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SingleSource ShortestPaths on Arbitrary Directed Graphs in Linear AverageCase Time
 In Proc. 12th ACMSIAM Symposium on Discrete Algorithms
, 2001
"... The quest for a lineartime singlesource shortestpath (SSSP) algorithm on directed graphs with positive edge weights is an ongoing hot research topic. While Thorup recently found an O(n + m) time RAM algorithm for undirected graphs with n nodes, m edges and integer edge weights in f0; : : : ; 2 w ..."
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Cited by 28 (5 self)
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The quest for a lineartime singlesource shortestpath (SSSP) algorithm on directed graphs with positive edge weights is an ongoing hot research topic. While Thorup recently found an O(n + m) time RAM algorithm for undirected graphs with n nodes, m edges and integer edge weights in f0; : : : ; 2 w 1g where w denotes the word length, the currently best time bound for directed sparse graphs on a RAM is O(n + m log log n). In the present paper we study the averagecase complexity of SSSP. We give a simple algorithm for arbitrary directed graphs with random edge weights uniformly distributed in [0; 1] and show that it needs linear time O(n + m) with high probability. 1 Introduction The singlesource shortestpath problem (SSSP) is a fundamental and wellstudied combinatorial optimization problem with many practical and theoretical applications [1]. Let G = (V; E) be a directed graph, jV j = n, jEj = m, let s be a distinguished vertex of the graph, and c be a function assigning a n...
A Parallelization of Dijkstra's Shortest Path Algorithm
 IN PROC. 23RD MFCS'98, LECTURE NOTES IN COMPUTER SCIENCE
, 1998
"... The single source shortest path (SSSP) problem lacks parallel solutions which are fast and simultaneously workefficient. We propose simple criteria which divide Dijkstra's sequential SSSP algorithm into a number of phases, such that the operations within a phase can be done in parallel. We give a P ..."
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Cited by 26 (6 self)
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The single source shortest path (SSSP) problem lacks parallel solutions which are fast and simultaneously workefficient. We propose simple criteria which divide Dijkstra's sequential SSSP algorithm into a number of phases, such that the operations within a phase can be done in parallel. We give a PRAM algorithm based on these criteria and analyze its performance on random digraphs with random edge weights uniformly distributed in [0, 1]. We use
Parallel Shortest Path for Arbitrary Graphs
 In EUROPAR: Parallel Processing, 6th International EUROPAR Conference. LNCS
, 2000
"... . In spite of intensive research, no workecient parallel algorithm for the single source shortest path problem is known which works in sublinear time for arbitrary directed graphs with nonnegative edge weights. We present an algorithm that improves this situation for graphs where the ratio dc= ..."
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Cited by 11 (4 self)
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. In spite of intensive research, no workecient parallel algorithm for the single source shortest path problem is known which works in sublinear time for arbitrary directed graphs with nonnegative edge weights. We present an algorithm that improves this situation for graphs where the ratio dc= between the maximum weight of a shortest path dc and a \safe step width" is not too large. We show how such a step width can be found eciently and give several graph classes which meet the above condition, such that our parallel shortest path algorithm runs in sublinear time and uses linear work. The new algorithm is even faster than a previous one which only works for random graphs with random edge weights [10]. On those graphs our new approach is faster by a factor of (log n= log log n) and achieves an expected time bound of O(log 2 n) using linear work. 1 Introduction The single source shortest path problem (SSSP) is a fundamental and wellstudied combinatorial optimizati...
Buckets strike back: Improved Parallel ShortestPaths
 Proc. 16th Intl. Par. Distr. Process. Symp. (IPDPS
, 2002
"... We study the averagecase complexity of the parallel singlesource shortestpath (SSSP) problem, assuming arbitrary directed graphs with n nodes, m edges, and independent random edge weights uniformly distributed in [0; 1]. We provide a new bucketbased parallel SSSP algorithm that runs in T = O(log ..."
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Cited by 6 (2 self)
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We study the averagecase complexity of the parallel singlesource shortestpath (SSSP) problem, assuming arbitrary directed graphs with n nodes, m edges, and independent random edge weights uniformly distributed in [0; 1]. We provide a new bucketbased parallel SSSP algorithm that runs in T = O(log 2 n min i f2 i L + jV i jg) averagecase time using O(n+m+T ) work on a PRAM where L denotes the maximum shortestpath weight and jV i j is the number of graph vertices with indegree at least 2 i . All previous algorithms either required more time or more work. The minimum performance gain is a logarithmic factor improvement; on certain graph classes, accelerations by factors of more than n 0:4 can be achieved. The algorithm allows adaptation to distributed memory machines, too.
Directed SingleSource ShortestPaths in Linear AverageCase Time
, 2001
"... The quest for a lineartime singlesource shortestpath (SSSP) algorithm on directed graphs with positive edge weights is an ongoing hot research topic. While Thorup recently found an O(n + m) time RAM algorithm for undirected graphs with n nodes, m edges and integer edge weights in f0; : : : ; 2 ..."
Abstract
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The quest for a lineartime singlesource shortestpath (SSSP) algorithm on directed graphs with positive edge weights is an ongoing hot research topic. While Thorup recently found an O(n + m) time RAM algorithm for undirected graphs with n nodes, m edges and integer edge weights in f0; : : : ; 2 1g where w denotes the word length, the currently best time bound for directed sparse graphs on a RAM is O(n +m log log n).