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3rd Computer Science On-line Conference (CSOC)

作者： Kiktenko, Anastasia Lunkovskiy, Mikhail Nikiforov, Konstantin St Petersburg State Univ Fac Appl Math & Control Proc Univ Prospekt 35 St Petersburg 198504 Russia

ISBN: (纸本)9783319067407

This study is focused on informational sensitivity of an algorithm, defined as impact of different fixed-length inputs on the value of the algorithm's complexity function. In addition to classic worst-case complexity this characteristic provides a supplementary tool for more detailed and more "real world'' approach to studying algorithms. Statistical measure of informational sensitivity is calculated based on statistical analysis of results obtained from multiple runs of the same program implementation of the algorithm in question with random inputs. This theory is illustrated by an example of algorithm that solves the travelling salesman problem by branch and bound method using the concorde package. For a sample of different input graphs with 1,000 divided by 10,000 vertices the statistical measurements of informational sensitivity were found and confidence ranges for complexity function were constructed. It was proven that this particular algorithm is highly sensitive to fixed-size inputs by complexity function.

关键词： Informational sensitivity Resource effectiveness algorithm complexity Travelling salesman problem TSP

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A novel time computation model based on algorithm complexity for data intensive scientific workflow design and scheduling

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2009年第16期21卷 2070-2083页

作者： He, Jing Zhang, Yanchun Huang, Guangyan Pang, Chaoyi Victoria Univ Sch Sci & Engn Melbourne Vic 8001 Australia Chinese Acad Sci Res Ctr Fictitious Econ & Data Sci Beijing 100190 Peoples R China

Scientific workflow offers a framework for cooperation between remote and shared resources on a grid computing environment (GCE) for scientific discovery. One major function of scientific workflow is to schedule a collection of computational subtasks in well-defined orders for efficient outputs by estimating task duration at runtime. In this paper, we propose a novel time computation model based on algorithm complexity (termed as TCMAC model) for high-level data intensive scientific workflow design. The proposed model schedules the subtasks based on their durations and the complexities of participant algorithms. Characterized by utilization of task duration computation function for time efficiency, the TCMAC model has three features for a full-aspect scientific workflow including both dataflow and control-flow: (1) provides flexible and reusable task duration functions in GCE;(2) facilitates better parallelism in iteration structures for providing more precise task durations;and (3) accommodates dynamic task durations for rescheduling in selective structures of control flow. We will also present theories and examples in scientific workflows to show the efficiency of the TCMAC model, especially for control-flow. Copyright (C) 2009 John Wiley & Sons, Ltd.

关键词： scientific workflow computation time model dataflow control-flow algorithm complexity

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Predicting algorithmic complexity through structure analysis and compression

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APPLIED SOFT COMPUTING 2013年第8期13卷 3582-3596页

作者： Mann, Zoltan Adam Papp, Pal Andras Budapest Univ Technol & Econ Dept Comp Sci & Informat Theory H-1117 Budapest Hungary

The complexity of an algorithm is usually specified by the maximum number of steps made by the algorithm, as a function of the size of the input. However, as different inputs of equal size can yield dramatically different algorithm runtime, the size of the input is not always an appropriate basis for predicting algorithm runtime. In this paper, we argue that the compressed size of the input is more appropriate for this purpose. In particular, we devise a genetic algorithm for compressing a graph by finding the most compact description of its structure, and we demonstrate how the compressed size of the problem instance correlates with the runtime of an exact algorithm for two hard combinatorial problems (graph coloring and Boolean satisfiability). (C) 2013 Elsevier B. V. All rights reserved.

关键词： algorithm complexity Compression Genetic algorithm Graph coloring #SAT

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A novel time computation model based on algorithm complexity for data intensive scientific workflow design and scheduling

A novel time computation model based on algorithm complexity...

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3rd International Workshop on Workflow Management and Applications in Grid Environments (WaGe2008)

关键词： scientific workflow computation time model dataflow control-flow algorithm complexity

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Enlarging the Gap Between Quantum and Classical Query complexity of Multifunctions

Enlarging the Gap Between Quantum and Classical Query Comple...

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9th International Conference on Natural Computation (ICNC)

作者： Vasilieva, Alina Shishova, Elena Mischenko-Slatenkova, Taisia Univ Latvia Fac Comp Riga Latvia

ISBN: (纸本)9781467347143

Quantum computing aims to use quantum mechanical effects for the efficient performance of computational tasks. A popular research direction is enlarging the gap between classical and quantum algorithm complexity of the same computational problem. We present new results in quantum query algorithm design for multivalued functions that allow to achieve a large quantum versus classical complexity separation. To compute a basic finite multifunction in a quantum model only one query is enough while classically three queries are required. Then, we present two generalizations and a modification of the original algorithm, and obtain the following complexity gaps: Q(UD) (M') <= N versus C-UD (M') >= 3N, and Q(RD) (M '') = 1 versus N/2 + 1 <= C-RD (M '') <= N.

关键词： quantum computing quantum query model algorithm complexity multifunction

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On a facility location problem with applications to tele-diagnostic

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OPTIMIZATION LETTERS 2013年第6期7卷 1179-1192页

作者： Apollonio, N. Caramia, M. Italiano, G. F. Ist Applicaz Calcolo I-00185 Rome Italy Univ Roma Tor Vergata Dipartimento Ingn Impresa I-00133 Rome Italy Univ Roma Tor Vergata Dipartimento Informat Sistemi & Prod I-00133 Rome Italy

Consider an undirected graph G modelling a network. Each vertex in the graph contains some physical devices, which can be monitored and possibly repaired from a remote site in case they become faulty. We assume that there can be two kinds of faults in the system: soft faults, which can be repaired remotely from another site (i.e., a monitor), and severe faults which cannot be repaired remotely and require further (possibly human) interventions. We assume that soft faults happen with some fixed probability lambda, 0 < lambda a parts per thousand currency sign 1. We investigate the problem of locating monitors in the network so as to minimize the total expected communication cost per fault. We formalize such a problem as a location problem with a cost function depending on lambda and study some properties of the optimal solutions. The latter are exploited for investigating the complexity of the problem and providing efficient approximation algorithms.

关键词： algorithm complexity Graph algorithms Location problems

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An improved low-complexity LMMSE channel estimation algorithm

An improved low-complexity LMMSE channel estimation algorith...

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International Conference on Control Engineering and Communication Technology (ICCECT)

作者： Wang, Xuchen Guo, Feng Wuhan Univ Technol Sch Informat Engn Wuhan 430070 Peoples R China

ISBN: (纸本)9781467344999

This paper proposes an improved linear minimum mean square error (LMMSE) algorithm of adaptive order determination by taking advantage of the structure characteristics of time domain least square (LS) channel estimation based on hardware platform, which provides the approximate estimation approach of max-time delay and noise power. In addition, this algorithm achieves a practical channel estimation formula which greatly reduces the complexity of the algorithm by decomposing the autocorrelation matrix into some sub-matrixes on the foundation of correlation bandwidth. Finally, comparisons are made between the simulation performances of improved LMMSE algorithm with those of other estimation methods for further analysis.

关键词： LTE LMMSE adaptive order determination channel parameter algorithm complexity

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Compressed Topology Tomography in Sensor Networks

Compressed Topology Tomography in Sensor Networks

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IEEE Wireless Communications and Networking Conference (WCNC)

作者： Liang, Yao Liu, Rui Indiana Univ Purdue Univ Indianapolis Dept Comp & Informat Sci Indiana PA 15705 USA

ISBN: (纸本)9781467359399;9781467359382

Wireless sensor network (WSN) topology tomography is essential for routing improvement, topology control, anomaly detection and load balance. Previous studies on WSN topology tomography are restricted to static routing tree estimation, which is unrealistic in real-world WSNs due to wireless channel dynamics. We study general WSN routing topology tomography from indirect measurements observed at the sink, where routing structure is dynamic. We formulate the problem as a novel compressed sensing problem, and present our decoding algorithm. We provide rigorous complexity analyses of our algorithm. Thorough simulations validate the effectiveness of our approach and algorithm.

关键词： network tomography wireless sensor networks compressed sensing algorithm complexity

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NOISE EFFECTS IN THE QUANTUM SEARCH algorithm FROM THE VIEWPOINT OF COMPUTATIONAL complexity

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INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS AND COMPUTER SCIENCE 2012年第2期22卷 493-499页

作者： Gawron, Piotr Klamka, Jerzy Winiarczyk, Ryszard Polish Acad Sci Inst Theoret & Appl Informat PL-44100 Gliwice Poland

We analyse the resilience of the quantum search algorithm in the presence of quantum noise modelled as trace preserving completely positive maps. We study the influence of noise on the computational complexity of the quantum search algorithm. We show that it is only for small amounts of noise that the quantum search algorithm is still more efficient than any classical algorithm.

关键词： quantum algorithms quantum noise algorithm complexity

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Channel Estimation algorithms for OFDM-IDMA: complexity and Performance

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2012年第5期11卷 1722-1732页

作者： Hammarberg, Peter Rusek, Fredrik Edfors, Ove Lund Univ Elect & Informat Technol Dept S-22100 Lund Sweden

In this paper, a number of channel estimation algorithms for iterative receivers are compared for the case of an up-link orthogonal frequency division multiplexing interleave division multiple access (OFDM-IDMA) system. Both pilot based algorithms, used to obtain an initial estimate, as well as semi-blind decision-directed algorithms working as a component of the iterative receiver are considered. algorithms performing either joint minimum mean square error (MMSE) channel estimation, or iterative estimation using space-alternating expectation maximization (SAGE), are evaluated. The considered algorithms differ in terms of complexity, as well as performance. The main contribution of this paper is to give an overview of different channel estimation approaches for OFDM-IDMA, where the complexity versus performance tradeoff is at the focal point. There is no single channel estimator providing the best tradeoff and our analysis shows how the system load (number of users) and the SNR influence the estimator choice.

关键词： Channel estimation OFDM-IDMA algorithm complexity expectation maximization (EM) SAGE discrete prolate spheroidal (DPS) sequences

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