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General Meeting of the IEEE-Power-and-Energy-Society (PES)

作者： Liu, W-H Edwin McArthur, Stephen Giri, Jay Miu, Karen Pratt, Rob Wen, Jun Uluski, Bob Dow, Luther Labut, Gerard IEEE Computing and Analytical Methods Subcommittee United States IEEE PES Intelligent Systems Subcommittee United States IEEE PES Multi-Agent System Working Group United States Power Systems Technology and Strategic Initiatives ALSTOM Grid Redmond WA United States Electrical and Computer Engineering Department Drexel University United States Pacific Northwest National Laboratory's (PNNL's) Smart Grid R and D Program U.S. Department of Energy United States Transmission and Interconnection Planning Group Southern California Edison (SCE) Company United States WECC Modeling and Validation Working Group United States EPRI Power Delivery and Utilization Area United States Distribution and West Coast Operations Quanta Technology United States Distribution Operations SmartCurrentssm Program Strategy DTE Energy Detroit MI United States

ISBN: (纸本)9781457710018

The effort of "Smart Grid" is to modernize grid infrastructure and build-in intelligence to power grids and delivery systems, and their interfaces to customer premises. However, the perspectives range from an emphasis on infrastructure to an emphasis on new paradigm-shifting applications. Alternatively, the smart grid can be thought of as the advanced information technologies that enable the desired analytical applications. As a general understanding, we believe that Smart Grid needs to integrate power system analysis, computing and economics to enhance grid reliability, efficiency, and security, and contributes to the climate change strategic goal. In this Supersession, the analytics that empowers smart grid applications is discussed;and the practical implementation and integration challenges will be presented.

关键词： smart grid analytical applications system integration

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Looking around with your brain in a virtual world

Looking around with your brain in a virtual world

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IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB)

作者： Danny Plass-Oude Bos Matthieu Duvinage Oytun Oktay Jaime Delgado Saa Huseyin Guruler Ayhan Istanbullu Marijn van Vliet Bram van de Laar Mannes Poel Linsey Roijendijk Luca Tonin Ali Bahramisharif Boris Reuderink HMI group Faculty of EEMCS University of Twente Netherlands TCTS Laboratory Electrical Engineering University of Mons Belgium Electronics and Communications Corlu Engineering Namik Kemal Üniversitesi Turkey IEE Group of Robotics and Intelligent Systems Universidad del Norte Colombia Faculty of Engineering and Natural Sciences VPA Laboratory Sabanci University Turkey Department of Electronics and Computer Education Faculty of Technical Education Mugla University Turkey Faculty of Computer Engineering Balikesir University Turkey Donders Institute for Brain Cognition and Behaviour Radboud University Nijmegen Nijmegen Netherlands CNBI École Polytechnique Fédérale de Lausanne Switzerland Institute for Computing and Information Sciences Radboud University Nijmegen Nijmegen Netherlands

Offline analysis pipelines have been developed and evaluated for the detection of covert attention from electroen-cephalography recordings, and the detection of overt attention in terms of eye movement based on electrooculographic measurements. Some additional analysis were done in order to prepare the pipelines for use in a real-time system. This real-time system and a game application in which these pipelines are to be used were implemented. The game is set in a virtual environment where player is a wildlife photographer on an uninhabited island. Overt attention is used to adjust the angle of the first person camera, when the player is tracking animals. When making a photograph, the animal will flee when it notices it is looked at directly, so covert attention is required to get a good shot. Future work will entail user tests with this system to evaluate usability, user experience, and characteristics of the signals related to overt and covert attention when used in such an immersive environment.

关键词： Pipelines Accuracy Electrooculography Electrodes Training Electroencephalography Games

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Multi-objective virtual machine placement in virtualized data center environments

Multi-objective virtual machine placement in virtualized dat...

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2010 IEEE/ACM International Conference on Green computing and Communications, GreenCom 2010, 2010 IEEE/ACM International Conference on Cyber, Physical and Social computing, CPSCom 2010

作者： Xu, Jing Fortes, José A. B. Advanced Computing and Information Systems Laboratory Department of Electrical and Computer Engineering University of Florida PO Box 116200 Gainesville FL 32611-6200 United States

ISBN: (纸本)9780769543314

Server consolidation using virtualization technology has become increasingly important for improving data center efficiency. It enables one physical server to host multiple independent virtual machines (VMs), and the transparent movement of workloads from one server to another. Fine-grained virtual machine resource allocation and reallocation are possible in order to meet the performance targets of applications running on virtual machines. On the other hand, these capabilities create demands on system management, especially for large-scale data centers. In this paper, a two-level control system is proposed to manage the mappings of workloads to VMs and VMs to physical resources. The focus is on the VM placement problem which is posed as a multi-objective optimization problem of simultaneously minimizing total resource wastage, power consumption and thermal dissipation costs. An improved genetic algorithm with fuzzy multi-objective evaluation is proposed for efficiently searching the large solution space and conveniently combining possibly conflicting objectives. A simulation-based evaluation using power-consumption and thermal-dissipation models (learned from profiling of a BladeCenter), demonstrates the good performance, scalability and robustness of our proposed approach when compared with four well-known bin-packing algorithms and two single-objective approaches. Our approach can seek and find solutions that exhibit good balance among the conflicting objectives while others cannot. © 2010 IEEE.

关键词： Virtual machine

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Implementing global automata in PLCs based on the IEC 61131-3 programming norm

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International Journal of Industrial and systems engineering 2010年第2期6卷 163-186页

作者： Deligiannis, Vasileios Manesis, Stamatis Department of Electrical and Computer Engineering Laboratory of Systems and Measurement University of Patras Rion-Patras 26500 Greece

Global Automata are a recently proposed approach on modelling contemporary industrial systems. They are based on automata philosophy and are specially orientated for industrial use. In industry the dominant controller is the Programmable Logic Controller (PLC), which is a special aim computer suitably built for the application control tasks. The IEC 61131-3 Programming Norm describes all the well-known languages for programming PLCs and this paper presents a synthesis tool for implementing global automata in PLCs based on this programming norm. Differences on language semantics between several manufacturers are frequent since the international standard is an open frame. Due to this fact the presented synthesis tool gives an industrial engineer the general guidance to write the respective code from a global automaton. Copyright © 2010 Inderscience Enterprises Ltd.

关键词： Programmable logic controllers

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Integration of global and local information in videos for key frame extraction 11

Integration of global and local information in videos for ke...

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11th IEEE International Conference on Information Reuse and Integration, IRI 2010

作者： Liu, Dianting Shyu, Mei-Ling Chen, Chao Chen, Shu-Ching Department of Electrical and Computer Engineering University of Miami Coral Gables FL 33124 United States Distributed Multimedia Information Systems Laboratory School of Computing and Information Sciences Florida International University Miami FL 33199 United States

ISBN: (纸本)9781424480975

Key frame extraction methods aim to obtain a set of frames that can efficiently represent and summarize video contents and be reused in many video retrieval-related applications. An effective set of key frames, viewed as a high-quality summary of the video, should include the major objects and events of the video, and contain little redundancy and overlapped content. In this paper, a new key frame extraction method is presented, which not only is based on the traditional idea of clustering in the feature extraction phase but also effectively reduces redundant frames using the integration of local and global information in videos. Experimental results on the TRECVid 2007 test video dataset have demonstrated the effectiveness of our proposed key frame extraction method in terms of the compression rate and retrieval precision. © 2010 IEEE.

关键词： Integration

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On the Use of Machine Learning to Predict the Time and Resources Consumed by Applications 10

On the Use of Machine Learning to Predict the Time and Resou...

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IEEE/ACM International Symposium on Cluster computing and the Grid (CCGRID)

作者： Andréa Matsunaga José A.B. Fortes Advanced Computing and Information Systems Laboratory Department of Electrical and Computer Engineering University of Florida Gainesville FL USA

ISBN: (纸本)9780769540399

Most data centers, clouds and grids consist of multiple generations of computing systems, each with different performance profiles, posing a challenge to job schedulers in achieving the best usage of the infrastructure. A useful piece of information for scheduling jobs, typically not available, is the extent to which applications will use available resources once they are executed. This paper comparatively assesses the suitability of several machine learning techniques for predicting spatio temporal utilization of resources by applications. Modern machine learning techniques able to handle large number of attributes are used, taking into account application- and system-specific attributes (e.g., CPU micro architecture, size and speed of memory and storage, input data characteristics and input parameters). The work also extends an existing classification tree algorithm, called Predicting Query Runtime (PQR), to the regression problem by allowing the leaves of the tree to select the best regression method for each collection of data on leaves. The new method (PQR2) yields the best average percentage error, predicting execution time, memory and disk consumption for two bioinformatics applications, BLAST and RAxML, deployed on scenarios that differ in system and usage. In specific scenarios where usage is a non-linear function of system and application attributes, certain configurations of two other machine learning algorithms, Support Vector Machine and k-nearest neighbors, also yield competitive results. In addition, experiments show that the inclusion of system performance and application-specific attributes also improves the performance of machine learning algorithms investigated.

关键词： Machine learning Machine learning algorithms Processor scheduling Regression tree analysis Mesh generation Cloud computing Grid computing Classification tree analysis Classification algorithms Prediction algorithms

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Multi-Objective Virtual Machine Placement in Virtualized Data Center Environments

Multi-Objective Virtual Machine Placement in Virtualized Dat...

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IEEE/ACM Int'l Conference on & Int'l Conference on Cyber, Physical and Social computing (CPSCom) Green computing and Communications (GreenCom)

作者： Jing Xu Jose A. B. Fortes Advanced Computing and Information Systems Laboratory Department of Electrical and Computer Engineering University of Florida Gainesville FL USA

Server consolidation using virtualization technology has become increasingly important for improving data center efficiency. It enables one physical server to host multiple independent virtual machines (VMs), and the transparent movement of workloads from one server to another. Fine-grained virtual machine resource allocation and reallocation are possible in order to meet the performance targets of applications running on virtual machines. On the other hand, these capabilities create demands on system management, especially for large-scale data centers. In this paper, a two-level control system is proposed to manage the mappings of workloads to VMs and VMs to physical resources. The focus is on the VM placement problem which is posed as a multi-objective optimization problem of simultaneously minimizing total resource wastage, power consumption and thermal dissipation costs. An improved genetic algorithm with fuzzy multi-objective evaluation is proposed for efficiently searching the large solution space and conveniently combining possibly conflicting objectives. The simulation-based evaluation using power-consumption and thermal-dissipation models based on profiling of a Blade Center, demonstrates the good performance, scalability and robustness of our proposed approach. Compared with four well-known bin-packing algorithms and two single-objective approaches, the solutions obtained from our approach seek good balance among the conflicting objectives while others cannot.

关键词： Servers Optimization Power demand Virtual machining Resource management Memory management Thermal management

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Studying the impact of synchronization frequency on scheduling tasks with dependencies in heterogeneous systems

Studying the impact of synchronization frequency on scheduli...

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作者： Andronikos, Theodore Ciorba, Florina M. Riakiotakis, Ioannis Papakonstantinou, George Chronopoulos, Anthony T. Department of Informatics Ionian University Corfu Greece Computing Systems Laboratory Department of Electrical and Computer Engineering National Technical University of Athens Greece Center for Advanced Vehicular Systems Mississippi State University MS United States Department of Computer Science University of Texas at San Antonio 6900 N. Loop 1604 West San Antonio TX 78249 United States

In this work, we develop and evaluate a theoretical model, which we then use to study the impact of the synchronization frequency on the performance of dynamic self-scheduling algorithms. These algorithms are used to parallelize loops with data dependencies on heterogeneous systems. The proposed model uses a formula to estimate the parallel time as a function of the synchronization frequency. Inter-node communication has been proven to be the dominant factor for the performance degradation of applications containing loops with data dependencies. The synchronization mechanism therefore requires careful fine-tuning in order to give the best possible performance. The proposed model determines the optimal synchronization frequency that results in the minimum parallel time. We use this model to study the impact of the synchronization frequency on the parallel execution of a computational kernel from image processing. For this kernel, the synchronization frequency giving the minimum parallel time predicted by our theoretical model was very close to the synchronization frequency giving the least parallel time in practice. We validate our model by extensive comparisons of the theoretically predicted parallel time and synchronization frequency against those obtained from practical experiments. The comparisons show that the proposed model is highly accurate, its predictions for the optimal synchronization frequency being within 0.0250% of the experimentally optimal synchronization frequency in the best case, and within 0.1750% of the experimentally optimal synchronization frequency in the worst case. Finally, the comparisons show that the proposed model improves on a previously existing model in heterogeneous systems, whereas it gives similar results in homogeneous systems. © 2010 Elsevier B.V. All rights reserved.

关键词： Synchronization

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Fuzzy-Bayesian network approach to genre-based recommender systems

Fuzzy-Bayesian network approach to genre-based recommender s...

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IEEE International Conference on Fuzzy systems (FUZZ-IEEE)

作者： Soheila Ashkezari-T Mohammad-R. Akbarzadeh-T Department of Computer Engineering Cognitive Computing Laboratory Center of Applied Research on Soft computing and Intelligent systems Ferdowsi University of Mashhad Mashhad Iran Departments of Electrical Engineering and Computer Engineering Cognitive Computing Laboratory Center of Applied Research on Soft computing and Intelligent systems Ferdowsi University of Mashhad Iran

The World Wide Web has created a new media for mass marketing that can also be highly customized to online customers' needs and expectations. Recommender systems (RS) play an important role in this area. Here, we aim to establish a genre-based collaborative RS to automatically suggest and rank a list of appropriate items (movies) to a user based on the user profile and the past voting patterns of other users with similar tastes. The contribution of this paper is using genre based information in a hybrid fuzzy-Bayesian network collaborative RS. The interest to the different genres is computed based on a hybrid user model. The similarity of like-minded users according to the fuzzy distance and also Pearson correlation coefficient is involved in a Bayesian network.

关键词： Motion pictures Mathematical model Collaboration Recommender systems Equations Computational modeling

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A Smart-NIC-Based Power-Proxy Solution for Reduced Power Consumption during Instant Messaging

A Smart-NIC-Based Power-Proxy Solution for Reduced Power Con...

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IEEE Green Technologies Conference (IEEE-Green)

作者： Dexiang Wang Janise McNair Alan George Wireless and Mobile Systems Laboratory Department of Electrical and Computer Engineering University of Florida Gainesville USA NSF Center for High-Performance Reconfigurable Computing (CHREC) Department of Electrical and Computer Engineering University of Florida Gainesville USA

ISBN: (纸本)9781424452743

The major challenge to achieving efficient power management for local computers that serve as edge devices of the Internet is to achieve long sleeping times while at the same time maintaining network connectivity. By modifying the network interface card (NIC) with a low-weight proxy module that can handle a certain amount of network protocol semantics and hence still keep the local computer alive on the Internet, a longer host sleeping time can be achieved, while keeping many of the components, including CPU, memory, motherboard, hard drive, etc, remain in a very-low-energy mode. In this paper, we pursue a power-proxy solution to the widely-used Instant Messenger (IM) applications. Yahoo! ® Messenger is selected for a case study to investigate its communication protocol YMSG. Furthermore, the decision on inactivity time-out values is a crucial factor for energy savings, but the random nature of idle periods makes the decision another challenge. We formulate the decision problem into a stochastic program and propose an adaptive algorithm to set up appropriate inactivity time-out values. Simulations show that the proposed power-proxy solution combined with the inactivity time-out setup algorithm can efficiently reduce the power consumption of an edge computer.

关键词： Energy consumption computer networks IP networks Protocols computer network management Energy management Network interfaces computer interfaces Central Processing Unit Drives

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