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Power-aware I/O-Intensive and CPU-Intensive Applications Hybrid Deployment within Virtualization Environments

Power-aware I/O-Intensive and CPU-Intensive Applications Hyb...

引用

The 2010 ieee international conference on progress in informatics and computing

作者： Zhiwu Liu,Ruhui Ma,Fanfu Zhou,Yindong Yang School of Electronic and Electric Engineering Shanghai Jiao Tong University Shanghai,China 200240 Zhengwei Qi,Haibing Guan School of Electronic and Electric Engineering Shanghai Key Laboratory of Scalable computing and Systems Shanghai Jiao Tong University Shanghai,China 200240

As more and more software applications are migrating from local desktops to remote data centers,efficient data centers management is becoming increasingly *** management of data centers has been facing a key challenge how to trade-off power consumption and Quality of Service (QoS) of *** deal with this challenge,there has been a lot of ongoing efforts on power-aware and QoS-aware application *** on these works,we present I/O-Intensive and CPU-Intensive applications hybrid deployment to optimize resource utilization within virtualization environments. In this work,we investigate the resources allocation between virtual machines where I/O and CPU-Intensive applications reside,to achieve power-aware applications hybrid deployment. To demonstrate the problem of I/O and CPU resource in virtualization environment,we use Xen as the Virtual Machine Monitor to do *** different resource allocation configurations,we evaluate power efficiency up to 2%～12%, compared to the default *** also can conclude the more CPU resource that the CPU-Intensive application in the hybrid deployment applications need to satisfy QoS,the more power efficiency improvement that hybrid deployment can bring.

关键词： Virtualization Green computing Power Efficiency Data Center

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An Improved Precoding of Approximative Matrix Inverse Computations Based on Norm Minimization Algorithm in Massive MIMO System

An Improved Precoding of Approximative Matrix Inverse Comput...

引用

2015 ieee international conference on progress in informatics and computing(PIC 2015)

作者： Hongliu Tu Yanjun Hu Yaohua Xu Fengrong Li Key laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Key Laboratory of Wireless Sensor Network & Communication Shanghai Institute of Microsystem and Information TechnologyChinese Academy of Sciences

In massive multiple-input multiple-output（MIMO） system, scaling up the antennas of base station（BS） has a clear benefit on sum rate and energy efficiency, but the signal processing complexity can be very high and many algorithms cannot be implemented in practice for high hardware cost. Approximati ve Matrix Inverse Computations（AMIC） algorithm is a kind of lowcomplexity precoding for large multiuser MIMO systems, but the Bite Error Rate（BER） performance is shown to be not better than the classical MMSE precoding. To improve the BER performance of AMIC algorithm, in this paper, we use norm minimization algorithm to change the coefficient of the precoding matrix to improve the BER performance of AMIC algorithm. It can verify that the proposed algorithm can achieve better BER performance than the AMIC algorithm by using only a limited number of Neumann series iterations, and keep lower complexity. The proposed scheme is a compromise solution between complexity and BER performance.

关键词： Massive MIMO linear precoding algorithm approximative matrix inverse norm minimization

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Toward an Online Anomaly Intrusion Detection System Based on Deep Learning

Toward an Online Anomaly Intrusion Detection System Based on...

引用

international conference on Machine Learning and Applications (ICMLA)

作者： Khaled Alrawashdeh Carla Purdy Department of Electrical Engineering and Computing Systems University of Cincinnati Cincinnati OH USA

ISBN: (纸本)9781509061686

In the past twenty years, progress in intrusion detection has been steady but slow. The biggest challenge is to detect new attacks in real time. In this work, a deep learning approach for anomaly detection using a Restricted Boltzmann Machine (RBM) and a deep belief network are implemented. Our method uses a one-hidden layer RBM to perform unsupervised feature reduction. The resultant weights from this RBM are passed to another RBM producing a deep belief network. The pre-trained weights are passed into a fine tuning layer consisting of a Logistic Regression (LR) classifier with multi-class soft-max. We have implemented the deep learning architecture in C++ in Microsoft Visual Studio 2013 and we use the DARPA KDDCUP'99 dataset to evaluate its performance. Our architecture outperforms previous deep learning methods implemented by Li and Salama in both detection speed and accuracy. We achieve a detection rate of 97.9% on the total 10% KDDCUP'99 test dataset. By improving the training process of the simulation, we are also able to produce a low false negative rate of 2.47%. Although the deficiencies in the KDDCUP'99 dataset are well understood, it still presents machine learning approaches for predicting attacks with a reasonable challenge. Our future work will include applying our machine learning strategy to larger and more challenging datasets, which include larger classes of attacks.

关键词： Machine learning Intrusion detection Training Feature extraction Testing Logistics Data mining

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Study on Classification of Domain-Oriented User Exploration Process for Exploratory Search

Study on Classification of Domain-Oriented User Exploration ...

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2015 ieee international conference on progress in informatics and computing(PIC 2015)

作者： Pengfei Li Yin Zhang Kening Gao Bin Zhang College of Information Science and Engineering/Key Laboratory of Medical Image Computing Northeastern University/Ministry of Education

In the study of exploratory search, different supporting methods have already been proposed to meet users’ different information needs. However, these methods are mostly targeted at different domains of user exploration process. In this paper, we study on a classification method of domain-oriented user exploration process for exploratory search to support determine user’s search domains for search engines who will well-directed help users to complete exploratory tasks. First, we seek to define and built exploration process model base on tree structure. Second, we study on domain-oriented classification method based on user exploration process model and design a parameter training method based on List Net. In the experimental stage, we compare the abilities between our method and two ‘baseline’ methods. Results show that the precision, recall and F1-measure of our method is found to increase by 7 percent to 15 percent over these previous methods.

关键词： Exploratory search user exploration process tree structure model List Net

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An Effective Heuristic for Due-Date-Constrained Bag-of-Tasks Scheduling Problem for Total Cost Minimization on Hybrid Clouds

An Effective Heuristic for Due-Date-Constrained Bag-of-Tasks...

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2016 ieee international conference on progress in informatics and computing

作者： Yi Zhang Jin Sun Jie Zhu School of Computer Science & Engineering Nanjing University of Science & Technology School of Computer Science & Technology Nanjing University of Posts & Telecommunications

Bag-of-Tasks(BoT) applications consisting of multiple tasks widely exist in numerous fields. As customers use cloud resources in a pay-as-you-go way, they are willing to execute BoT applications on clouds. Cloud providers and customers establish contracts in which applications' due dates are specified. If an application cannot be finished before the due date, the cloud provider should pay a tardiness penalty. When the private cloud has insufficient available resources to afford all customer-submitted BoT applications, the cloud provider has to outsource some tasks to public clouds with resource-used costs. The key challenge here is how to schedule tasks on hybrid clouds to minimize the total cost, including all applications' tardiness penalties and the cost of using public clouds' resources. We study and formulate this problem as an Integer Programming. Accordingly, we propose an effective greedy heuristic(GH) including two phases(task ordering and task scheduling). GH uses an Earlier Latest Start Time First method(ELSTF) for task ordering with the result that a task sequence is obtained.A Task Dispatching method(TD) is established for the task scheduling, in which each task in the obtained task sequence is scheduled one by one. Experimental results demonstrate that the proposed GH outperforms the baseline(RoundR obin) remarkably. ELSTF and TD are also verified to be effective.

关键词： Bag-of-Tasks Scheduling Hybrid Clouds Due Date Total Cost Minimization

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Automatic Analysis of Tongue Substance Color and Coating Color Using Sparse Representation-Based Classifier

Automatic Analysis of Tongue Substance Color and Coating Col...

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2016 ieee international conference on progress in informatics and computing

作者： Panling Qu Hui Zhang Li Zhuo Pei Zhang Jing Zhang Signal and Information Processing Laboratory Beijing University of Technology

Sparse Representation-based Classifier(SRC) is less sensitive to the shortage of data and the selection of feature space. In this paper, SRC is adopted to perform automatic analysis of tongue substance color and coating color which is considered as small dataset classification task. Firstly, for both training samples and testing samples, the tongue body regions are segmented, the regions of tongue substance and coating are separated and the features of these regions are extracted. Then, the feature vectors of testing samples are represented by sparse coding. Finally, the feature vectors of testing samples are reconstructed for each category, the residuals are calculated and the category of the smallest residual is determined as the classification result. Experimental results show that the proposed method can achieve the classification accuracy of 87.80% and 90.51% for the colors of tongue substance and tongue coating respectively. In addition, the classification accuracy of tongue coating color can reach to 91.19% with the assistance of visual samples by SRC. The proposed method provides a new method for automatic analysis of tongue color, and it is also a new application of SRC.

关键词： Traditional Chinese Medical tongue diagnosis substance color coating color sparse representation-based classifier small dataset visual samples

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Fine-grained Vehicle Recognition Using Hierarchical Fine-Tuning Strategy for Urban Surveillance Videos

Fine-grained Vehicle Recognition Using Hierarchical Fine-Tun...

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2016 ieee international conference on progress in informatics and computing

作者： Qiang Zhang Li Zhuo Xiaochen Hu Jing Zhang Signal & Information Processing Laboratory Beijing University of Technology Collaborative Innovation Center of Electric Vehicles in Beijing

The Fine-grained Vehicle recognition is easily affected by small visual changes. The existing recognition methods have less robustness to these conditions(such as illumination, weather changes, etc.) and the accuracy of vehicle recognition in complex environments cannot achieve a satisfying result. In this paper, a high-accuracy fine-grained vehicle recognition method using Convolutional Neural Network for urban surveillance videos is proposed. Differing from the conventional CNN based methods, which usually obtain a single classification model, the proposed method combines Pre-training and hierarchical fine-tuning to obtain different classification model that can adapt to the change of illumination conditions. In the recognition phase, the input image is evaluated firstly using the proposed image quality assessment method. Then, the classification model is selected adaptively according to the results of quality evaluation and used for recognition. To test our method, we use a publicly vehicle recognition dataset for Urban Surveillance Videos provide by Yang. Experimental results show that the accuracy of the proposed method is up to 98.89%, which is 0.5% higher than Yang's method.

关键词： fine-grained vehicle recognition hierarchical fine-tuning quality assessment

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An Explanatory Analysis of Electricity Prices within Day-Ahead Spanish Energy Market by Using a Graphical Automatization with R

An Explanatory Analysis of Electricity Prices within Day-Ahe...

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2014 ieee international conference on progress in informatics and computing

作者： Jose Manuel Velasco Beatriz Gonzlez-Prez Guadalupe Miana Victoria Lopez Raquel Caro Faculty of Computer Science Complutense University of MadridSpain Higher Technical School of Engineering Pontificia Comillas UniverstySpain

Since 1998, the Spanish and Portuguese Administrations began toshare a common path in building the Iberian Electricity Market(MIBEL). This cooperation has been very successful, not only for its contribution tothe existence of an electricity market on an Iberian level, but alsoon a European scale, as a significant step in building the Internal Energy *** price of electricity in the MIBEL is very changeable. This creates a lot of uncertainty and risk in market actors. Due tocontinuous changes in demand and marginal price adjustment,buyers and sellers can not know in advance the evolution of prices. Our interestis tostudy of this uncertainty since the perspective of the buyer and not the seller's perspective. The aim of this work is todevelop a graphical analysis of the variables involved in the Spanish Energy Marketin order toexplain the electric price and provide tosmall traders, that could be interested in participating in that market, better knowledge of the schedule. On the other hand, large industrial consumers use this information todesign strategies tooptimize its production capacity and improve their production costs. In this article the variable of interestis the marginal price instead of *** paper provides a graphical analysis by means of an easily reproducible automatization with the R project for statistical computing that allows toexplore, visualize and understand the key variables that define its final value. Mibel 2011 and 2012 data are used for ilustrations. The results show the importance of the calendar effect, seasonality and trend as principal factors totake intoaccount for posterior fases:modeling and forecasting.

关键词： electricity market exploratory analysis R language

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Multivariable GPC for processes with multiple time delays: Implementation issues

Multivariable GPC for processes with multiple time delays: I...

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international conference on Emerging Technologies and Factory Automation (ETFA)

作者： A. Pawlowski J. L. Guzmán M. Berenguel J. E. Normey-Rico S. Dormido Department of Computer Science and Automatic Control UNED Madrid Spain Department of Informatics University of Almeria Almeria Spain Universidad de Almeria Almeria AndalucÃa ES Universidade Federal de Santa Catarina Florianopolis SC BR

ISBN: (纸本)9781509013159

In this work, implementation issues related to multivariable Generalized Predictive Control (GPC) for processes with multiple time delays are analyzed. Due to specific properties of those processes, the resulting control system has to account for the existing delays between control variables changes and their effect on controlled outputs. In the case of Model Predictive Control (MPC) techniques, such as GPC, the dead-time issue can be captured in the process model and thus considered in the predictive mechanism of the controller. However, this working principle results in augmented matrix dimensions that considers input-output time delays as additional zero entries. This fact increases the computational load and has to be accounted for in the control system design, specially in systems where computing resources are scarce (eg. embedded systems). The reduction of the matrix dimension, and hence the computation required, depends on how the delay terms are structured. The presented analysis considers two different GPC implementations for multivariable dead-time processes, which are used to compensate for internal matrix dimensions for the multiple time delays. Each implementation mode is evaluated for two industrial multivariable processes, providing several performance indexes. Performed simulations show that the required computational load can be reduced when adequate implementation mode is selected.

关键词： Delay effects Delays MIMO Process control Control systems Computational modeling Predictive models

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3D Model Retrieval from Multiple Photographic Images

3D Model Retrieval from Multiple Photographic Images

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The 2010 ieee international conference on progress in informatics and computing

作者： Qianwei Bian Department of Computer Science & Engineering Shanghai Jiao Tong University Shanghai,China Yuanjun He Department of Computer Science & Engineering Shanghai Jiao Tong University Shanghai,China Weimin Luo Department of computing The Hong Kong Polytechnic University Hong Kong,China Hongming Cai School of Software Shanghai Jiao Tong University Shanghai,China

Due to the recent significant improvements in game entertainment,CAD,CAE and some other 3D fields,the number of 3D models is increasing *** a result,there is an increasing need for procedures supporting the automatic search for 3D objects in *** this paper,we present a novel framework to retrieve 3D models in 3 ***,users input multiple ordered images of an object as *** photo environment is needed.A voxel model will be generated automatically according to these ***,we provide a tool to modify voxel *** procedure can help eliminate defects caused by uncertain photo *** the model produced by the first step is reasonable,this step will be optional. Finally,the modified model will be retrieved by a method called Solid-D2,which provides a fast and discriminating descriptor for 3D *** algorithm is chosen to err on the side of retrieval speed with certain *** models from the database will be *** results indicate that the proposed method is easy-to-use,efficient and applicable for 3D model retrieval.

关键词： 3D model retrieval image based modeling VD2 voxel model

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