
vertex different from v and w leaves v and w in the same strongly connected
component. We show how to compute the above relations in linear time so that we
can report in constant time if two vertices are 2-vertex-connected or if they
are vertex-resilient. We also show how to compute in linear time a sparse
certificate for these relations, i.e., a subgraph of the input graph that has
O(n) edges and maintains the same 2-vertex-connectivity and vertex-resilience
relations as the input graph, where n is the number of vertices.Comment: arXiv admin note: substantial text overlap with arXiv:1407.304
Data Dissemination in Unified Dynamic Wireless Networks
We give efficient algorithms for the fundamental problems of Broadcast and
Local Broadcast in dynamic wireless networks. We propose a general model of
communication which captures and includes both fading models (like SINR) and
graph-based models (such as quasi unit disc graphs, bounded-independence
graphs, and protocol model). The only requirement is that the nodes can be
embedded in a bounded growth quasi-metric, which is the weakest condition known
to ensure distributed operability. Both the nodes and the links of the network
are dynamic: nodes can come and go, while the signal strength on links can go
up or down.
The results improve some of the known bounds even in the static setting,
including an optimal algorithm for local broadcasting in the SINR model, which
is additionally uniform (independent of network size). An essential component
is a procedure for balancing contention, which has potentially wide
applicability. The results illustrate the importance of carrier sensing, a
stock feature of wireless nodes today, which we encapsulate in primitives to
better explore its uses and usefulness.Comment: 28 pages, 2 figure
Advances in Functional Decomposition: Theory and Applications
Functional decomposition aims at finding efficient representations for Boolean functions. It is used in many applications, including multi-level logic synthesis, formal verification, and testing.
This dissertation presents novel heuristic algorithms for functional decomposition. These algorithms take advantage of suitable representations of the Boolean functions in order to be efficient.
The first two algorithms compute simple-disjoint and disjoint-support decompositions. They are based on representing the target function by a Reduced Ordered Binary Decision Diagram (BDD). Unlike other BDD-based algorithms, the presented ones can deal with larger target functions and produce more decompositions without requiring expensive manipulations of the representation, particularly BDD reordering.
The third algorithm also finds disjoint-support decompositions, but it is based on a technique which integrates circuit graph analysis and BDD-based decomposition. The combination of the two approaches results in an algorithm which is more robust than a purely BDD-based one, and that improves both the quality of the results and the running time.
The fourth algorithm uses circuit graph analysis to obtain non-disjoint decompositions. We show that the problem of computing non-disjoint decompositions can be reduced to the problem of computing multiple-vertex dominators. We also prove that multiple-vertex dominators can be found in polynomial time. This result is important because there is no known polynomial time algorithm for computing all non-disjoint decompositions of a Boolean function.
The fifth algorithm provides an efficient means to decompose a function at the circuit graph level, by using information derived from a BDD representation. This is done without the expensive circuit re-synthesis normally associated with BDD-based decomposition approaches.
Finally we present two publications that resulted from the many detours we have taken along the winding path of our research
The leafage of a chordal graph
The leafage l(G) of a chordal graph G is the minimum number of leaves of a
tree in which G has an intersection representation by subtrees. We obtain upper
and lower bounds on l(G) and compute it on special classes. The maximum of l(G)
on n-vertex graphs is n - lg n - (1/2) lg lg n + O(1). The proper leafage l*(G)
is the minimum number of leaves when no subtree may contain another; we obtain
upper and lower bounds on l*(G). Leafage equals proper leafage on claw-free
chordal graphs. We use asteroidal sets and structural properties of chordal
graphs.Comment: 19 pages, 3 figure
Routing in Histograms
Let be an -monotone orthogonal polygon with vertices. We call
a simple histogram if its upper boundary is a single edge; and a double
histogram if it has a horizontal chord from the left boundary to the right
boundary. Two points and in are co-visible if and only if the
(axis-parallel) rectangle spanned by and completely lies in . In the
-visibility graph of , we connect two vertices of with an edge
if and only if they are co-visible.
We consider routing with preprocessing in . We may preprocess to
obtain a label and a routing table for each vertex of . Then, we must be
able to route a packet between any two vertices and of , where each
step may use only the label of the target node , the routing table and
neighborhood of the current node, and the packet header.
We present a routing scheme for double histograms that sends any data packet
along a path whose length is at most twice the (unweighted) shortest path
distance between the endpoints. In our scheme, the labels, routing tables, and
headers need bits. For the case of simple histograms, we obtain a
routing scheme with optimal routing paths, -bit labels, one-bit
routing tables, and no headers.Comment: 18 pages, 11 figure
A simple and optimal ancestry labeling scheme for trees
We present a ancestry labeling scheme for trees. The
problem was first presented by Kannan et al. [STOC 88'] along with a simple solution. Motivated by applications to XML files, the label size was
improved incrementally over the course of more than 20 years by a series of
papers. The last, due to Fraigniaud and Korman [STOC 10'], presented an
asymptotically optimal labeling scheme using
non-trivial tree-decomposition techniques. By providing a framework
generalizing interval based labeling schemes, we obtain a simple, yet
asymptotically optimal solution to the problem. Furthermore, our labeling
scheme is attained by a small modification of the original solution.Comment: 12 pages, 1 figure. To appear at ICALP'1
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