Showing papers on "Prim's algorithm published in 1983"
TL;DR: A distributed algorithm is presented that constructs the minimum weight spanning tree in a connected undirected graph with distinct edge weights that can be initiated spontaneously at any node or at any subset of nodes.
Abstract: Abstract : A distributed algorithm is presented that constructs the minimum weight spanning tree in a connected undirected graph with distinct edge weights. A processor exists at each node of the graph, knowing initially only the weights of the adjacent edges. The processors obey the same algorithm and exchange messages with neighbors until the tree is constructed. The total number of messages required for a graph of N nodes and E edges is at most 5N log of N to the base 2 + 2E and a message contains at most one edge weight plus log of 8N to the base 2 bits. The algorithm can be initiated spontaneously at any node or at any subset of nodes.
1,152 citations
104 citations
TL;DR: This work extends to the multi-constrained, unweighted case, the analysis that was already made in a previous work for the one-conStrained, weighted case of undirected spanning tree problems from the viewpoint of their computational complexity.
48 citations
TL;DR: The empirical performance of the algorithms of Kruskal, Prim, and Sollin for determining a minimum spanning tree is examined and found to be considerably better than suggested by worst case analysis.
11 citations
TL;DR: An application of the bucket sort in Kruskal's minimal spanning tree algorithm is proposed, which is very fast if the edge costs are from a distribution which is close to uniform.
8 citations
TL;DR: The worst case running time of the minimal spanning tree algorithm presented by Bentley and Friedman is shown to be N2 logN, fork≧2 andΘ(N2), fork=1.
Abstract: This paper concerns the worst case running time of the minimal spanning tree algorithm presented by Bentley and Friedman. For a set ofN points ink-dimensional Euclidean space the worst case performance of the algorithm is shown to beΘ(N
2 logN), fork≧2 andΘ(N
2), fork=1.
6 citations
TL;DR: An algorithm for designing a deadlock-free system with the minimum resource cost is presented, whose running time is bounded by O(ca(m) + mlogm), where the inverse of Ackermann's function, which is very slowly growing.
Abstract: Consider a system consisting of a set ofn processes, P~, P2 . . . . . Pn, and a set of serially reusable resources of m different types, R1, R~ . . . . . R,~. It is assumed that the system is \"claim-limited,\" that is, its \"claim matrix\" C, whose (i, j ) element C(i, j) is the maximum number of units of R: that may be needed by P, at the same time, is known a priori. It is desired to design a deadlock-free system, that is, one which never deadlocks for any allocation sequence within the limits given by C. For j ffi 1, 2 . . . . . m, let a, (>0) be the cost of one unit of Rj. An algorithm for designing a deadlock-free system with the minimum resource cost is presented. Its running time is bounded by O(ca(m) + mlogm), where e ts the number of nonzero elements in C and a, is the inverse of Ackermann's function, which is very slowly growing
2 citations
TL;DR: The algorithm presented here is between 350% and 26000% faster than the best algorithm previously published, and hence the computer analysis of circuits of a reasonable size is now feasible.
Abstract: Enumerating the spanning trees common to a pair of graphs is a problem which arises in symbolic circuit analysis. The algorithm presented here is between 350% and 26000% faster than the best algorithm previously published, and hence the computer analysis of circuits of a reasonable size is now feasible.
2 citations