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14th IEEE International conference on Image Processing, ICIP 2007

作者： Bo, Wang Zhihai, He Yu, Sun Dept. of Electrical and Computer Engineering University of Missouri Columbia MO 65211 United States Department of Computer Science University of Central Arkansas Conway AR United States

ISBN: (纸本)1424414377

Video streaming imposes high rate requirement and stringent constraints on resource limited mesh networks. In this work, we develop a distributed asynchronous particle swarm optimization (DAPSO) algorithm for resource allocation and performance optimization scheme for video communication over large-scale mesh networks. Unlike many network resource allocation performance optimization algorithms in the literatures which are able to handle convex network utility functions, the proposed scheme is able to handle generic nonlinear network utility functions. We will use a specific rate allocation and quality optimization problem for an example to demonstrate the efficiency of the proposed scheme and compare its performance with other algorithms, such as distributed gradient search. ©2007 IEEE.

关键词： Video streaming

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Robust control design on Scilab: Hybrid remotely operated vehicle

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COMPUTER APPLICATIONS IN ENGINEERING EDUCATION 2023年第6期31卷 1776-1795页

作者： Roque-Quispe, Alejandra C. Alvarez-Quispe, Andres B. J. Yanyachi, Pablo R. Yanyachi, Daniel Cutipa-Luque, Juan C. Univ Nacl San Agustin Arequipa Lab control Proc complejos & vehiculos tripulados Arequipa Peru Univ Nacl San Agustin Arequipa Lab control Proc complejos & vehiculos tripulados Santa Catalina 117 Arequipa 04000 Peru

The goal of this work is to demonstrate the advanced features of Scilab/Xcos software in the process of designing robust controllers and to validate them numerically by a multivariable system with high coupled dynamics;it is a hybrid remotely operated vehicle (HROV). The methodology presents five steps which are the nonlinear model representation, the model linearization, the building of augmented plants, the synthesis of robust controllers through the optimization algorithms, and the plotting of the results. Linear models can be obtained straightforwardly at many operation points. The robust controllers are synthesized using the H & INFIN;${{\rm{ {\mathcal H} }}}_{\infty }$ mixed sensitivity approach and tested in Scilab script and in the Xcos block diagram interface. The surge and yaw rate vehicle dynamics are controlled by a centralized controller;obtaining a good settling time, of less than 14 s, without overshooting and mitigating the coupling dynamics. Moreover, the good shaping in sensitivity and complementary sensitivity indicates robustness in performance and stability for the HROV. The proposed methodology includes time and frequency domain analysis, among other advanced features, to overcome the need for commercial software.

关键词： engineering tools nonlinear dynamics remotely operated vehicle robust control simulation

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Improving particle swarm optimization performance with local search for high-dimensional function optimization

Improving particle swarm optimization performance with local...

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2nd International conference on nonlinear Programming with Applications

作者： Wang, Yong-Jun Tsinghua Univ Sch Aerosp Beijing 100084 Peoples R China CNPC BGP Zhuozhou 072751 Peoples R China

Particle swarm optimization (PSO) is one recently proposed population-based stochastic optimization technique, and gradient-based descent methods are efficient local optimization techniques that are often used as a necessary ingredient of hybrid algorithms for global optimization problems (GOPs). By examining the properties of the two methods, a two-stage hybrid algorithm for global optimization is proposed. In the present algorithm, the gradient descent technique is used to find a local minimum of the objective function efficiently, and a PSO method with latent parallel search capability is employed to help the algorithm to escape from the previously converged local minima to a better point which is then used as a starting point for the gradient methods to restart a new local search. The above search procedure is applied repeatedly until a global minimum is found (when a global minimum is known in advance) or the maximum number of function evaluations is reached. In addition, a repulsion technique and partially initializing population method are incorporated in the new algorithm to increase its global jumping ability. Simulation results on 15 test problems including five large-scale ones with dimensions up to 1000 demonstrate that the proposed method is more stable and efficient than several other existing methods.

关键词： global optimization gradient descent method particle swarm optimization (PSO) repulsion technique

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Deterministic global optimization using space-filling curves and multiple estimates of Lipschitz and Holder constants

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COMMUNICATIONS IN nonlinear SCIENCE AND NUMERICAL SIMULATION 2015年第1-3期23卷 328-342页

作者： Lera, Daniela Sergeyev, Yaroslav D. Univ Cagliari Dipartimento Matemat & Informat Cagliari Italy Univ Calabria Dipartimento Ingn Informat Modellist Elettron & S Via Pietro Bucci 42C I-87036 Arcavacata Di Rende CS Italy Natl Res Council Italy Inst High Performance Comp & Networking I-87036 Arcavacata Di Rende CS Italy NI Lobachevskiy Univ Nizhni Novgorod Software Dept Nizhnii Novgorod Russia

In this paper, the global optimization problem min(y is an element of S) F(y) with S being a hyperinterval in R-N and F(y) satisfying the Lipschitz condition with an unknown Lipschitz constant is considered. It is supposed that the function F(y) can be multiextremal, non-differentiable, and given as a 'black-box'. To attack the problem, a new global optimization algorithm based on the following two ideas is proposed and studied both theoretically and numerically. First, the new algorithm uses numerical approximations to space-filling curves to reduce the original Lipschitz multi-dimensional problem to a univariate one satisfying the Holder condition. Second, the algorithm at each iteration applies a new geometric technique working with a number of possible Holder constants chosen from a set of values varying from zero to infinity showing so that ideas introduced in a popular DIRECT method can be used in the Holder global optimization. Convergence conditions of the resulting deterministic global optimization method are established. Numerical experiments carried out on several hundreds of test functions show quite a promising performance of the new algorithm in comparison with its direct competitors. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Global optimization Lipschitz functions Space-filling curves Holder functions Deterministic numerical algorithms DIRECT Classes of test functions

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Design and optimization of Multilayer Cylindrical Magnetic Shield for SERF Atomic Magnetometer Application

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IEEE SENSORS JOURNAL 2020年第4期20卷 1793-1800页

作者： Li, Jundi Quan, Wei Han, Bangcheng Wang, Zhuo Fang, Jiancheng Beihang Univ Innovat Res Inst Frontier Sci & Technol Beijing 100191 Peoples R China Beihang Univ Adv Innovat Ctr Biomed Engn Beijing 100191 Peoples R China Beijing Acad Quantum Informat Sci Beijing 100094 Peoples R China

A set of five-layer cylindrical magnetic shields is designed and constructed to attenuate external geomagnetic field to less than 10 nT (ideally zero). We aim to achieve a shield design having high shielding factor, low magnetic noise, and small volume. However, magnetic noise is incompatible with shielding factor and volume. Thus, there is a compromise. This paper presents an optimization method to acquire a sufficiently effective, low-noise, and lightweight multi-layer shield. The optimization objective and constraints are provided in the form of analytic expressions. The mathematical model is constructed in MATLAB. The optimization is executed in iSIGHT software integrated MATLAB. By optimizing the nonlinear programming quadratic line (NLPQL) algorithm, theoretically the axial shielding factor S-tot(A) can be increased by a factor of about 390.3, on the premise that the magnetic noise and volume have increased negligibly. Apart from better shielding performance, a combination of optimum parameters is obtained. This optimization method has good universality. As long as certain shielding requirements are determined, the corresponding optimum parameters can be acquired accurately. This method is of great significance for future improvements to shield design.

关键词： Magnetic sensors design optimization magnetic shielding finite element analysis iterative algorithms

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VETRA - offline analysis and monitoring software platform for the LHCb Vertex Locator

VETRA - offline analysis and monitoring software platform fo...

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17th International conference on Computing in high Energy and Nuclear Physics (CHEP)

作者： Szumlak, Tomasz Univ Glasgow Dept Phys & Astron Glasgow G12 8QQ Lanark Scotland

The LHCb experiment is dedicated to studying CP violation and rare decay phenomena. In order to achieve these physics goals precise tracking and vertexing around the interaction point is crucial. This is provided by the VELO (VErtex LOcator) silicon detector. After digitization, FPGAs are employed to run several algorithms to suppress noise and reconstruct clusters. This is performed by an FPGA based processing board. An off-line software project, VETRA, has been developed which performs a bit perfect emulation of this complex processing in the FPGAs. This is a novel development as this hardware emulation is not standalone but rather is fully integrated into the LHCb software to allow the reconstruction of full data from the detector. This software platform facilitates the development and understanding of the behaviour of the processing algorithms, the optimization of the parameters of the algorithms that will be loaded into the FPGA and monitoring of the detector performance. This framework has also been adopted by the Silicon Tracker detector of LHCb. This processing framework was successfully used with the first 1500 tracks of data in the VELO obtained from the first LHC beam in September 2008. The software architecture and utilisation of the VETRA project will be discussed in detail.

关键词： Field programmable gate arrays (FPGA)

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Emulation performance Study of Traffic-Aware Policy Enforcement in software Defined Networks 11

Emulation Performance Study of Traffic-Aware Policy Enforcem...

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11th IEEE International conference on Mobile Ad Hoc and Sensor Systems

作者： Vawter, Isaac Pan, Deng Ma, Wenrui Univ Massachusetts Dept Comp Sci Amherst MA 01003 USA Florida Int Univ Dept Comp Sci Miami FL 33199 USA

ISBN: (纸本)9781479960361

Modern networks require robust traffic handling policies in order to minimize unwanted traffic and maximize performance. These policies are enforced by the placement of rules on network devices such as routers and switches. For high-speed processing, the rules are stored in Ternary Content Addressable Memory (TCAM) [3]. Because it is expensive, there is only a limited amount of TCAM on each network device. software Defined Networking (SDN) [2] and the OpenFlow [1] protocol provide the capability to control the way rules are generated and placed within a network. This allows researchers to design algorithms that control TCAM usage while optimizing performance. The goal of this project is to develop a test bed for researchers to easily implement and evaluate their performance-optimizing algorithms. In this paper, we describe a test bed that emulates SDN activity and captures network performance data for rule placement algorithm evaluation.

关键词： software Defined Networking OpenFlow Network Emulation performance optimization Link Load

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Resource Allocation in Cognitive Heterogeneous Networks Considering the Arrival of Primary Users

Resource Allocation in Cognitive Heterogeneous Networks Cons...

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IEEE International conference on Communication software and Networks (ICCSN)

作者： Shi, Shuo Liang, Nan Gu, Xuemai Harbin Inst Technol Commun Res Ctr Harbin Peoples R China

ISBN: (纸本)9781479919840

Recently, cognitive heterogeneous networks (CHNs) have attracted more attention of the researchers' because of the heterogeneity of the cognitive radio networks, and also the high efficiency of spectrum utilization. A resource allocation algorithm in CHNs based on the convex optimization theory is studied in this paper, considering the probability of the primary users'(PUs) arrival. The goal of the algorithm is to minimize the transmitting delay of SUs during the communication via different radio access technologies(RATs). A model of two state birth-death process is used to describe the probability of PUs using the channel in the paper. The numerical results show that the proposed algorithm can improve the delay performance of the system and it outperforms other algorithms in the references.

关键词： resources allocation CHN arrival convex optimization

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A Domain-specific Language to Facilitate software Defined Radio Parallel Executable Patterns Deployment on Heterogeneous Architectures

A Domain-specific Language to Facilitate Software Defined Ra...

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33rd IEEE International performance, Computing, and Communications conference (IPCCC)

作者： Mohapi, Lerato J. Winberg, Simon Inggs, Michael Univ Cape Town Radar Remote Sensing Grp Dept Elect Engn ZA-7925 Cape Town South Africa

ISBN: (纸本)9781479975754

In this paper, we present a domain-specific language, referred to as OptiSDR, that matches high level digital signal processing (DSP) routines for software defined radio (SDR) to their generic parallel executable patterns targeted to heterogeneous computing architectures (HCAs). These HCAs includes a combination of hybrid GPU-CPU and DSP-FPGA architectures that are programmed using different programming paradigms such as C/C++, CUDA, OpenCL, and/or VHDL. OptiSDR presents an intuitive single high-level source code and near specification-level approach for optimization and facilitation of HCAs. OptiSDR uses an optimized embedded domain-specific language (DSL) compiler framework called Delite. Our focus is on the programming language expressiveness for parallel programming and optimization of typical DSP algorithms for deployment on SDR HCAs. We demonstrate the capability of OptiSDR to express the solution to the issues of parallel DSP low-level implementation complexities in the closest way to the original parallel programming of SDR systems. This paper will achieve these by focusing on three generic parallel executable patterns suitable for DSP routines such as cross-correlation, convolution in FIR filter based Hilbert transformers, and fast Fourier transforms for spectral analysis. This paper concludes with a performance analysis using DSP algorithms that tests automatically generated code against hand-crafted solutions.

关键词： FIR filters Hilbert transforms convolution fast Fourier transforms parallel programming program compilers programming languages signal processing software radio spectral analysis telecommunication computing DSL compiler framework DSP algorithms DSP routines DSP-FPGA architectures Delite FIR filter OptiSDR SDR HCA cross-correlation digital signal processing domain-specific language heterogeneous computing architectures high-level source code hybrid GPU-CPU parallel executable patterns deployment programming language programming paradigms software defined radio Computer architecture DSL Digital signal processing Finite impulse response filters Graphics processing units Programming

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Parallelization of a non-linear multi-objective optimization algorithm: Application to a location problem

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APPLIED MATHEMATICS AND COMPUTATION 2015年 255卷 114-124页

作者： Gila Arrondo, Aranzazu Redondo, Juana L. Fernandez, Jose Ortigosa, Pilar M. Univ Murcia Dept Stat & Operat Res Murcia Spain Univ Granada Dept Comp Architecture & Technol CeiA3 Agrifood Campus Int Excellence Granada Spain Univ Almeria CeiA3 Dept Informat Agrifood Campus Int Excellence Almeria Spain

Real-life problems usually include conflicting objectives. Solving multi-objective problems (i.e., obtaining the complete efficient set and the corresponding Pareto-front) via exact methods is in many cases nearly intractable. In order to cope with those problems, several (meta) heuristic procedures have been developed during the last decade whose aim is to obtain a good discrete approximation of the Pareto-front. In this vein, a new multi-objective evolutionary algorithm, called FEMOEA, which can be applied to many nonlinear multi-objective optimization problems, has recently been proposed. Through a comparison with an exact interval branch-and-bound algorithm, it has been shown that FEMOEA provides very good approximations of the Pareto-front. Furthermore, it has been compared to the reference algorithms NSGA-II, SPEA2 and MOEA/D. Comprehensive computational studies have shown that, among the studied algorithms, FEMOEA was the one providing, on average, the best results for all the quality indicators analyzed. However, when the set approximating the Pareto-front must have many points (because a high precision is required), the computational time needed by FEMOEA may not be negligible at all. Furthermore, the memory requirements needed by the algorithm when solving those instances may be so high that the available memory may not be enough. In those cases, parallelizing the algorithm and running it in a parallel architecture may be the best way forward. In this work, a parallelization of FEMOEA, called FEMOEA-Paral, is presented. To show its applicability, a bi-objective competitive facility location and design problem is solved. The results show that FEMOEA-Paral is able to maintain the effectiveness of the sequential version and this by reducing the computational costs. Furthermore, the parallel version shows good scalability. The efficiency results have been analyzed by means of a profiling and tracing toolkit for performance analysis. (C) 2014 Elsevier Inc. All

关键词： nonlinear multi-objective optimization Multi-objective evolutionary algorithm Parallelism Efficiency Effectiveness Tuning and Analysis Utilities performance System Facility location problem

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