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Small kDominating Sets in Planar Graphs with Applications
 IN GRAPHTHEORETIC CONCEPTS IN COMPUTER SCIENCE (BOLTENHAGEN
, 2001
"... A subset of nodes S in a graph G is called kdominating if, for every node u of the graph, the distance from u to S is at most k. We consider the parameter k (G) de ned as the cardinality of the smallest kdominating set of G. For planar graphs, we show that for every > 0 and for every k & ..."
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Cited by 10 (0 self)
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A subset of nodes S in a graph G is called kdominating if, for every node u of the graph, the distance from u to S is at most k. We consider the parameter k (G) de ned as the cardinality of the smallest kdominating set of G. For planar graphs, we show that for every > 0 and for every k
A Distributed Algorithm to Find kdominating Sets
, 1999
"... We consider a connected undirected graph G(n; m) with n nodes and m edges. A kdominating set D in G is a set of nodes having the property that every node in G is at most k edges away from at least one node in D. ..."
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Cited by 17 (0 self)
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We consider a connected undirected graph G(n; m) with n nodes and m edges. A kdominating set D in G is a set of nodes having the property that every node in G is at most k edges away from at least one node in D.
Fast Distributed Construction of Small kDominating Sets and Applications
, 2000
"... This paper presents a fast distributed algorithm to compute a small kdominating set D (for any xed k) and its induced graph partition (breaking the graph into radius k clusters centered around the vertices of D). The time complexity of the algorithm is O(k log n). ..."
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Cited by 66 (8 self)
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This paper presents a fast distributed algorithm to compute a small kdominating set D (for any xed k) and its induced graph partition (breaking the graph into radius k clusters centered around the vertices of D). The time complexity of the algorithm is O(k log n).
On Constructing kConnected kDominating Set in Wireless Networks
 In Proceedings of the 19 th International Parallel & Distributed Processing Symposium (IPDPS
, 2005
"... An important problem in wireless ad hoc and sensor networks is to select a few nodes to form a virtual backbone that supports routing and other tasks such as area monitoring. Previous work in this area has focused on selecting a small virtual backbone for high efficiency. In this paper, we propose ..."
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Cited by 50 (1 self)
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the construction of a kconnected kdominating set (kCDS) as a backbone to balance efficiency and fault tolerance. Four localized kCDS construction protocols are proposed. The first protocol randomly selects virtual backbone nodes with a given probability pk, where pk depends on the value of k and network
Community detection in graphs
, 2009
"... The modern science of networks has brought significant advances to our understanding of complex systems. One of the most relevant features of graphs representing real systems is community structure, or clustering, i. e. the organization of vertices in clusters, with many edges joining vertices of th ..."
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Cited by 801 (1 self)
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The modern science of networks has brought significant advances to our understanding of complex systems. One of the most relevant features of graphs representing real systems is community structure, or clustering, i. e. the organization of vertices in clusters, with many edges joining vertices
Planning Algorithms
, 2004
"... This book presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics. The particular subjects covered include motion planning, discrete planning, planning ..."
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Cited by 1108 (51 self)
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This book presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics. The particular subjects covered include motion planning, discrete planning
The Viterbi algorithm
 Proceedings of the IEEE
, 1973
"... vol. 6, no. 8, pp. 211220, 1951. [7] J. L. Anderson and J. W..Ryon, “Electromagnetic radiation in accelerated systems, ” Phys. Rev., vol. 181, pp. 17651775, 1969. [8] C. V. Heer, “Resonant frequencies of an electromagnetic cavity in an accelerated system of reference, ” Phys. Reu., vol. 134, pp. A ..."
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Cited by 985 (3 self)
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vol. 6, no. 8, pp. 211220, 1951. [7] J. L. Anderson and J. W..Ryon, “Electromagnetic radiation in accelerated systems, ” Phys. Rev., vol. 181, pp. 17651775, 1969. [8] C. V. Heer, “Resonant frequencies of an electromagnetic cavity in an accelerated system of reference, ” Phys. Reu., vol. 134, pp. A799A804, 1964. [9] T. C. Mo, “Theory of electrodynamics in media in noninertial frames and applications, ” J. Math. Phys., vol. 11, pp. 25892610, 1970.
Improved algorithms for optimal winner determination in combinatorial auctions and generalizations
, 2000
"... Combinatorial auctions can be used to reach efficient resource and task allocations in multiagent systems where the items are complementary. Determining the winners is NPcomplete and inapproximable, but it was recently shown that optimal search algorithms do very well on average. This paper present ..."
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Cited by 598 (55 self)
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presents a more sophisticated search algorithm for optimal (and anytime) winner determination, including structural improvements that reduce search tree size, faster data structures, and optimizations at search nodes based on driving toward, identifying and solving tractable special cases. We also uncover
The program dependence graph and its use in optimization
 ACM Transactions on Programming Languages and Systems
, 1987
"... In this paper we present an intermediate program representation, called the program dependence graph (PDG), that makes explicit both the data and control dependence5 for each operation in a program. Data dependences have been used to represent only the relevant data flow relationships of a program. ..."
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Cited by 989 (3 self)
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In this paper we present an intermediate program representation, called the program dependence graph (PDG), that makes explicit both the data and control dependence5 for each operation in a program. Data dependences have been used to represent only the relevant data flow relationships of a program
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