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AllPairs SmallStretch Paths
 Journal of Algorithms
, 1997
"... Let G = (V; E) be a weighted undirected graph. A path between u; v 2 V is said to be of stretch t if its length is at most t times the distance between u and v in the graph. We consider the problem of finding smallstretch paths between all pairs of vertices in the graph G. It is easy to see that f ..."
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Cited by 37 (7 self)
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Let G = (V; E) be a weighted undirected graph. A path between u; v 2 V is said to be of stretch t if its length is at most t times the distance between u and v in the graph. We consider the problem of finding smallstretch paths between all pairs of vertices in the graph G. It is easy to see
AllPairs SmallStretch Paths
"... Abstract Let G = (V; E) be a weighted undirected graph. A path between u; v 2 V is said to be of stretch t if its length is at most t times the distance between u and v in the graph. We consider the problem of finding smallstretch paths between all pairs of vertices in the graph G. It is easy to se ..."
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Abstract Let G = (V; E) be a weighted undirected graph. A path between u; v 2 V is said to be of stretch t if its length is at most t times the distance between u and v in the graph. We consider the problem of finding smallstretch paths between all pairs of vertices in the graph G. It is easy
Faster Algorithms for Approximate Distance Oracles and AllPairs Small StretchPaths
"... ffi(u, v) < = ^ffi(u, v) < = t * ffi(u, v). The most efficient algorithms known for computing small stretch distances in Gare the approximate distance oracles of [16] and the three algorithms in [9] to compute allpairs stretch t distancesfor t = 2, 7/3, and 3. We present faster algorithms fo ..."
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ffi(u, v) < = ^ffi(u, v) < = t * ffi(u, v). The most efficient algorithms known for computing small stretch distances in Gare the approximate distance oracles of [16] and the three algorithms in [9] to compute allpairs stretch t distancesfor t = 2, 7/3, and 3. We present faster algorithms
Fibonacci Heaps and Their Uses in Improved Network optimization algorithms
, 1987
"... In this paper we develop a new data structure for implementing heaps (priority queues). Our structure, Fibonacci heaps (abbreviated Fheaps), extends the binomial queues proposed by Vuillemin and studied further by Brown. Fheaps support arbitrary deletion from an nitem heap in qlogn) amortized tim ..."
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Cited by 739 (18 self)
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in the problem graph: ( 1) O(n log n + m) for the singlesource shortest path problem with nonnegative edge lengths, improved from O(m logfmh+2)n); (2) O(n*log n + nm) for the allpairs shortest path problem, improved from O(nm lo&,,,+2,n); (3) O(n*logn + nm) for the assignment problem (weighted bipartite
How bad is selfish routing?
 JOURNAL OF THE ACM
, 2002
"... We consider the problem of routing traffic to optimize the performance of a congested network. We are given a network, a rate of traffic between each pair of nodes, and a latency function for each edge specifying the time needed to traverse the edge given its congestion; the objective is to route t ..."
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Cited by 657 (27 self)
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We consider the problem of routing traffic to optimize the performance of a congested network. We are given a network, a rate of traffic between each pair of nodes, and a latency function for each edge specifying the time needed to traverse the edge given its congestion; the objective is to route
Random Key Predistribution Schemes for Sensor Networks”,
 IEEE Symposium on Security and Privacy,
, 2003
"... Abstract Efficient key distribution is the basis for providing secure communication, a necessary requirement for many emerging sensor network applications. Many applications require authentic and secret communication among neighboring sensor nodes. However, establishing keys for secure communicatio ..."
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Cited by 832 (12 self)
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keys for all pairs of nodes is not viable due to the large number of sensors and the limited memory of sensor nodes. A new key distribution approach was proposed by Eschenauer and Gligor [11] to achieve secrecy for nodetonode communication: sensor nodes receive a random subset of keys from a key pool
FASTER ALGORITHMS FOR ALLPAIRS APPROXIMATE SHORTEST PATHS IN UNDIRECTED GRAPHS
, 2006
"... Let G = (V, E) be a weighted undirected graph having nonnegative edge weights. An estimate ˆ δ(u, v) of the actual distance δ(u, v) between u, v ∈ V is said to be of stretch t iff δ(u, v) ≤ ˆ δ(u, v) ≤ t · δ(u, v). Computing allpairs small stretch distances efficiently (both in terms of time ..."
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Cited by 9 (2 self)
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Let G = (V, E) be a weighted undirected graph having nonnegative edge weights. An estimate ˆ δ(u, v) of the actual distance δ(u, v) between u, v ∈ V is said to be of stretch t iff δ(u, v) ≤ ˆ δ(u, v) ≤ t · δ(u, v). Computing allpairs small stretch distances efficiently (both in terms of time
Dynamic Approximate AllPairs Shortest Paths in Undirected Graphs
"... Abstract We obtain three new dynamic algorithms for the approximate allpairs shortest paths problem in unweighted undirected graphs: 1. For any fixed " ? 0, a decremental algorithm withan expected total running time of ~O(mn), where m is the number of edges and n is the number of vertice ..."
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Abstract We obtain three new dynamic algorithms for the approximate allpairs shortest paths problem in unweighted undirected graphs: 1. For any fixed " ? 0, a decremental algorithm withan expected total running time of ~O(mn), where m is the number of edges and n is the number of ver
Indexing and Querying XML Data for Regular Path Expressions
 IN VLDB
, 2001
"... With the advent of XML as a standard for data representation and exchange on the Internet, storing and querying XML data becomes more and more important. Several XML query languages have been proposed, and the common feature of the languages is the use of regular path expressions to query XML ..."
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Cited by 343 (9 self)
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, (2) ##Join for scanning sorted elements and attributes to find elementattribute pairs, and (3) ##Join for finding KleeneClosure on repeated paths or elements. The ##Join algorithm is highly effective particularly for searching paths that are very long or whose lengths are unknown
Finding the Hidden Path: Time Bounds for AllPairs Shortest Paths
, 1993
"... We investigate the allpairs shortest paths problem in weighted graphs. We present an algorithmthe Hidden Paths Algorithmthat finds these paths in time O(m* n+n² log n), where m is the number of edges participating in shortest paths. Our algorithm is a practical substitute for Dijkstra&ap ..."
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Cited by 75 (0 self)
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's algorithm. We argue that m* is likely to be small in practice, since m* = O(n log n) with high probability for many probability distributions on edge weights. We also prove an Ω(mn) lower bound on the running time of any pathcomparison based algorithm for the allpairs shortest paths problem. Path
Results 1  10
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