The connectivity problem is a fundamental problem in graph theory. The best known algorithm to solve the connectivity problem on general graphs with n vertices and m edges takes O( K(G) mn(1.5)) time, where K(G) is th...
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The connectivity problem is a fundamental problem in graph theory. The best known algorithm to solve the connectivity problem on general graphs with n vertices and m edges takes O( K(G) mn(1.5)) time, where K(G) is the vertex connectivity of G. In this paper, an efficient algorithm is designed to solve vertex connectivity problem, which takes O(n(2)) time and O(n) space for a trapezoid graph.
In this paper, we consider a variant of the well-known Steiner tree problem. Given a complete graph G = (V, E) with a cost function c : E -> R+ and two subsets R and R' satisfying R' subset of R subset of V...
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In this paper, we consider a variant of the well-known Steiner tree problem. Given a complete graph G = (V, E) with a cost function c : E -> R+ and two subsets R and R' satisfying R' subset of R subset of V, a selected-internal Steiner tree is a Steiner tree which contains (or spans) all the vertices in R such that each vertex in R' cannot be a leaf. The selected-internal Steiner tree problem is to find a selected-internal Steiner tree with the minimum cost. In this paper, we present a 2 rho-approximation algorithm for the problem, where p is the best-known approximation ratio for the Steiner tree problem. (c) 2007 Elsevier B.V. All rights reserved.
In this paper, we introduce new geometric ad-hoc routing algorithms to route queries in static sensor networks. For singlesource-queries routing, we utilise a centralised mechanism to accomplish a query using an asymp...
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In this paper, we introduce new geometric ad-hoc routing algorithms to route queries in static sensor networks. For singlesource-queries routing, we utilise a centralised mechanism to accomplish a query using an asymptotically optimal number of transmissions O(c), where c is the length of the shortest path between the source and the destination. For multiple-source-queries routing, the number of transmissions for each query is bounded by O(c log n), where n is the number of nodes in the network. For both single-source and multiple-source queries, the routing stage is preceded by preprocessing stages requiring O(nD) and O(n(2)D) transmissions, respectively, where D is the diameter of the network. Our algorithm improves the complexity of the currently best known algorithms in terms of the number of transmissions for each query. The preprocessing is worthwhile if it is followed by frequent queries. We could also imagine that there is an extra initial power (say, batteries) available during the preprocessing stage or alternatively the positions of the sensors are known in advance and the preprocessing can be done before the sensors are deployed in the field. It is also worth mentioning that a lower bound of Omega(c(2)) transmissions has been proved if preprocessing is not allowed [***, ***, ***, Asymptotically optimal geometric mobile ad-hoc routing, in: Proceedings of the Sixth International Workshop on Discrete Algorithm and Methods for Mobility, Atlanta, GA, September 2002, pp. 24-33]. (C) 2006 Elsevier B.V. All rights reserved.
The problem of extracting a basis of irredundant motifs from a sequence is considered. In previous work such bases were built incrementally for all suffixes of the input string s in O(n(3)), where n is the length of s...
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ISBN:
(纸本)9783540735441
The problem of extracting a basis of irredundant motifs from a sequence is considered. In previous work such bases were built incrementally for all suffixes of the input string s in O(n(3)), where n is the length of s. Faster, non-incremental algorithms have been based on the landmark approach to string searching due to Fischer and Paterson, and exhibit respective time bounds of O(n(2) logn log|Sigma|) and O(|Sigma|n(2) log(2) n log log n), with Z denoting the alphabet. The algorithm by Fischer and Paterson makes crucial use of the FFT, which is impractical with long sequences. The algorithm presented in the present paper does not need to resort to the FFT and yet is asymptotically faster than previously available ones. Specifically, an off-line algorithm is presented taking time O(|Sigma|n(2)), which is optimal for finite Z.
We study the explicit deterministic treasure hunt problem in an n-vertex network. This problem was firstly introduced by Ta-Shma, and Zwick in [9] [SODA'07]. It is the variant of the well known rendezvous problem ...
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ISBN:
(纸本)9783540771180
We study the explicit deterministic treasure hunt problem in an n-vertex network. This problem was firstly introduced by Ta-Shma, and Zwick in [9] [SODA'07]. It is the variant of the well known rendezvous problem in which one of the robot (the treasure) is always stationary. We obtain an O(n(c (1+1/lambda)))-time solution for this problem, which significantly improves the currently best known result of running time O(n(2c)) in [9], where c is a fixed constant from the construction of an universal exploration sequence in [8,9], lambda is a constant integer and lambda >> 1. The treasure hunt problem motivates the study of strongly universal exploration sequences. We give a better explicit construction of strongly universal exploration sequences than the one in [9].
We study the problem of enumerating substrings that are common amongst genomes that share evolutionary descent. For example, one might want to enumerate all identical (therefore conserved) substrings that are shared b...
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ISBN:
(纸本)3540332952
We study the problem of enumerating substrings that are common amongst genomes that share evolutionary descent. For example, one might want to enumerate all identical (therefore conserved) substrings that are shared between all mammals and not found in nonmammals. Such collection of substrings may be used to identify conserved subsequences or to construct sets of identifying substrings for branches of a phylogmetic tree. For two disjoint sets of genomes on a phylogenetic tree, a substring is called a tag if it is found in all of the genomes of one set and none of the genomes of the other set. We present a near-linear time algorithm that finds all tags in a given phylogeny;and a sublinear space algorithm (at the expense of running time) that is more suited for very large data sets. Under a stochastic model of evolution, we show that a simple process of tag-generation essentially captures all possible ways of generating tags. We use this insight to develop a faster tag discovery algorithm with a small chance of error. However, since tags are not guaranteed to exist in a given data set, we generalize the notion of a tag from a single substring to a set of substrings. We present a linear programming-based approach for finding approximate generalized tag sets. Finally, we use our tag enumeration algorithm to analyze a phylogeny containing 57 whole microbial genomes. We find tags for all nodes in the phylogeny except the root for which we find generalized tag sets.
The most efficient currently known algorithms for two-dimensional pattern matching with rotations have a worst case time complexity of O(n(2)m(3)), where the size of the text is n x n and the size of the pattern is m ...
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The most efficient currently known algorithms for two-dimensional pattern matching with rotations have a worst case time complexity of O(n(2)m(3)), where the size of the text is n x n and the size of the pattern is m x m. In this paper we present a new algorithm for the problem whose running time is 0(n(2),m(2)). (c) 2006 Published by Elsevier B.V.
In this paper, an algorithm is designed to find a maximum weight independent set of a circular-arc graph with n vertices. The weights considered here are all non-negative real numbers and associated with each of the v...
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In this paper, an algorithm is designed to find a maximum weight independent set of a circular-arc graph with n vertices. The weights considered here are all non-negative real numbers and associated with each of the vertex of the graph. The proposed algorithm runs in time O(n(2)). Here we shown that the program slots of television channels during 24 hours can be modeled as a circular-arc graph. Each program represents a vertex and number of viewers of that program represents the weight of the corresponding vertex. Two vertices are connected by an edge iff the corresponding program slots have a common program time, i.e., if I-i and I-j are the program slots of two programs i and j then the corresponding vertices i and j are connected by an edge iff I-i boolean AND I-j not equal phi. We also shown that the non-overlapping program slots with maximum number of viewers can be selected by computing maximum weight independent set on the corresponding circular-arc graph.
The most efficient currently known algorithms for two-dimensional pattern matching with rotations have a worst case time complexity of O(n(2)m(3)), where the size of the text is n x n and the size of the pattern is m ...
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ISBN:
(纸本)354022341X
The most efficient currently known algorithms for two-dimensional pattern matching with rotations have a worst case time complexity of O(n(2)m(3)), where the size of the text is n x n and the size of the pattern is m x m. In this paper we present a new algorithm for the problem whose running time is 0(n(2),m(2)). (c) 2006 Published by Elsevier B.V.
In this article, we present an approximation algorithm for solving the single source shortest paths problem on weighted polyhedral surfaces. We consider a polyhedral surface P as consisting of n triangular faces, wher...
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In this article, we present an approximation algorithm for solving the single source shortest paths problem on weighted polyhedral surfaces. We consider a polyhedral surface P as consisting of n triangular faces, where each face has an associated positive weight. The cost of travel through a face is the Euclidean distance traveled, multiplied by the face's weight. For a given parameter E, 0 < epsilon < 1, the cost of the computed paths is at most 1 + epsilon times the cost of corresponding shortest paths. Our algorithm is based on a novel way of discretizing polyhedral surfaces and utilizes a generic greedy approach for computing shortest paths in geometric graphs obtained by such discretization. Its running time is O(C(P)(n)/(rootepsilon) log (n)/(epsilon) log (1)/(epsilon)) time, where C(P) captures geometric parameters and the weights of the faces of P.
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