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The Role Graph Model and Conflict of Interest
 ACM Transactions on Information and System Security
, 1999
"... We describe in more detail than before the reference model for rolebased access control introduced by Nyanchama and Osborn, and the rolegraph model with its accompanying algorithms, which is one way of implementing rolerole relationships. An alternative role insertion algorithm is added, and it i ..."
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Cited by 115 (2 self)
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We describe in more detail than before the reference model for rolebased access control introduced by Nyanchama and Osborn, and the rolegraph model with its accompanying algorithms, which is one way of implementing rolerole relationships. An alternative role insertion algorithm is added, and it is shown how the role creation policies of Fernandez et al. correspond to role addition algorithms in our model. We then use our reference model to provide a taxonomy for kinds of conflict. We then go on to consider in some detail privilegeprivilege and rolerole conflicts in conjunction with the role graph model. We show how rolerole conflicts lead to a partitioning of the role graph into nonconflicting collections that can together be safely authorized to a given user. Finally, in an appendix, we present the role graph algorithms with additional logic to disallow roles that contain conflicting privileges.
A separator theorem for graphs with an excluded minor and its applications
 IN PROCEEDINGS OF THE 22ND ANNUAL ACM SYMPOSIUM ON THEORY OF COMPUTING
, 1990
"... Let G be an nvertex graph with nonnegative weights whose sum is 1 assigned to its vertices, and with no minor isomorphic to a given hvertex graph H. We prove that there is a set X of no more than h 3/2 n 1/2 vertices of G whose deletion creates a graph in which the total weight of every connected ..."
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Cited by 93 (1 self)
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Let G be an nvertex graph with nonnegative weights whose sum is 1 assigned to its vertices, and with no minor isomorphic to a given hvertex graph H. We prove that there is a set X of no more than h 3/2 n 1/2 vertices of G whose deletion creates a graph in which the total weight of every connected component is at most 1/2. This extends significantly a wellknown theorem of Lipton and Tarjan for planar graphs. We exhibit an algorithm which finds, given an nvertex graph G with weights as above and an hvertex graph H, either such a set X or a minor of G isomorphic to H. The algorithm runs in time O(h 1/2 n 1/2 m), where m is the number of edges of G plus the number of its vertices. Our results supply extensions of the many known applications of the LiptonTarjan separator theorem from the class of planar graphs (or that of graphs with bounded genus) to any class of graphs with an excluded minor. For example, it follows that for any fixed graph H, given a graph G with n vertices and with no Hminor one can approximate the size of the maximum independent set of G up to a relative error of 1 / √ log n in polynomial time, find that size exactly and find the chromatic number of G in time 2 O( √ n) and solve any sparse system of n linear equations in n unknowns whose sparsity structure 0 corresponds to G in time O(n 3/2). We also describe a combinatorial application of our result which relates the treewidth of a graph to the maximum size of a Khminor in it.
Learning Maps for Indoor Mobile Robot Navigation
 ARTIFICIAL INTELLIGENCE (ACCEPTED FOR PUBLICATION)
, 1997
"... Autonomous robots must be able to learn and maintain models of their environments. Research on mobile robot navigation has produced two major paradigms for mapping indoor environments: gridbased and topological. While gridbased methods produce accurate metric maps, their complexity often prohibits ..."
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Cited by 88 (12 self)
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Autonomous robots must be able to learn and maintain models of their environments. Research on mobile robot navigation has produced two major paradigms for mapping indoor environments: gridbased and topological. While gridbased methods produce accurate metric maps, their complexity often prohibits efficient planning and problem solving in largescale indoor environments. Topological maps, on the other hand, can be used much more efficiently, yet accurate and consistent topological maps are often difficult to learn and maintain in largescale environments, particularly if momentary sensor data is highly ambiguous. This paper describes an approach that integrates both paradigms: gridbased and topological. Gridbased maps are learned using artificial neural networks and naive Bayesian integration. Topological maps are generated on top of the gridbased maps, by partitioning the latter into coherent regions. By combining both paradigms, the approach presented here gains advantages from both worlds: accuracy/consistency and efficiency. The paper gives results for autonomous exploration, mapping and operation of a mobile robot in populated multiroom environments.
A dynamic survey of graph labellings
 Electron. J. Combin., Dynamic Surveys(6):95pp
, 2001
"... A graph labeling is an assignment of integers to the vertices or edges, or both, subject to certain conditions. Graph labelings were first introduced in the late 1960s. In the intervening years dozens of graph labelings techniques have been studied in over 1000 papers. Finding out what has been done ..."
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Cited by 85 (0 self)
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A graph labeling is an assignment of integers to the vertices or edges, or both, subject to certain conditions. Graph labelings were first introduced in the late 1960s. In the intervening years dozens of graph labelings techniques have been studied in over 1000 papers. Finding out what has been done for any particular kind of labeling and keeping up with new discoveries is difficult because of the sheer number of papers and because many of the papers have appeared in journals that are not widely available. In this survey I have collected everything I could find on graph labeling. For the convenience of the reader the survey includes a detailed table of contents and index.
Upward Planarity Testing
 SIAM Journal on Computing
, 1995
"... Acyclic digraphs, such as the covering digraphs of ordered sets, are usually drawn upward, i.e., with the edges monotonically increasing in the vertical direction. A digraph is upward planar if it admits an upward planar drawing. In this survey paper, we overview the literature on the problem of upw ..."
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Cited by 82 (15 self)
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Acyclic digraphs, such as the covering digraphs of ordered sets, are usually drawn upward, i.e., with the edges monotonically increasing in the vertical direction. A digraph is upward planar if it admits an upward planar drawing. In this survey paper, we overview the literature on the problem of upward planarity testing. We present several characterizations of upward planarity and describe upward planarity testing algorithms for special classes of digraphs, such as embedded digraphs and singlesource digraphs. We also sketch the proof of NPcompleteness of upward planarity testing.
Spatial Learning for Navigation in Dynamic Environments
, 1996
"... This article describes techniques that have been developed for spatial learning in dynamic environments and a mobile robot system, ELDEN, that integrates these techniques for exploration and navigation in dynamic environments. In this research, we introduce the concept of adaptive place networks, in ..."
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Cited by 77 (5 self)
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This article describes techniques that have been developed for spatial learning in dynamic environments and a mobile robot system, ELDEN, that integrates these techniques for exploration and navigation in dynamic environments. In this research, we introduce the concept of adaptive place networks, incrementallyconstructed spatial representations that incorporate variableconfidence links to model uncertainty about topological adjacency. These networks guide the robot's navigation while constantly adapting to any topological changes that are encountered. ELDEN integrates these networks with a reactive controller that is robust to transient changes in the environment and a relocalization system that uses evidence grids to recalibrate dead reckoning. Footnotes 1 Manuscript received . . . 2 Department of Computer Engineering and Science, Case Western Reserve University, Cleveland, OH, 44106, USA (email: yamauchi@alpha.ces.cwru.edu, URL: http://yuggoth.ces.cwru.edu/yamauchi/index.ht...
Capacity of Power Constrained AdHoc Networks
, 2004
"... Throughput capacity is a critical parameter for the design and evaluation of adhoc wireless networks. Consider n identical randomly located nodes, on a unit area, forming an adhoc wireless network. Assuming a fixed per node transmission capability of T bits per second at a fixed range, it has been ..."
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Cited by 77 (2 self)
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Throughput capacity is a critical parameter for the design and evaluation of adhoc wireless networks. Consider n identical randomly located nodes, on a unit area, forming an adhoc wireless network. Assuming a fixed per node transmission capability of T bits per second at a fixed range, it has been shown that the uniform throughput capacity per node r(n) is .
Strengthening the Closure Concept in ClawFree Graphs
, 1999
"... We give a strengthening of the closure concept for clawfree graphs introduced by the second author in 1997. The new closure of a clawfree graph G defined here is uniquely determined and preserves the value of the circumference of G. We present an infinite family of graphs with n vertices and 3 2 ..."
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Cited by 69 (14 self)
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We give a strengthening of the closure concept for clawfree graphs introduced by the second author in 1997. The new closure of a clawfree graph G defined here is uniquely determined and preserves the value of the circumference of G. We present an infinite family of graphs with n vertices and 3 2 n \Gamma 1 edges for which the new closure is the complete graph K n . Keywords: closure, cycle closure, clawfree graph, circumference, hamiltonian graph AMS Subject Classifications (1991): 05C45, 05C35 1 1 Introduction We consider finite simple undirected graphs G = (V (G); E(G)). For concepts and notation not defined here we refer the reader to [1]. We denote by c(G) the circumference of G, i.e. the length of a longest cycle in G, by NG (x) the neighborhood of a vertex x in G (i.e., NG (x) = fy 2 V (G)j xy 2 E(G)g), and we denote NG [x] = NG (x) [ fxg. For a nonempty set A ` V (G), the induced subgraph on A is denoted by hAiG , the notation G \Gamma A stands for hV (G) n AiG (if A ...
DataGathering Wireless Sensor Networks: Organization and Capacity
 Computer Networks
, 2003
"... In this paper we study the transport capacity of a datagathering wireless sensor network under di#erent communication organizations. In particular, we consider using a flat as well as a hierarchical/clustering architecture to realize manytoone communications. The capacity of the network under thi ..."
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Cited by 61 (3 self)
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In this paper we study the transport capacity of a datagathering wireless sensor network under di#erent communication organizations. In particular, we consider using a flat as well as a hierarchical/clustering architecture to realize manytoone communications. The capacity of the network under this manytoone data gathering scenario is reduced compared to random onetoone communication due to the unavoidable creation of a point of tra#c concentration at the data collector/receiver. We introduce the overall throughput bound of # = per node, where W is the transmission capacity, and show under what conditions it can be achieved and under what conditions it cannot. When those conditions are not met, we constructively show how # = # is achieved with high probability as the number of sensors goes to infinity. We also show how the introduction of clustering can improve the throughput. We discuss the tradeo#s between achieving capacity and energy consumption, how transport capacity might be a#ected by considering innetwork processing and the implications this study has on the design of practical protocols for largescale datagathering wireless sensor networks.
Tree spanners
 SIAM J. Discrete Math
, 1995
"... A tree tspanner T of a graph G is a spanning tree in which the distance between every pair of vertices is at most t times their distance in G. This notion is motivated by applications in communication networks, distributed systems, and network design. This paper studies graph theoretic, algorithmic ..."
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Cited by 60 (1 self)
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A tree tspanner T of a graph G is a spanning tree in which the distance between every pair of vertices is at most t times their distance in G. This notion is motivated by applications in communication networks, distributed systems, and network design. This paper studies graph theoretic, algorithmic and complexity issues about tree spanners. It is shown that a tree 1spanner, if it exists, in a weighted graph with m edges and n vertices is a minimum spanning tree and can be found in O(m log β(m, n)) time, where β(m, n) = min{i  log (i) n ≤ m/n}. On the other hand, for any fixed t> 1, the problem of determining the existence of a tree tspanner in a weighted graph is proven to be NPcomplete. For unweighted graphs, it is shown that constructing a tree 2spanner takes linear time, whereas determining the existence of a tree tspanner is NPcomplete for any fixed t ≥ 4. A theorem which captures the structure of tree 2spanners is presented for unweighted graphs. For digraphs, an O((m+n)α(m, n)) algorithm is provided for