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International Conference on Wireless Communications and Signal Processing (WCSP)

作者： Yanqun Tang Caiyao Sheng Wei Liu Yunpeng Hu Xiaoyi Zhang Zhengzhou Institute of Information Science and Technology Zhengzhou P. R. China National Digital Switching System Engineering & Technology R&D Center Zhengzhou P. R. China PLA Troops 91290 Beijing P. R. China

ISBN: (纸本)9781467376884

The thinking of signal-to-leakage-plus-noise ratio (SLNr) is widely used for multi-user multiple-input multiple-output (MU-MIMO) systems in many works. We analyze the secrecy performance of the SLNr-based beamforming scheme in the multiple-input single-output multi-antenna eavesdropper (MISÓME) wiretap channel. Our analysis proofs the SLNr-based beamforming scheme has almost the same performance as the generalized eigenvalue decomposition (GEd) based beamforming scheme, and has significant gain over the zero-forcing (ZF) beamforming scheme.

关键词： GEd-based beamforming SLNr-based beamforming Wiretap channel ZF beamforming performance analysis Beamforming Privacy Scheme multiple input multiple output systems

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City-Level Geolocation Based on routing Feature

City-Level Geolocation Based on Routing Feature

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International Conference on Advanced Information Networking and Applications (AINA)

作者： Fan Zhao Yuhan Song Fenlin Liu Ke Ke Jingning Chen Xiangyang Luo Zhengzhou Information Science and Technology Institute China National Digital Switching System Engineering and Technological R&D Center Zhenazhou Henan China Zhengzhou Information Science and Technology Institute State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou Henan China

For the problem that traditional approaches for IP geolocation based on delay measurement are difficult to apply to network with weak connectivity such as China's Internet, in this paper, we utilize its hierarchical topology and proposed an approach of City-level geolocation based on routing feature. Taking IPs with known geographical location as reference nodes, this approach extracts identifying IPs of candidate regions or cities based on decision tree learning algorithm. We match the path of the target with IPs above called identifying features, and then select the region or city whose identifying feature is contained on the target's path as geolocation result. This approach improves the average accuracy for the Internet with weak connectivity hierarchical topology to 93% vs. 73% for the previous learning-based geolocation approach.

关键词： Geology Cities and towns IP networks delays Internet Topology Network topology

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Spectral segmentation based on the weighted histogram

Spectral segmentation based on the weighted histogram

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2013 International Conference on Future Computer and Information technology, ICFCIT 2013

作者： Zeng, Lei Chen, Jian Tong, Li Yan, Bin Ping, Xijian National Digital Switching System Engineering and Technology R and D Center Zhengzhou China

ISBN: (纸本)9781845648510

Spectral segmentation algorithms can extract the global impression of an image and be widely used in many areas and applications related to image segmentation. Traditional spectral algorithms need to construct an affinity matrix based on all the pixels in the image and compute the eigenvectors of the matrix to find global optimum segmentation. With the growing of image size, the spatial and computational complexity increases egregiously. We propose a novel approach for solving the problem. rather than focusing on pixels in the image, our approach aims at the gray histogram extracting the global impression of an image. We construct an affinity matrix directly based on the gray histogram and weight matrix with a histogram coefficient of corresponding gray level. Our method decreases the affinity matrix dimension to 256 × 256 at most for the gray image, and thus decreases the complexity sharply. The spatial and computational complexity is insensitive to the image size. We have used the proposed method to segment text and PCB images, and found the segmentation results to be very encouraging. © 2014 WIT Press.

关键词： Computational complexity

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center surround feature detection of volumetric data

Center surround feature detection of volumetric data

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2013 International Conference on Future Computer and Information technology, ICFCIT 2013

作者： Cui, Mingming Chen, Jian Yan, Bin Zeng, Lei Tong, Li National Digital Switching System Engineering and Technology R and D Center Zhengzhou China

ISBN: (纸本)9781845648510

The process of feature point detection is the first stage of many computer vision applications including object detection, recognition and reconstruction. Aimed at the drawbacks (e.g. inefficiency and poor rotation invariance) of some classical detectors for volumetric data, we present a new scale-invariant center surround feature detector. Combining a 3d center surround feature point detector and the use of an integral image will accelerate the building of the scale space. Meantime, we also use Harris criterion to perform line suppression to enhance the stability of feature point detection. The experimental results indicate that our new detectors make the balance between computational efficiency and repetition rate. © 2014 WIT Press.

关键词： Computational efficiency

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基于OpenFlow的流分片负载均衡算法(英文)

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China Communications 2014年第12期11卷 72-82页

作者：王鹏兰巨龙陈庶樵 National Digital Switching System Engineering and Technological R&D Center(NDSC)

Today’s data center networks are designed using densely interconnected hosts in the data *** are multiple paths between source host and destination ***,how to balance traffic is key issue with the fast growth of network *** lots of load balancing methods have been proposed,the traditional approaches cannot fully satisfy the requirement of load balancing in data center *** main reason is the lack of efficient ways to obtain network traffic statistics from each network *** a solution,the OpenFlow protocol enables monitoring traffic statistics by a centralized ***,existing solutions based on OpenFlow present a difficult dilemma between load balancing and packet *** achieve a balance between load balancing and packet reordering,we propose an OpenFlow based flow slice load balancing *** introducing the idea of differentiated service,the scheme classifies Internet flows into two categories:the aggressive and the normal,and applies different splitting granularities to the two classes of *** scheme improves the performance of load balancing and also reduces the number of reordering *** the trace-driven simulations,we show that the proposed scheme gains over 50%improvement over previous schemes under the path delay estimation errors,and is a practical and efficient algorithm.

关键词： OpenFlow traffic splitting load balancing packet reordering splitting granularity

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Learning class-specific pooling shapes for image classification

Learning class-specific pooling shapes for image classificat...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Jinzhuo Wang Wenmin Wang ronggang Wang Wen Gao Digital Media R&D Center Peking University Shenzhen Graduate School National Engineering Laboratory for Video Technology Peking University

Spatial pyramid (SP) representation is an extension of bag-of-feature model which embeds spatial layout information of local features by pooling feature codes over pre-defined spatial shapes. However, the uniform style of spatial pooling shapes used in standard SP is an ad-hoc manner without theoretical motivation, thus lacking the generalization power to adapt to different distribution of geometric properties across image classes. In this paper, we propose a data-driven approach to adaptively learn class-specific pooling shapes (CSPS). Specifically, we first establish an over-complete set of spatial shapes providing candidates with more flexible geometric patterns. Then the optimal subset for each class is selected by training a linear classifier with structured sparsity constraint and color distribution cues. To further enhance the robust of our model, the representations over CSPS are compressed according to the shape importance and finally fed to SVM with a multi-shape matching kernel for classification task. Experimental results on three challenging datasets (Caltech-256, Scene-15 and Indoor-67) demonstrate the effectiveness of the proposed method on both object and scene images.

关键词： Shape Image color analysis Standards Kernel Training Layout Encoding

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A blind extraction method of FH signals based on improved symmetric co-occurrence matrix in HF channel

A blind extraction method of FH signals based on improved sy...

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International Conference on Vehicle and Mechanical engineering and Information technology, VMEIT 2014

作者： Gu, Pei Wang, Bin National Digital Switching System Engineering and Technological R and D Center Zhengzhou China

ISBN: (纸本)9783038350606

To remove the noise and interference signals in the blind detection of FH signals from HF channel, this paper gives a FH signals extraction method based on the improved symmetric GLCM, by combining the time-frequency analysis with the threshold method of GLCM. Firstly, the paper defines the calculation of improved symmetric GLCM on the direction of frequency and time. Then, the noise threshold is estimated based on the noise probability in the improved GLCM of frequency and the FH signals from the improved GLCM of time can be extracted by using the noise threshold. Simulation results show that the method can extract integrated FH signals under low SNr without any prior information, and that the estimation of noise threshold is more accurate and stable. Furthermore the method is simple with a small amount of computation, which is easy to be applied in the engineering. © (2014) Trans Tech Publications, Switzerland.

关键词： Image processing

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OpenFIow Based Flow Slice Load Balancing

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China Communications 2014年第12期11卷 72-82页

作者： WANG Peng LAN Julong CHEN Shuqiao National Digital Switching System Engineering and Technological R&D Center (NDSC) Zhengzhou He'nan 450000 China

Today's data center networks are designed using densely interconnected hosts in the data *** are multiple paths between source host and destination ***,how to balance traffic is key issue with the fast growth of network *** lots of load balancing methods have been proposed,the traditional approaches cannot fully satisfy the requirement of load balancing in data center *** main reason is the lack of efficient ways to obtain network traffic statistics from each network *** a solution,the OpenFlow protocol enables monitoring traffic statistics by a centralized ***,existing solutions based on OpenFlow present a difficult dilemma between load balancing and packet *** achieve a balance between load balancing and packet reordering,we propose an OpenFlow based flow slice load balancing *** introducing the idea of differentiated service,the scheme classifies Internet flows into two categories:the aggressive and the normal,and applies different splitting granularities to the two classes of *** scheme improves the performance of load balancing and also reduces the number of reordering *** the trace-driven simulations,we show that the proposed scheme gains over 50%improvement over previous schemes under the path delay estimation errors,and is a practical and efficient algorithm.

关键词： OpenFlow traffic splitting load balancing packet reordering splitting granularity

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An early traffic sampling algorithm 9

An early traffic sampling algorithm

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9th International ICST Conference on Testbeds and research Infrastructures for the development of Networks and Communities, TridentCom 2014

作者： Ying, Hou Hai, Huang dan, Chen Shengnan, Wang Peng, L. National Digital Switching System Engineering and Techological R and D center ZhengZhou450002 China

ISBN: (纸本)9783319133256

The first several packets of a flow play key role in the on-line traffic managements. Early traffic sampling, extracting the first several packets of every flow, is raised. This paper proposes a structure named CTBF, combination of counting Bloom Filter and time Bloom Filter. Based on it, the algorithm is designed to realize automatically removing the space occupied by the timeout flow. The analyses and experiments demonstrate that the sampling accuracy of CTBF is better than that of LrU and Fixed-T algorithm in the same space. © Institute for Computer Sciences, Social Informatics and Telecommunications engineering 2014.

关键词： Bandpass filters

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Traffic classification method by combination of host behaviour and statistical approach

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Journal of engineering Science and technology review 2014年第3期7卷 151-157页

作者： Hou, Ying Huang, Hai Shao, Wenchao Huang, Heqing National Digital Switching System Engineering and Techological R and D Center ZhengZhou 450002 China University of Kentucky Lexington KY 40506-0046 United States

Traffic classification, one of the most active fields in Internet traffic research, is the substructure of network design and management. Generally, there are four techniques to identify the traffic, port-based, payload-based, flow statistic-based, and host-based approaches. In this paper, a hybrid method to classify the traffic was proposed combining the host behaviour and the Affinity Propagation (AP) algorithm. Simple features in the statistical process were selected at the first stage of classification;then, the initial classification results and the host behaviour model were combined to generate the final results. The host behaviour model was updated by the feedback of previous classification. The combining classification approach was evaluated on two real traces. The results indicated that the proposed technique offered improved performance compared with BLINC and independent AP algorithms. © 2014 Kavala Institute of technology.

关键词： Telecommunication traffic

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