49,233 research outputs found
List rankings and on-line list rankings of graphs
A -ranking of a graph is a labeling of its vertices from
such that any nontrivial path whose endpoints have the same
label contains a larger label. The least for which has a -ranking is
the ranking number of , also known as tree-depth. The list ranking number of
is the least such that if each vertex of is assigned a set of
potential labels, then can be ranked by labeling each vertex with a label
from its assigned list. Rankings model a certain parallel processing problem in
manufacturing, while the list ranking version adds scheduling constraints. We
compute the list ranking number of paths, cycles, and trees with many more
leaves than internal vertices. Some of these results follow from stronger
theorems we prove about on-line versions of list ranking, where each vertex
starts with an empty list having some fixed capacity, and potential labels are
presented one by one, at which time they are added to the lists of certain
vertices; the decision of which of these vertices are actually to be ranked
with that label must be made immediately.Comment: 16 pages, 3 figure
Competitive versions of vertex ranking and game acquisition, and a problem on proper colorings
In this thesis we study certain functions on graphs. Chapters 2 and 3 deal with variations on vertex ranking, a type of node-labeling scheme that models a parallel processing problem. A k-ranking of a graph G is a labeling of its vertices from {1,...,k} such that any nontrivial path whose endpoints have the same label contains a vertex with a larger label. In Chapter 2, we investigate the problem of list ranking, wherein every vertex of G is assigned a set of possible labels, and a ranking must be constructed by labeling each vertex from its list; the list ranking number of G is the minimum k such that if every vertex is assigned a set of k possible labels, then G is guaranteed to have a ranking from these lists. We compute the list ranking numbers of paths, cycles, and trees with many leaves. In Chapter 3, we investigate the problem of on-line ranking, which asks for an algorithm to rank the vertices of G as they are revealed one at a time in the subgraph of G induced by the vertices revealed so far. The on-line ranking number of G is the minimum over all such labeling algorithms of the largest label that the algorithm can be forced to use. We give algorithmic bounds on the on-line ranking number of trees in terms of maximum degree, diameter, and number of internal vertices.
Chapter 4 is concerned with the connectedness and Hamiltonicity of the graph G^j_k(H), whose vertices are the proper k-colorings of a given graph H, with edges joining colorings that differ only on a set of vertices contained within a connected subgraph of H on at most j vertices. We introduce and study the parameters g_k(H) and h_k(H), which denote the minimum j such that G^j_k(H) is connected or Hamiltonian, respectively. Finally, in Chapter 5 we compute the game acquisition number of complete bipartite graphs. An acquisition move in a weighted graph G consists a vertex v taking all the weight from a neighbor whose weight is at most the weight of v. In the acquisition game on G, each vertex initially has weight 1, and players Min and Max alternate acquisition moves until the set of vertices remaining with positive weight is an independent set. Min seeks to minimize the size of the final independent set, while Max seeks to maximize it; the game acquisition number is the size of the final set under optimal play
Efficient Algorithms for Asymptotic Bounds on Termination Time in VASS
Vector Addition Systems with States (VASS) provide a well-known and
fundamental model for the analysis of concurrent processes, parameterized
systems, and are also used as abstract models of programs in resource bound
analysis. In this paper we study the problem of obtaining asymptotic bounds on
the termination time of a given VASS. In particular, we focus on the
practically important case of obtaining polynomial bounds on termination time.
Our main contributions are as follows: First, we present a polynomial-time
algorithm for deciding whether a given VASS has a linear asymptotic complexity.
We also show that if the complexity of a VASS is not linear, it is at least
quadratic. Second, we classify VASS according to quantitative properties of
their cycles. We show that certain singularities in these properties are the
key reason for non-polynomial asymptotic complexity of VASS. In absence of
singularities, we show that the asymptotic complexity is always polynomial and
of the form , for some integer , where is the
dimension of the VASS. We present a polynomial-time algorithm computing the
optimal . For general VASS, the same algorithm, which is based on a complete
technique for the construction of ranking functions in VASS, produces a valid
lower bound, i.e., a such that the termination complexity is .
Our results are based on new insights into the geometry of VASS dynamics, which
hold the potential for further applicability to VASS analysis.Comment: arXiv admin note: text overlap with arXiv:1708.0925
An Analysis of Optimal Link Bombs
We analyze the phenomenon of collusion for the purpose of boosting the
pagerank of a node in an interlinked environment. We investigate the optimal
attack pattern for a group of nodes (attackers) attempting to improve the
ranking of a specific node (the victim). We consider attacks where the
attackers can only manipulate their own outgoing links. We show that the
optimal attacks in this scenario are uncoordinated, i.e. the attackers link
directly to the victim and no one else. nodes do not link to each other. We
also discuss optimal attack patterns for a group that wants to hide itself by
not pointing directly to the victim. In these disguised attacks, the attackers
link to nodes hops away from the victim. We show that an optimal disguised
attack exists and how it can be computed. The optimal disguised attack also
allows us to find optimal link farm configurations. A link farm can be
considered a special case of our approach: the target page of the link farm is
the victim and the other nodes in the link farm are the attackers for the
purpose of improving the rank of the victim. The target page can however
control its own outgoing links for the purpose of improving its own rank, which
can be modeled as an optimal disguised attack of 1-hop on itself. Our results
are unique in the literature as we show optimality not only in the pagerank
score, but also in the rank based on the pagerank score. We further validate
our results with experiments on a variety of random graph models.Comment: Full Version of a version which appeared in AIRweb 200
Improving search order for reachability testing in timed automata
Standard algorithms for reachability analysis of timed automata are sensitive
to the order in which the transitions of the automata are taken. To tackle this
problem, we propose a ranking system and a waiting strategy. This paper
discusses the reason why the search order matters and shows how a ranking
system and a waiting strategy can be integrated into the standard reachability
algorithm to alleviate and prevent the problem respectively. Experiments show
that the combination of the two approaches gives optimal search order on
standard benchmarks except for one example. This suggests that it should be
used instead of the standard BFS algorithm for reachability analysis of timed
automata
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