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IEEE International Conference on Communications Workshops

作者： Shaohe Lv Weihua Zhuang Xiaodong Wang Xingming Zhou National Laboratory of Parallel and Distributed Processing National University of Defense Technology Department of Electrical and Computer Engineering University of Waterloo

ISBN: (纸本)9781612842325

We consider the greedy scheduling based on the physical model in wireless networks with successive interference cancellation (SIC). There are two major stages in a scheduling scheme, link selection (to decide which link is scheduled next) and time slot selection (to deciding which slot is allocated to a given link). Most available schemes take a first-fit policy in the latter and strive to achieve good performance by careful selection of link ordering with respect to interference. Due to the accumulation effect and sequential detection nature of SIC, however, it is difficult to evaluate the interference of a link. As a result, many existing scheduling schemes become less efficient. In this paper, we take a new look on the problem and focus to the time slot selection stage. We define tolerance margin to measure the saturation of a link set and present two heuristic policies: one is to schedule a link to a slot such that the resulting set of links has a maximum tolerance margin;the other is to choose a slot such that the increase of tolerance margin is minimum. Simulation results show that the performance of the proposed schemes is better than the first-fit policy and is close to the optimal solution.

关键词： Link scheduling Successive interference cancellation Physical interference model

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Reducing cache contention in a multi-core processor via a scheduler

Reducing cache contention in a multi-core processor via a sc...

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International Conference on Advanced computer Theory and engineering, ICACTE

作者： S.Kazem Shekofteh Hossein Deldari Maryam Baradaran Khalkhali Parallel and Distributed Processing Laboratory Department of Computer Engineering Ferdowsi University of Mashhad Mashhad Iran Department of Computer Engineering Mashhad Branch Islamic Azad University Mashhad Iran

Multi-core architectures, which have multiple processing units on a single chip, are widely viewed as a way to achieve higher processor performance. Well scheduling of running threads on these processors will result in achieving higher performance. Modern multi-core systems are designed to allow clusters of cores to share various hardware structures, such as last-level caches, memory controllers, and interconnections, as well as prefetching hardware. Without considering these shared resources, scheduling the threads will cause serious degradation in overall performance of the system. In this paper we propose a novel algorithm to schedule the threads that considers these potential contentions to keep away from. The simulation results showed that the proposed scheduler would avoid from lots of contentions between threads on various resources especially on shared caches.

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Virtual Frame Aggregation: Clustered Channel Access in Wireless Networks

Virtual Frame Aggregation: Clustered Channel Access in Wirel...

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IEEE International Conference on Communications

作者： Xuan Dong Shaohe Lv Chunsheng Zhu Rukhsana Ruby Xiaodong Wang Xingming Zhou Victor C. M. Leung National Laboratory of Parallel and Distributed Processing National University of Defense Technology Department of Electrical and Computer Engineering The University of British Columbia

ISBN: (纸本)9781467364300

Coordination among users is inevitable in wireless communication for efficient medium access. Even though the data rate of individual user increases significantly, the performance of wireless network does not grow up accordingly due to the high MAC coordination overhead. In this paper, we present VFA, namely virtual frame aggregation, to achieve high coordination efficiency by amortizing the overhead over multiple transmissions. VFA provides a novel way to construct a winner cluster and allow the winners to transmit without interruption. Specifically, in a multicarrier network, every contending node chooses a subcarrier and the nodes are ordered by the index of the chosen subcarrier. When there are some subcarriers chosen by two or more nodes, an additional slot is exploited to reorder the collided nodes. Finally, all ordered nodes form a cluster and the transmissions are issued sequentially and uninterruptedly. Simulation results show that usually two slots are enough to construct a sufficiently large winner cluster. Moreover, VFA achieves a notable throughput gain over IEEE 802.11 as high as 120% with better fairness under various scenarios.

关键词： Wireless communication Antennas Wires

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A Wallet-Size Cluster for H.264 Encoding

A Wallet-Size Cluster for H.264 Encoding

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International Conference on Information Technology and Applications, ICITA

作者： Liang-Teh Lee Chia-Ying Tseng Kang-Yuan Liu Kuan-Ching Li Department of Computer Science and Engineering Tatung University Taipei Taiwan Parallel and Distributed Processing Center Department of Computer Science and Information Management Providence University Taichung Taiwan

ISBN: (纸本)0769523161

A scalable wallet-size cluster computing system has been proposed to obtain low cost, low power consumption and small sized digital home processing center. In this paper, we apply the wallet-size cluster for H.264 encoding to accelerate the H.264 video processing. We analyze the encoder scheme of the H.264, and perform the H.264 encoding in parallel through the nodes of the cluster. The experimental results show that an efficient real time video processing for H.264 can be achieved

关键词： Encoding Video coding Videoconference Costs Energy consumption Acceleration Bit rate IEC standards ISO standards Streaming media

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Versatile Stack Management for Multitasking Sensor Networks

Versatile Stack Management for Multitasking Sensor Networks

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IEEE International Conference on Distributed Computing Systems

作者： Rui Chu Lin Gu Yunhao Liu Mo Li Xicheng Lu National Laboratory for Parallel and Distributed Processing National University of Defense Technology Department of Computer Science and Engineering Hong Kong University of Science and Technology

ISBN: (纸本)9781424472611;9780769540597

The networked application environment has motivated the development of multitasking operating systems for sensor networks and other low-power electronic devices, but their multitasking capability is severely limited because traditional stack management techniques perform poorly on small-memory systems. In this paper, we show that combining binary translation and a new kernel runtime can lead to efficient OS designs on resource-constrained platforms. We introduce SenSmart, a multitasking OS for sensor networks, and present new OS design techniques for supporting preemptive multi-task scheduling, memory isolation, and versatile stack management. We have implemented SenSmart on MICA2/MICAz motes. Evaluation shows that SenSmart performs efficient binary translation and demonstrates a significantly better capability in managing concurrent tasks than other sensornet operating systems.

关键词： parallel processing (computerS) Sensor networks Electron devices Furnace conveyors Cache Memory System Operating systems osmium

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POLUS: A POwerful Live Updating System

POLUS: A POwerful Live Updating System

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International Conference on Software engineering (ICSE)

作者： Haibo Chen Jie Yu Rong Chen Binyu Zang Pen-Chung Yew Parallel Processing Institute Fudan University Shanghai China Department of Computer Science and Engineering University of Minnesota Twin-Cities Minneapolis MN USA

This paper presents POLUS, a software maintenance tool capable of iteratively evolving running software into newer versions. POLUS's primary goal is to increase the dependability of contemporary server software, which is frequently disrupted either by external attacks or by scheduled upgrades. To render POLUS both practical and powerful, we design and implement POLUS aiming to retain backward binary compatibility, support for multithreaded software and recover already tainted state of running software, yet with good usability and very low runtime overhead. To demonstrate the applicability of POLUS, we report our experience in using POLUS to dynamically update three prevalent server applications: vsftpd, sshd and apache HTTP server. Performance measurements show that POLUS incurs negligible runtime overhead: a less than 1% performance degradation (but 5% for one case). The time to apply an update is also minimal.

关键词： Application software Software maintenance Web server Software tools Usability Runtime Measurement Degradation computer bugs Software engineering

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Application of QR decomposition-based least squares technique to improve air traffic control radar

Application of QR decomposition-based least squares techniqu...

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Midwest Symposium on Circuits and Systems (MWSCAS)

作者： T. Ogunfunmi Nam Ling Signal and Image Processing Laboratory (SIPL) Department of Electrical Engineering Santa Clara University Santa Clara CA USA Computer Systems and Parallel Processing Research Laboratory (CSPPRL) Department of Computer Engineering Santa Clara University Santa Clara CA USA

For real-time radar processing, it is very desirable to have an algorithm that does not assume restricted statistics of the input data and can be implemented for high-speed processing (without a high cost) to meet real-time requirements. We therefore apply the QR decomposition-based least-squares method for linear prediction to the problem of computing the reflection coefficients of a lattice predictor, instead of using the conventional Burg algorithm. We also propose a modified one-dimensional ring architecture for implementing the QR method of least-squares. The particular application considered in this case is that of surveillance radar systems for air traffic control.< >

关键词： Least squares methods Air traffic control Radar applications Signal processing algorithms Radar signal processing Statistics Systolic arrays Radar imaging Signal processing Surveillance

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The prediction model based on RBF network in achieving elastic cloud

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Advances in Information Sciences and Service Sciences 2011年第11期3卷 67-78页

作者： Shi, Peichang Wang, Huaimin Ding, Bo Liu, Ran Wang, Tianzuo National Laboratory for Parallel and Distributed Processing School of Computer and Science National University of Defense Technology China Department of Electronics and Information Engineering Huazhong University of Science Technology China

Cloud needs to have rapid and elastic resources supply capability, because of the fluctuant resources demand of end-users. Multi-scale resources elastic binding is an important method to provide cloud services with rapid and elastic service capability. The most challenging problem in multi-scale resources elastic binding is how to predict the dynamic resource demand of end-users, and then decide when and to what extent multi-scale resources need elastic binding based on the prediction. In this paper, we present the prediction model based on RBF (Radial Basis Function) Network, which is used to predict end-users resource demand in advance. Compared with current prediction methods, it has faster prediction speed and higher prediction accuracy. Then we use traces data (the bandwidth demand of Web type of cloud services) collected from a real-world cloud provider: ChinaCache, as the training and testing data set to validate the method. Finally, we evaluate the predicted results using general prediction accuracy metrics. The results prove that the prediction model based on RBF network is able to resolve the decision problem in multi-scale resources elastic binding.

关键词： Radial basis function networks

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Two-dimensional euler PCA for face recognition 21

Two-dimensional euler PCA for face recognition

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21st International Conference on MultiMedia Modeling, MMM 2015

作者： Tan, Huibin Zhang, Xiang Guan, Naiyang Tao, Dacheng Huang, Xuhui Luo, Zhigang Science and Technology on Parallel Distributed Processing Laboratory College of Computer National University of Defense Technology Changsha Hunan410073 China Department of Computer Science and Technology College of Computer National University of Defense Technology Changsha Hunan410073 China Centre for Quantum Computation and Intelligent Systems and the Faculty of Engineering and Information Technology University of Technology Sydney 235 Jones Street UltimoNSW2007 Australia

ISBN: (纸本)9783319144412

Principal component analysis (PCA) projects data on the directions with maximal variances. Since PCA is quite effective in dimension reduction, it has been widely used in computer vision. However, conventional PCA suffers from following deficiencies: 1) it spends much computational costs to handle high-dimensional data, and 2) it cannot reveal the nonlinear relationship among different features of data. To overcome these deficiencies, this paper proposes an efficient two-dimensional Euler PCA (2D-ePCA) algorithm. Particularly, 2D-ePCA learns projection matrix on the 2D pixel matrix of each image without reshaping it into 1D long vector, and uncovers nonlinear relationships among features by mapping data onto complex representation. Since such 2D complex representation induces much smaller kernel matrix and principal subspaces, 2D-ePCA costs much less computational overheads than Euler PCA on large-scale dataset. Experimental results on popular face datasets show that 2D-ePCA outperforms the representative algorithms in terms of accuracy, computational overhead, and robustness. © Springer International Publishing Switzerland 2015.

关键词： Principal component analysis

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Non-negative low-rank and group-sparse matrix factorization 21

Non-negative low-rank and group-sparse matrix factorization

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21st International Conference on MultiMedia Modeling, MMM 2015

作者： Wu, Shuyi Zhang, Xiang Guan, Naiyang Tao, Dacheng Huang, Xuhui Luo, Zhigang Science and Technology on Parallel Distributed Processing Laboratory College of Computer National University of Defense Technology Changsha Hunan410073 China Department of Computer Science and Technology College of Computer National University of Defense Technology Changsha Hunan410073 China Centre for Quantum Computation & Intelligent Systems and the Faculty of Engineering and Information Technology University of Technology Sydney 235 Jones Street UltimoNSW2007 Australia

ISBN: (纸本)9783319144412

Non-negative matrix factorization (NMF) has been a popular data analysis tool and has been widely applied in computer vision. However, conventional NMF methods cannot adaptively learn grouping structure froma *** paper proposes a non-negative low-rank and group-sparse matrix factorization (NLRGS) method to overcome this deficiency. Particularly, NLRGS captures the relationships among examples by constraining rank of the coefficients meanwhile identifies the grouping structure via group sparsity regularization. By both constraints, NLRGS boosts NMF in both classification and clustering. However, NLRGS is difficult to be optimized because it needs to deal with the low-rank constraint. To relax such hard constraint, we approximate the low-rank constraint with the nuclear norm and then develop an optimization algorithm for NLRGS in the frame of augmented Lagrangian method(ALM). Experimental results of both face recognition and clustering on four popular face datasets demonstrate the effectiveness of NLRGS in quantities. © Springer International Publishing Switzerland 2015.

关键词： Non-negative matrix factorization

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