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Deterministic broadcast and gossiping algorithms for ad hoc networks

JOURNAL OF SUPERCOMPUTING 2006年第2期37卷 115-144页

作者： Sinha, Koushik Srimani, Pradip K. Clemson Univ Dept Comp Sci Clemson SC 29634 USA

We present in this paper three deterministic broadcast and a gossiping algorithm suitable for ad hoc networks where topology changes range from infrequent to very frequent. The proposed algorithms are designed to work in networks where the mobile nodes possessing collision detection capabilities. Our first broadcast algorithm accomplishes broadcast in O(nlog n) for networks where topology changes are infrequent. We also present an O(nlog n) worst case time broadcast algorithms that is resilient to mobility. For networks where topology changes are frequent, we present a third algorithm that accomplishes broadcast in O(triangle center dot n log n+n center dot vertical bar M vertical bar) in the worst case scenario, where vertical bar M vertical bar is the length of the message to be broadcasted and triangle the maximum node degree. We then extend one of our broadcast algorithms to develop an O(Dn log n + D-2) algorithm for gossiping in the same network model.

关键词： MOBILE communication systems BROADCASTING industry RADIO networks computer algorithms TELECOMMUNICATION systems computer networks TOPOLOGY ELECTRONIC systems TELECOMMUNICATION INFORMATION technology

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Deterministic Importance Sampling with Error Diffusion

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computer GRAPHICS FORUM 2009年第4期28卷 1055-1064页

作者： Szirmay-Kalos, Laszlo Szecsi, Laszlo Tech Univ Budapest Dept Control Engn & Informat Technol Budapest Hungary

This paper proposes a deterministic importance sampling algorithm that is based on the recognition that delta-sigma modulation is equivalent to importance sampling. We propose a generalization for delta-sigma modulation in arbitrary dimensions, taking care of the curse of dimensionality as well. Unlike previous sampling techniques that transform low-discrepancy and highly stratified samples in the unit cube to the integration domain, our error diffusion sampler ensures the proper distribution and stratification directly in the integration domain. We also present applications, including environment mapping and global illumination rendering with virtual point sources.

关键词： computer algorithms computer programming algorithms computer graphics Digital image processing Graph algorithms

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Solving Constrained Global Optimization Problems by Using Hybrid Evolutionary Computing and Artificial Life Approaches

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MATHEMATICAL PROBLEMS IN ENGINEERING 2012年第1期2012卷 1-36页

作者： Wu, Jui-Yu Lunghwa Univ Sci & Technol Dept Business Adm Guishan 333 Taoyuan County Taiwan

This work presents a hybrid real-coded genetic algorithm with a particle swarm optimization (RGA-PSO) algorithm and a hybrid artificial immune algorithm with a PSO (AIA-PSO) algorithm for solving 13 constrained global optimization (CGO) problems, including six nonlinear programming and seven generalized polynomial programming optimization problems. External RGA and AIA approaches are used to optimize the constriction coefficient, cognitive parameter, social parameter, penalty parameter, and mutation probability of an internal PSO algorithm. CGO problems are then solved using the internal PSO algorithm. The performances of the proposed RGA-PSO and AIA-PSO algorithms are evaluated using 13 CGO problems. Moreover, numerical results obtained using the proposed RGA-PSO and AIA-PSO algorithms are compared with those obtained using published individual GA and AIA approaches. Experimental results indicate that the proposed RGA-PSO and AIA-PSO algorithms converge to a global optimum solution to a CGO problem. Furthermore, the optimum parameter settings of the internal PSO algorithm can be obtained using the external RGA and AIA approaches. Also, the proposed RGA-PSO and AIA-PSO algorithms outperform some published individual GA and AIA approaches. Therefore, the proposed RGA-PSO and AIA-PSO algorithms are highly promising stochastic global optimization methods for solving CGO problems.

关键词： GENETIC algorithms PARTICLE swarm optimization computer algorithms MATHEMATICAL optimization COMBINATORIAL optimization LINEAR programming

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Bilevel Traffic Evacuation Model and Algorithm Design for Large-Scale Activities

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MATHEMATICAL PROBLEMS IN ENGINEERING 2017年第1期2017卷 1-13页

作者： Bao, Danwen Gu, Jiayu Jia, Junhua Nanjing Univ Aeronaut & Astronaut Collage Civil Aviat Nanjing 210016 Jiangsu Peoples R China

This paper establishes a bilevel planning model with one master and multiple slaves to solve traffic evacuation problems. The minimum evacuation network saturation and shortest evacuation time are used as the objective functions for the upper-and lower-level models, respectively. The optimizing conditions of this model are also analyzed. An improved particle swarm optimization ( PSO) method is proposed by introducing an electromagnetism-like mechanism to solve the bilevel model and enhance its convergence efficiency. A case study is carried out using the Nanjing Olympic Sports Center. The results indicate that, for large-scale activities, the average evacuation time of the classic model is shorter but the road saturation distribution is more uneven. Thus, the overall evacuation efficiency of the network is not high. For induced emergencies, the evacuation time of the bilevel planning model is shortened. When the audience arrival rate is increased from 50% to 100%, the evacuation time is shortened from 22% to 35%, indicating that the optimization effect of the bilevel planning model is more effective compared to the classic model. Therefore, the model and algorithm presented in this paper can provide a theoretical basis for the traffic-induced evacuation decision making of large-scale activities.

关键词： ELECTROMAGNETISM PROBLEM solving PARTICLE swarm optimization STOCHASTIC convergence computer algorithms

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Research on FCM and NHL Based High Order Mining Driven by Big Data

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MATHEMATICAL PROBLEMS IN ENGINEERING 2015年第1期2015卷 1-7页

作者： Peng, Zhen Peng, Jie Zhao, Wei Chen, Zhenguo Inst Sci & Technol Informat China Resource Sharing & Promot Ctr Beijing 100038 Peoples R China North China Inst Sci & Technol Sch Comp Beijing 101601 Peoples R China

In order to get the high order evaluation and correlation degree among big data with the characteristics of multidimension and multigranularity, an FCM and NHL based high order mining algorithm driven by big data is proposed, which is a kind of machine learning based on qualitative knowledge. The algorithmis applied in scientific and technical talent forecast. Driven by the big data of scientific research track of scientific and technical talents, the index system is designed and the big data is automatically acquired and processed. Accordingly, the high order evaluations in dimension level and target level can be inferred by the correlation weights mining. And the outstanding young talents in material field in 2014 have been actively recommended to review department for decision-making.

关键词： DATA mining DATA analysis computer algorithms DECISION making MACHINE learning

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Comparison of switching control algorithms effective in restricting the switching in the neighborhood of the origin

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SMART MATERIALS AND STRUCTURES 2010年第6期19卷 065003-1-065003-11页

作者： Joung, JinWook Smyth, Andrew W. Chung, Lan Dankook Univ Dept Architectural Engn Gyeonggi Do 448701 South Korea Columbia Univ Dept Civil Engn & Engn Mech New York NY 10027 USA

The active interaction control (AIC) system consisting of a primary structure, an auxiliary structure and an interaction element was proposed to protect the primary structure against earthquakes and winds. The objective of the AIC system in reducing the responses of the primary structure is fulfilled by activating or deactivating the switching between the engagement and the disengagement of the primary and auxiliary structures through the interaction element. The status of the interaction element is controlled by switching control algorithms. The previously developed switching control algorithms require an excessive amount of switching, which is inefficient. In this paper, the excessive amount of switching is restricted by imposing an appropriately designed switching boundary region, where switching is prohibited, on pre-designed engagement-disengagement conditions. Two different approaches are used in designing the newly proposed AID-off and AID-off 2 algorithms. The AID-off 2 algorithm is designed to affect deactivated switching regions explicitly, unlike the AID-off algorithm, which follows the same procedure of designing the engagement-disengagement conditions of the previously developed algorithms, by using the current status of the AIC system. Both algorithms are shown to be effective in reducing the amount of switching times triggered from the previously developed AID algorithm under an appropriately selected control sampling period for different earthquakes, but the AID-off 2 algorithm outperforms the AID-off algorithm in reducing the number of switching times.

关键词： algorithms Primary structure boundary regions Earthquakes computer algorithms Disconnection switching annexe

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Soylent: A Word Processor with a Crowd Inside

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COMMUNICATIONS OF THE ACM 2015年第8期58卷 85-94页

作者： Bernstein, Michael S. Little, Greg Miller, Robert C. Hartmann, Bjoern Ackerman, Mark S. Karger, David R. Crowell, David Panovich, Katrina Stanford Univ Stanford CA 94305 USA Univ Calif Berkeley Div Comp Sci Berkeley CA 94720 USA Univ Michigan Comp Sci & Engn Ann Arbor MI 48109 USA MIT CSAIL Cambridge MA USA Google Inc Mountain View CA USA

This paper introduces architectural and interaction patterns for integrating crowdsourced human contributions directly into user interfaces. We focus on writing and editing, complex endeavors that span many levels of conceptual and pragmatic activity. Authoring tools offer help with pragmatics, but for higher-level help, writers commonly turn to other people. We thus present Soylent, a word processing interface that enables writers to call on Mechanical Turk workers to shorten, proofread, and otherwise edit parts of their documents on demand. To improve worker quality, we introduce the Find-Fix-Verify crowd programming pattern, which splits tasks into a series of generation and review stages. Evaluation studies demonstrate the feasibility of crowdsourced editing and investigate questions of reliability, cost, wait time, and work time for edits.

关键词： Crowdsourcing computer architecture User interfaces (computer systems) Human-machine systems computer programming Electronic data processing computer algorithms

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Tabled logic programming based IP matching tool using forced simulation

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IEE PROCEEDINGS-computerS AND DIGITAL TECHNIQUES 2004年第3期151卷 199-208页

作者： Roop, PS Sowmya, A Ramesh, S Guo, HF Univ Auckland Dept ECE Auckland 1 New Zealand Univ New S Wales Sch CSE Sydney NSW 2052 Australia Indian Inst Technol Dept CSE Bombay 400076 Maharashtra India Univ Nebraska Dept CS Omaha NE 68182 USA

Automatic IP (intellectual property) matching is a key to the reuse of IP cores. A new tabled logic programming-based IP matching algorithm is given that can check whether a given programmable IP can be adapted to match a given specification. When such adaptation is possible, the algorithm also generates a device driver (an interface) to adapt the IP. Though simulation, refinement and bisimulation algorithms exist, they cannot be used to check the adaptability of an IP, which is the essence of reuse. The IP matching algorithm is based on a formal verification technique called forced simulation. A forced simulation matching algorithm is implemented using a tabled logic programming environment, which provides distinct advantages for encoding such an algorithm. The tool has been used to match several specifications to programmable IN, achieving on an average 12 times speedup and 64% reduction in code size in comparison with previously published algorithms.

关键词： LOGIC programming computer programming computer algorithms ELECTRONIC systems SYSTEMS design computer simulation

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An effective memetic differential evolution algorithm based on chaotic local search

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INFORMATION SCIENCES 2011年第15期181卷 3175-3187页

作者： Jia, Dongli Zheng, Guoxin Khan, Muhammad Khurram Shanghai Univ Key Lab Special Fiber Opt & Opt Access Networks Shanghai 200072 Peoples R China Hebei Univ Engn Sch Informat & Elect Engn Handan 056038 Peoples R China King Saud Univ CoEIA Riyadh 11653 Saudi Arabia

This paper proposes an effective memetic differential evolution (DE) algorithm, or DECLS, that utilizes a chaotic local search (CLS) with a 'shrinking' strategy. The CLS helps to improve the optimizing performance of the canonical DE by exploring a huge search space in the early run phase to avoid premature convergence, and exploiting a small region in the later run phase to refine the final solutions. Moreover, the parameter settings of the DECLS are controlled in an adaptive manner to further enhance the search ability. To evaluate the effectiveness and efficiency of the proposed DECLS algorithm, we compared it with four state-of-the-art DE variants and the IPOP-CMA-ES algorithm on a set of 20 selected benchmark functions. Results show that the DECLS is significantly better than, or at least comparable to, the other optimizers in terms of convergence performance and solution accuracy. Besides, the DECLS has also shown certain advantages in solving high dimensional problems. (C) 2011 Elsevier Inc. All rights reserved.

关键词： EVOLUTIONARY computation NEURAL networks (computer science) computer algorithms ARTIFICIAL intelligence MEMETICS CHAOS theory STOCHASTIC convergence MATHEMATICAL optimization

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Ontology population as algebraic information system processing based on multi-agent natural language text analysis algorithms

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PROGRAMMING AND computer SOFTWARE 2015年第3期41卷 140-148页

作者： Garanina, N. O. Sidorova, E. A. Russian Acad Sci AP Ershov Inst Informat Syst Siberian Div Novosibirsk 630090 Russia

The paper presents an approach to ontology population as operations with Scott information system. The deducibility relation in the ontology population information system corresponds to rules of input data processing and ontology population. To implement an ontology population process, we suggest a multi-agent approach based on natural language semantic analysis. In the proposed multi-agent model, agents of the following two types interact: information agents corresponding to meaningful units of the information being retrieved and rule agents implementing population rules of the given ontology based on the semantic-syntactic model of the language.

关键词： INFORMATION processing INFORMATION storage & retrieval systems MULTIAGENT systems NATURAL language processing (computer science) computer algorithms ONTOLOGY

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