In this paper, we consider a cellular/infostation integrated network which supports on-demand data service delivery over a wireless link to users in a high-speed train. For the requests with different lifetimes and pr...
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ISBN:
(纸本)9781479913510
In this paper, we consider a cellular/infostation integrated network which supports on-demand data service delivery over a wireless link to users in a high-speed train. For the requests with different lifetimes and prices that they are willing to pay, we develop the optimal packet schedule that aims at earning the maximum revenue. To this end, we formulate the problem as an integer linear program (ILP) which is in general NP-hard. However, by exploring the special structure of the formulated ILP, we show that this problem can be turned into a P problem that admits efficient solvers. Specifically, we propose a novel Checker algorithm and prove that this algorithm is guaranteed to find the offline optimal schedule for the intended problem in polynomial time, when the number of total requests is proportional to the length of the total transmission time span. Based on the relevant insights, a class of efficient online Checker algorithms are then developed to approach the optimal schedule when a-priori knowledge of service demands and/or wireless channel capacities is not available in practical systems. It is shown that these online algorithms have a competitive ratio of 1/2, i.e., total revenue earned by them is at least half as much as the revenue earned by offline optimal schedule. Simulation results are provided to demonstrate the merit of the proposed algorithms.
The problem considered in this paper can be expressed as a question: Is it possible to visit all Tube lines in a day? This is a new type of combinatorial optimization problem which generalizes classic problems like TS...
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The problem considered in this paper can be expressed as a question: Is it possible to visit all Tube lines in a day? This is a new type of combinatorial optimization problem which generalizes classic problems like TSP, set cover. It has similarities with classic combinatorial optimization problems and ties with operations research applications. We call the graphs corresponding to the city railway systems subway graphs. Examples and properties of such graphs are described in the paper. We show that our problem is NP-hard. algorithms solving the problem are proposed and their performance is studied both analytically and experimentally on transportation networks of several big cities of the world. (C) 2012 Elsevier Ltd. All rights reserved.
A basic but expensive operation in implementations of several famous public-key crypto-systems is the computation of the multi-exponentiation in a certain finite multiplication group. In 2007, Yang et al. presented an...
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A basic but expensive operation in implementations of several famous public-key crypto-systems is the computation of the multi-exponentiation in a certain finite multiplication group. In 2007, Yang et al. presented an interesting asynchronous multi-exponentiation algorithm called the SUt method, which uses the binary representations for the exponents. In this note, we analyze the computational efficiency of the SUt method by modeling the scanning process as a Markov chain. It shows that their computational efficiency result is incorrect. Moreover, we make a performance comparison among the published techniques and show that the performance of a modified sliding window method is better than that of the SUt method, when there are 4 or more additional registers. We hope that our research will be convenient to the development of the cryptographic devices. (C) 2012 Elsevier By. All rights reserved.
The advent of low-cost, large-scale DNA synthesis, coupled with advanced algorithmic tools, opens the door to a host of exciting new biotechnology applications, including vaccines.
The advent of low-cost, large-scale DNA synthesis, coupled with advanced algorithmic tools, opens the door to a host of exciting new biotechnology applications, including vaccines.
In order to find community structure that exists in complex network structure, this paper introduced K-means approach to the complex network community structure of the research. This paper studies the complex network ...
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ISBN:
(纸本)9783642293894
In order to find community structure that exists in complex network structure, this paper introduced K-means approach to the complex network community structure of the research. This paper studies the complex network of community structure detection algorithm, through the existing algorithm learn and study, proposed an improved algorithm based on K-means. Not know the premise of community structure for the complex networks division, the algorithm is simple and easy to understand, and the algorithm was used in karate network, through experimental verification, experimental results show that the algorithm is effective.
Perfect sorting by reversals, a problem originating in computational genomics, is the process of sorting a signed permutation to either the identity or to the reversed identity permutation, by a sequence of reversals ...
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Perfect sorting by reversals, a problem originating in computational genomics, is the process of sorting a signed permutation to either the identity or to the reversed identity permutation, by a sequence of reversals that do not break any common interval. Berard et al. (2007) make use of strong interval trees to describe an algorithm for sorting signed permutations by reversals. Combinatorial properties of this family of trees are essential to the algorithm analysis. Here, we use the expected value of certain tree parameters to prove that the average run-time of the algorithm is at worst, polynomial, and additionally, for sufficiently long permutations, the sorting algorithm runs in polynomial time with probability one. Furthermore, our analysis of the subclass of commuting scenarios yields precise results on the average length of a reversal, and the average number of reversals.
Random Testing (RT) is an important and fundamental approach to testing computer software. Adaptive Random Testing (ART) has been proposed to improve the fault-detection capability of RT. ART employs the location info...
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Random Testing (RT) is an important and fundamental approach to testing computer software. Adaptive Random Testing (ART) has been proposed to improve the fault-detection capability of RT. ART employs the location information of successful test cases (those that have been executed but not revealed a failure) to enforce an even spread of random test cases across the input domain. Distance-based ART (D-ART) and Restriction-based ART (R-ART) are the first two ART methods, which have considerably improved the fault-detection capability of RT. Both these methods, however, require additional computation to ensure the generation of evenly spread test cases. To reduce the overhead in test case generation, we present in this paper a new ART method using the notion of iterative partitioning. The input domain is divided into equally sized cells by a grid. The grid cells are categorized into three different groups according to their relative locations to successful test cases. In this way, our method can easily identify those grid cells that are far apart from all successful test cases for test case generation. Our method significantly reduces the time complexity, while keeping the high fault-detection capability.
The map-reduce paradigm is now standard in industry and academia for processing large-scale data. In this work, we formalize job scheduling in map-reduce as a novel generalization of the two-stage classical flexible f...
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ISBN:
(纸本)9781450307437
The map-reduce paradigm is now standard in industry and academia for processing large-scale data. In this work, we formalize job scheduling in map-reduce as a novel generalization of the two-stage classical flexible flow shop (FFS) problem: instead of a single task at each stage, a job now consists of a set of tasks per stage. For this generalization, we consider the problem of minimizing the total flowtime and give an efficient 12-approximation in the offline setting and an online (1 + epsilon)-speed O(1/epsilon(2))-competitive algorithm. Motivated by map-reduce, we revisit the two-stage flow shop problem, where we give a dynamic program for minimizing the total flowtime when all jobs arrive at the same time. If there are fixed number of job-types the dynamic program yields a PTAS;it is also a QPTAS when the processing times of jobs are polynomially bounded. This gives the first improvement in approximation of flowtime for the two-stage flow shop problem since the trivial 2-approximation algorithm of Gonzalez and Sahni [29] in 1978, and the first known approximation for the FFS problem. We then consider the generalization of the two-stage FFS problem to the unrelated machines case, where we give an offline 6-approximation and an online (1 + epsilon)-speed O(1/epsilon(4))-competitive algorithm.
The basis for RTL-development and verification system is functional device specification. More often bugs are "produced" when informal transitions from this specification to RTL and "verification enviro...
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ISBN:
(纸本)9789665335870
The basis for RTL-development and verification system is functional device specification. More often bugs are "produced" when informal transitions from this specification to RTL and "verification environment"- code are taken by design and validation engineers. In contrast to this traditional approach the formal transition method to RTL-code and verification environment development is introduced, based on device C-model Control-DataFlow Graph (CDFG) analysis. As an example, in this article the introduced formal approach is applied for JPEG2000 model for getting RTL SystemC-code.
We present a 2D triangle mesh simplification model which is able to produce high quality approximations of any original planar mesh, regardless of the shape of the original mesh. This method consists of two phases: a ...
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We present a 2D triangle mesh simplification model which is able to produce high quality approximations of any original planar mesh, regardless of the shape of the original mesh. This method consists of two phases: a self-organizing algorithm and a triangulation algorithm. The self-organizing algorithm is an unsupervised incremental clustering algorithm which provides us a set of nodes representing the best approximation of the original mesh. The triangulation algorithm reconstructs the simplified mesh from the planar points obtained by the self-organizing training process. Some examples are detailed with the purpose of demonstrating the ability of the model to perform the task of simplifying an original mesh with irregular shape. (C) 2010 Elsevier Inc. All rights reserved.
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