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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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) log n log vertical bar Sigma vertical bar) and O(vertical bar Sigma vertical bar n(2) log(2) n log log n), with Sigma denoting the alphabet. The algorithm by Fischer and Paterson makes crucial use of the FFT, which is impractical with long sequences. The present paper describes an off-line algorithm for binary strings that takes O(n(2)) time. The algorithm does not need to resort to the FFT and yet its performance is optimal for finite Sigma.
We investigate the problem of getting to a higher instruction-level parallelism in string matching algorithms. In particular, starting from an algorithm based on bit-parallelism, we propose two flexible approaches for...
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ISBN:
(纸本)9783642131219
We investigate the problem of getting to a higher instruction-level parallelism in string matching algorithms. In particular, starting from an algorithm based on bit-parallelism, we propose two flexible approaches for boosting it with a higher level of parallelism. These approaches are general enough to be applied to other bit-parallel algorithms. It turns out that higher levels of parallelism lead to more efficient solutions in practical cases, as demonstrated by an extensive experimentation.
A token is hidden in one of several boxes and then the boxes are locked. The probability of placing the token in each of the boxes is known. A searcher is looking for the token by unlocking boxes where each box is ass...
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ISBN:
(纸本)9781605588889
A token is hidden in one of several boxes and then the boxes are locked. The probability of placing the token in each of the boxes is known. A searcher is looking for the token by unlocking boxes where each box is associated with an unlocking cost. The searcher conducts its search in rounds and must find the token in a predetermined number of rounds. In each round, the searcher may unlock any set of locked boxes concurrently. The optimization goal is to minimize the expected cost of unlocking boxes until the token is found. The motivation and main application of this game is the task of paging a mobile user (token) who is roaming in a zone of cells (boxes) in a cellular network system. Here, the unlocking costs reflect cell congestions and the placing probabilities represent the likelihood of the user residing in particular cells. Another application is the task of finding some data (token) that may be known to one of the sensors (boxes) of a sensor network. Here, the unlocking costs reflect the energy consumption of querying sensors and the placing probabilities represent the likelihood of the data being found in particular sensors. In general, we call mobile data any entity that has to be searched for. The special case, in which all the boxes have equal unlocking costs has been well studied in recent years and several optimal polynomial time solutions exist. To the best of our knowledge, this paper is the first to study the general problem in which each box may be associated with a different unlocking cost. We first present three special interesting and important cases for which optimal polynomial time algorithms exist: (i) There is no a priori knowledge about the location of the token and therefore all the placing probabilities are the same. (ii) There are no delay constraints so in each round only one box is unlocked. (iii) The token is atypical in the sense that it is more likely to be placed in boxes whose unlocking cost is low. Next, we consider the case of a
In this paper, we study an semi-online version of bin stretching problem on m parallel identical machines. Where the jobs arrive sorted by non-increasing processing times. We propose an semi-online algorithm and prove...
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In this paper, we study an semi-online version of bin stretching problem on m parallel identical machines. Where the jobs arrive sorted by non-increasing processing times. We propose an semi-online algorithm and prove that the competitive ratio of the algorithm is at most 1 + m-1-4m-2 < 5/4. We also show that the lower bound of the problem is at least 10/9.
Scaled Matching refers to the problem of finding all locations in the text where the pattern, proportionally enlarged according to an arbitrary real-sized scale, appears. Scaled matching is an important problem that w...
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Scaled Matching refers to the problem of finding all locations in the text where the pattern, proportionally enlarged according to an arbitrary real-sized scale, appears. Scaled matching is an important problem that was originally inspired by Computer Vision. Finding a combinatorial definition that captures the concept of real scaling in discrete images has been a challenge in the pattern matching field. No definition existed that captured the concept of real scaling in discrete images, without assuming an underlying continuous signal, as done in the image processing field. We present a combinatorial definition for real scaled matching that scales images in a pleasing natural manner. We also present efficient algorithms for real scaled matching. The running times of our algorithms are as follows. For T, a two-dimensional nxn text array, and P, an mxm pattern array, we find in T all occurrences of P scaled to any real value in time O(nm (3)+n (2) mlog m).
The computation of geodesic distances or paths between two points on triangulated meshes is a common operation in many computer graphics applications. In this article, we present an exact algorithm for the single-sour...
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The computation of geodesic distances or paths between two points on triangulated meshes is a common operation in many computer graphics applications. In this article, we present an exact algorithm for the single-source all-vertices shortest path problem. Mitchell et al. [1987] proposed an O(n(2) log n) method (MMP), based on Dijkstra's algorithm, where n is the complexity of the polyhedral surface. Then, Chen and Han [1990] (CH) improved the running time to O(n(2)). Interestingly Surazhsky et al. [2005] provided experimental evidence demonstrating that the MMP algorithm runs many times faster, in practice, than the CH algorithm. The CH algorithm encodes the structure of the set of shortest paths using a set of windows on the edges of the polyhedron. Our experiments showed that in many examples over 99% of the windows created by the CH algorithm are of no use to define a shortest path. So this article proposes to improve the CH algorithm by two separate techniques. One is to filter out useless windows using the current estimates of the distances to the vertices, the other is to maintain a priority queue like that achieved in Dijkstra's algorithm. Our experimental results suggest that the improved CH algorithm, in spite of an O(n(2) log n) asymptotic time complexity, greatly outperforms the original CH algorithm in both time and space. Furthermore, it generally runs faster than the MMP algorithm and uses considerably less space.
One of the main challenges in algorithmic mechanism design is to turn (existing) efficient algorithmic Solutions into efficient truthful mechanisms. Building a truthful mechanism is indeed a difficult process since th...
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One of the main challenges in algorithmic mechanism design is to turn (existing) efficient algorithmic Solutions into efficient truthful mechanisms. Building a truthful mechanism is indeed a difficult process since the underlying algorithm must obey certain "monotonicity" properties and suitable payment functions need to be computed (this task usually represents the bottleneck in the overall time complexity). We provide a general technique for building truthful mechanisms that provide optimal solutions in strongly polynomial time. We show that the entire mechanism can be obtained if one is able to express/write a strongly polynomial-time algorithm (for the corresponding optimization problem) as a "suitable combination" of simpler algorithms. This approach applies to a wide class of mechanism design graph problems, where each selfish agent corresponds to a weighted edge in a graph (the weight of the edge is the cost of using that edge). Our technique can be applied to several optimization problems which prior results cannot handle (e.g., MIN-MAX optimization problems). As an application, we design the first (strongly polynomial-time) truthful mechanism for the minimum diameter spanning tree problem, by obtaining it directly from an existing algorithm for solving this problem. For this non-utilitarian MIN-MAX problem, no truthful mechanism was known, even considering those running in exponential time (indeed, exact algorithms do not necessarily yield truthful mechanisms). Also, standard techniques for payment computations may result in a running time which is not polynomial in the size of the input graph. The overall running time of our mechanism, instead, is polynomial in the number n of nodes and in of edges, and it is only a factor O(n alpha(n, n)) away from the best known canonical centralized algorithm. (C) 2009 Elsevier B.V. All rights reserved.
The block sorting problem is the problem of minimizing the number of steps to sort a list of distinct items, where a sublist of items which are already in sorted order, called a block, can be moved in one step. We giv...
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The block sorting problem is the problem of minimizing the number of steps to sort a list of distinct items, where a sublist of items which are already in sorted order, called a block, can be moved in one step. We give an approximation algorithm for the block sorting problem with an approximation ratio of 2 and run time O(n(2)). The approximation algorithm is based oil the related concept of block deletion. We show that finding an optimum block deletion sequence can be done in O(n(2)) time, even though block sorting is known to be N P-hard. Block sorting has importance in connection with optical character recognition (OCR) and is related to transposition sorting in computational biology. (C) 2009 Published by Elsevier B.V.
Scalable energy-efficient training protocols are proposed for wireless networks consisting of sensors and a single actor, where the sensors are initially anonymous and unaware of their location. The protocols are base...
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Scalable energy-efficient training protocols are proposed for wireless networks consisting of sensors and a single actor, where the sensors are initially anonymous and unaware of their location. The protocols are based on an intuitive coordinate system imposed onto the deployment area, which partitions the sensors into clusters. The protocols are asynchronous, in the sense that the sensors wake up for the first time at random, then alternate between sleep and awake periods both of fixed length, and no explicit synchronization is performed between them and the actor. Theoretical properties are stated under which the training of all the sensors is possible. Moreover, both worst-case and average case analyses of the performance, as well as an experimental evaluation, are presented showing that the protocols are lightweight and flexible.
One of the main challenges in algorithmic mechanism design is to turn (existing) efficient algorithmic Solutions into efficient truthful mechanisms. Building a truthful mechanism is indeed a difficult process since th...
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ISBN:
(纸本)3540681388
One of the main challenges in algorithmic mechanism design is to turn (existing) efficient algorithmic Solutions into efficient truthful mechanisms. Building a truthful mechanism is indeed a difficult process since the underlying algorithm must obey certain "monotonicity" properties and suitable payment functions need to be computed (this task usually represents the bottleneck in the overall time complexity). We provide a general technique for building truthful mechanisms that provide optimal solutions in strongly polynomial time. We show that the entire mechanism can be obtained if one is able to express/write a strongly polynomial-time algorithm (for the corresponding optimization problem) as a "suitable combination" of simpler algorithms. This approach applies to a wide class of mechanism design graph problems, where each selfish agent corresponds to a weighted edge in a graph (the weight of the edge is the cost of using that edge). Our technique can be applied to several optimization problems which prior results cannot handle (e.g., MIN-MAX optimization problems). As an application, we design the first (strongly polynomial-time) truthful mechanism for the minimum diameter spanning tree problem, by obtaining it directly from an existing algorithm for solving this problem. For this non-utilitarian MIN-MAX problem, no truthful mechanism was known, even considering those running in exponential time (indeed, exact algorithms do not necessarily yield truthful mechanisms). Also, standard techniques for payment computations may result in a running time which is not polynomial in the size of the input graph. The overall running time of our mechanism, instead, is polynomial in the number n of nodes and in of edges, and it is only a factor O(n alpha(n, n)) away from the best known canonical centralized algorithm. (C) 2009 Elsevier B.V. All rights reserved.
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