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检索条件"任意字段=International Workshop on Multilevel Optimization - Algorithms and Applications"

共 1022 条记录，以下是381-390 订阅

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2nd international workshop on Adaptive Resource Management and Scheduling for Cloud Computing, ARMS-CC 2015 held in Conjunction with ACM Symposium on Principles of Distributed Computing, PODC 2015

2nd International Workshop on Adaptive Resource Management a...

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2nd international workshop on Adaptive Resource Management and Scheduling for Cloud Computing, ARMS-CC 2015

ISBN: (纸本)9783319284477

The proceedings contain 13 papers. The special focus in this conference is on Adaptive Resource Management and Scheduling for Cloud Computing. The topics include: Competitive analysis of task scheduling algorithms on a fault-prone machine and the impact of resource augmentation;using performance forecasting to accelerate elasticity;parametric analysis of mobile cloud computing frameworks using simulation modeling;bandwidth-aware resource optimization for SMT processors;user-guided provisioning in federated clouds for distributed calculations;a case of mobile-cloud collaborative computing under mobility;impact of virtual machines heterogeneity on data center power consumption in data-intensive applications;implementing the cloud software to data approach for openstack environments;cloud services composition through cloud patterns;a performance evaluation of hadoop’s schedulers under failures;partitioning graph databases by using access patterns and challenges and methodologies for acceleration.

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An Optimal Budget Assignment of Real-Time Query Processing for Wireless Sensor Networks in Context of the Internet of Things

An Optimal Budget Assignment of Real-Time Query Processing f...

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workshop on Computer Architecture, Embedded Systems, SoC, and VLSI/EDA / international Computer Symposium (ICS)

作者： Lu, Yung-Feng Kuo, Chin-Fu Suei, Pei-Lun Pao, Wei-Chen Natl Taichung Univ Sci & Technol Dept Comp Sci & Informat Engn Taichung Taiwan Natl Univ Kaohsiung Dept Comp Sci & Informat Engn Kaohsiung Taiwan

ISBN: (纸本)9781614994848;9781614994831

With the development of sensor, wireless mobile communication, embedded system and cloud computing, the technologies of Internet of Things (IOT) have been widely used in logistics, Smart Meter, public security, intelligent building and so on. The Internet of Things is regarded as the third wave of information technology after Internet and mobile communication network, which is characterized by more thorough sense and measure, more comprehensive inter operability and intelligence. Wireless Sensor Networks (WSN) is one of the most important building block for the IOT. It also have recently been in the limelight for many domains. WSN are useful in data collection, event detection or entity tracking applications. The characteristics of sensor networks have imposed various restrictions on their system designs. Since sensor nodes usually are developed by low-cost hardware, one major challenge in the development of many sensor-network applications is to provide high-security features with limited resources. In this paper, we propose a path generation framework with deadline considerations for real-time query processing. To meet the deadline, the framework will assign the time budget to the routing path, and then, derive a feasible path with the assigned time budget. To derive the optimal assignment of time budgets, this propose DP-base algorithms to solve this problem.

关键词： Internet of Things Query optimization Routing Wireless Sensor Networks

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Hamiltonian trajectories in a heterogeneous economic growth model for optimization resource productivity 16

Hamiltonian trajectories in a heterogeneous economic growth ...

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16th IFAC workshop on Control applications of optimization, CAO 2015

作者： Tarasyev, Alexander Usova, Anastasiia Wang, Wei Institute of Mathematics and Mechanics of the Ural Branch of the Russian Academy of Sciences S.Kovalevskaya str. 16 Ekaterinburg6220990 Russia Center for Industrial Ecology Department of Chemical Engineering TsinrhuLa University China

In the paper, a dynamic mechanism for optimization of resource productivity is analyzed witliin the economic growth model framework. The reoearch deals with the problem of shortage of natural resources, security of supply of energy and materials, and environmbntal impact of uncoiitrollsibk resource eonsumption. The model is (instructed within the framework of the mathematical theory of optimal control for problems with infinite horizon. The maik dement ot the model is phase constraints (on the resource consumption. The natural value of resources is introduced in the model construction as a pcnalty for the intensive resource oonsumption. The natural value of resources is balanced with thy consumption index in the utifity function. The optimal control probfem is posed to optimiee investment in csipitel, as u basic factor of production, ann investment in technology for raising resource jwoductivity. These two different types of investments generate heterogeneous character of the optimal control wroblem. The optimal steady trajectories satiseying phase constraints of the resource consumption mre constiucted within the Pontryagin maximum prmciple in the modol. lit is shown that under certain conditions for parameters the model admfis frajeetories with growing trends of production approaching steady states A structure of nonlinear stabilizers is proposed for designidu a feedback mechanism leading the economic system along trajectories of sustoinable growth to steady states. Numerical algorithms nre elaborated for constructing balanced investmenf levekin capitel and in fechnology oh resource productivity and reuchmg trajectories of sustainable growth. © 2015, IFAC (international Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Trajectories

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Dynamic self-optimizing control for oil reservoir waterflooding 2

Dynamic self-optimizing control for oil reservoir waterflood...

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2nd IFAC workshop on Automatic Control in Offshore Oil and Gas Production, OOGP 2015

作者： Grema, Alhaji S. Landa, Amaia C. Cao, Yi School of Engineering Cranfield University Cranfield Bedford United Kingdom

Waterflooding is a common oil recovery method where water is injected into the reservoir for increased productivity. Optimal operational strategy of waterflooding processes has to consider proceeds realized from produced oil and cost of productions including both injected and produced water. This is a dynamic optimization problem. The problem could be solved through numerical algorithms based on traditional optimal control theory which can provide only open-loop control solutions and rely on an accurate process model. However, reservoir properties are extremely uncertain and hence open-loop solutions based on a nominal model are not suitable for applications with real reservoirs. Introduction of feedback into the optimization structure to counteract the effect of uncertainties has been proposed recently. In this work, a novel feedback optimization method for optimal waterflooding operation is presented. In the approach appropriate controlled variables as combinations of measurement histories and manipulated variables are first derived through regression based on simulation data obtained from a nominal model. Then a feedback control law was represented as a linear function of measurement histories from the controlled variables obtained. Through a case study, it was shown that the feedback control solution proposed in this work was able to achieve a near-optimal operational profit with only 0.45% worse than that achieved through the true optimal control (with system's properties assumed to be known a priori), but 95.05% better than that obtained with the open-loop solution under uncertainties. © 2015, IFAG (international Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Structural optimization

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On non-differentiable time-varying optimization

On non-differentiable time-varying optimization

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IEEE international workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)

作者： Andrea Simonetto Geert Leus Faculty of EEMCS Delft University of Technology The Netherlands

We consider non-differentiable convex optimization problems that vary continuously in time and we propose algorithms that sample these problems at specific time instances and generate a sequence of converging near-optimal decision variables. This sequence converges up to a bounded error to the solution trajectory of the time-varying non-differentiable problems. We illustrate through analytical examples and a realistic numerical simulation the benefit of the algorithms in signal processing applications, e.g., for reconstructing time-varying sparse signals.

关键词： Convex functions Cost function Convergence Trajectory Signal processing algorithms Conferences

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optimization for performance and energy for batched matrix computations on GPUs 8

Optimization for performance and energy for batched matrix c...

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8th Annual workshop on General Purpose Processing using Graphics Processing Unit, GPGPU 2015

作者： Haidar, Azzam Dong, Tingxing Luszczek, Piotr Tomov, Stanimire Dongarra, Jack University of Tennessee United States Oak Ridge National Laboratory United States University of Manchester United Kingdom

ISBN: (纸本)9781450334075

As modern hardware keeps evolving, an increasingly effective approach to develop energy efficient and high-performance solvers is to design them to work on many small size in-dependent problems. Many applications already need this functionality, especially for GPUs, which are known to be currently about four to five times more energy efficient than multicore CPUs. We describe the development of the main one-sided factorizations that work for a set of small dense matrices in parallel, and we illustrate our techniques on the LU and Cholesky factorizations. We refer to this mode of operation as a batched factorization. Our approach is based on representing the algorithms as a sequence of batched BLAS routines for GPU-only execution. The goal of avoiding multicore CPU use, e.g., as in the hybrid CPU-GPU algorithms, is to exclusively benefit from the GPU's significantly higher energy efficiency, as well as from the removal of the costly CPU-to-GPU communications. Furthermore, we do not use a single symmetric multiprocessor (on the GPU) to factorize a single problem at a time. We illustrate how our performance analysis and the use of profiling and tracing tools guided the development and optimization of batched factorizations to achieve up to 2-fold speedup and 3-fold better energy efficiency compared to our highly optimized batched CPU implementations based on the MKL library (when using two sockets of Intel Sandy Bridge CPUs). Compared to a batched LU factorization featured in the CUBLAS library for GPUs, we achieved up to 2:5 speedup on the K40 GPU. Copyright 2015 ACM.

关键词： Factorization

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Concept of designing the wireless sensor networks based on ant intelligence

Concept of designing the wireless sensor networks based on a...

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IEEE international workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and applications

作者： Vasyl Yatskiv Nataliya Yatskiv Anatoliy Sachenko Orest Volynskyy Ternopil National Economic University Ternopil Ukraine

Implementation of WSN based on the proposed concept will simplify the process of recovery and scaling of network and improve network survivability due to the backup of important segments of distributed processor.

关键词： Wireless sensor networks Particle swarm optimization Wireless communication optimization Redundancy Heuristic algorithms Ant colony optimization

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Model-driven multi-quality auto-Tuning of robotic applications 15

Model-driven multi-quality auto-Tuning of robotic applicatio...

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Joint MORSE/VAO workshop on Model-Driven Robot Software Engineering and View-Based Software-Engineering, MORSE/VAO 2015

作者： Piechnick, Christian Götz, Sebastian Schöne, Rene Abmann, Uwe Technische Universität Dresden Nöthnitzer Str. 46 Dresden01187 Germany

ISBN: (纸本)9781450336147

For the Simultaneous Localization and Mapping (SLAM) problem, many implementations exist, which meet different requirements w.r.t. non-functional properties (e.g., performance). If those requirements change during runtime, the application should change the SLAM implementation. Implementing the selection of the optimal SLAM-algorithms for robots by hand is time consuming and leads to bad code maintainability by mixing application and adaptation logic. Moreover, the realization of the optimization in code requires the developer to re-implement parts of general purpose optimizers, which impairs reusability. An external adaptation logic selecting the optimal SLAM algorithm addresses the maintainability and programmability issues. A model-driven approach for both, application and selection problem, highly increases reusability. To reach these goals, we propose to use Multi-Quality Auto-Tuning (MQuAT), a model-driven approach to build and operate self-optimizing systems following the Models@*** paradigm. We evaluate our approach by a case study, where robots have to choose between several variants of a distributed SLAM algorithm. © 2015 ACM.

关键词： Reusability

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Particle swarm optimization for designing a micro strip patch antenna for Ku band applications

Particle swarm optimization for designing a micro strip patc...

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international Conference and workshop on Computing and Communication (IEMCON)

作者： Manpreet Singh Amandeep Singh Sappal Department of Electronics and Communication Engineering Bhai Gurdas Institue of Engineering & Technology Sangrur India Department of Electronics and Communication Engineering Punjabi University Patiala India

Due to their small size, microstrip patch antennas are widely used in the design of portable wireless communication equipments. Designing a patch antenna with reduced size, for a given band is major area of research these days. optimization algorithms are widely explored by researchers for calculating the parameters of a patch antenna for a given resonance frequency. In this paper, a microstrip patch antenna has been designed for Ku band. The results have been compared with the earlier published work.

关键词： Patch antennas Microstrip antennas Manganese Microstrip Mathematical model Particle swarm optimization

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Online Stochastic Tensor Decomposition for Background Subtraction in Multispectral Video Sequences 15

Online Stochastic Tensor Decomposition for Background Subtra...

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IEEE international Conference on Computer Vision (ICCV)

作者： Sobral, Andrews Javed, Sajid Jung, Soon Ki Bouwmans, Thierry Zahzah, El-hadi Univ La Rochelle Lab L3I MIA La Rochelle France Kyungpook Natl Univ Sch Comp Sci & Engn Daegu South Korea Univ La Rochelle Lab MIA Lab L3I La Rochelle France

ISBN: (纸本)9780769557205

Background subtraction is an important task for visual surveillance systems. However, this task becomes more complex when the data size grows since the real-world scenario requires larger data to be processed in a more efficient way, and in some cases, in a continuous manner. Until now, most of background subtraction algorithms were designed for mono or trichromatic cameras within the visible spectrum or near infrared part. Recent advances in multispectral imaging technologies give the possibility to record multispectral videos for video surveillance applications. Due to the specific nature of these data, many of the bands within multispectral images are often strongly correlated. In addition, processing multispectral images with hundreds of bands can be computationally burdensome. In order to address these major difficulties of multispectral imaging for video surveillance, this paper propose an online stochastic framework for tensor decomposition of multispectral video sequences (OSTD). First, the experimental evaluations on synthetic generated data show the robustness of the OSTD with other state of the art approaches then, we apply the same idea on seven multispectral video bands to show that only RGB features are not sufficient to tackle color saturation, illumination variations and shadows problem, but the addition of six visible spectral bands together with one near infra-red spectra provides a better background/foreground separation.

关键词： Matrix decomposition optimization Robustness Sparse matrices Streaming media Tensile stress Video surveillance

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