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Asia-Pacific Conference on communications

作者： Wei Li Zhen Yang Haifeng Hu Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Nanjing China

Graphical models have been widely applied in solving distributed inference problems in wireless sensor networks (WSNs). In this paper, we formulate the distributed multi-sensor tracking problem in a WSN as an inference problem on a factor graph. Using particle filtering methods, we propose a nonparametric variant of sum-product algorithm (SPA), called sequential particle-based SPA (SPSPA), for factor graphs to infer the multi-sensor target states over time. In the proposed algorithm, importance sampling methods are used to sample from message products, and the computational complexity of SPSPA is thus linear in the number of particles. We apply the SPSPA to a distributed multi-sensor tracking problem, and evaluate its performance in terms of the measurement noise and the number of particles.

关键词： wireless sensor networks wireless communication Filtering Noise measurement

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GRIDLESS TWO-DIMENSIONAL DOA ESTIMATION WITH L-SHAPED ARRAY BASED ON THE CROSS-COVARIANCE MATRIX

GRIDLESS TWO-DIMENSIONAL DOA ESTIMATION WITH L-SHAPED ARRAY ...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Xiaohuan Wu Wei-Ping Zhu Jun Yan Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (纸本)9781538646595

The atomic norm minimization (ANM) has been successfully incorporated into the two-dimensional (2-D) direction-of-arrival (DOA) estimation problem for super-resolution. However, its computational workload might be unaffordable when the number of snapshots is large. In this paper, we propose two gridless methods for 2-D DOA estimation with L-shaped array based on the atomic norm to improve the computational efficiency. Firstly, by exploiting the cross-covariance matrix an ANM-based model has been proposed. We then prove that this model can be efficiently solved as a semi-definite programming (SDP). Secondly, a modified model has been presented to improve the estimation accuracy. It is shown that our proposed methods can be applied to both uniform and sparse L-shaped arrays and do not require any knowledge of the number of sources. Furthermore, since our methods greatly reduce the model size as compared to the conventional ANM method, and thus are much more efficient. Simulations results are provided to demonstrate the advantage of our methods.

关键词： 2-D DOA estimation L-shaped array atomic norm cross-covariance matrix

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Heterogeneous Data Integration and Fusion System Based on Metadata Conflict Algorithms in USPIOT

Heterogeneous Data Integration and Fusion System Based on Me...

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wireless communication and sensor network, Intl Conference on

作者： Jian-Min Bao Tian-Tian Hu Lin Pan He Xu Hai-Feng Hu Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (纸本)9781479970926

With the development of the Internet of Things, data islands and information redundancy which caused by massive heterogeneous data has become a challenge of many commercial applications and scientific research hot spots. First, we proposed and designed a MapReduce data integration and data fusion architecture, then, we established a stable information processing environment and a unified information retrieval interface for users, and then we analyzed MapReduce implementation processes, management processes, and the connection process. Meanwhile we proposed a conflict processing algorithms in processing heterogeneous redundant data problems by using metadata, and applied them to the processing of creating the virtual database using MapReduce technology, eliminating the redundant information to enhance the utilization of data space. Finally, we established the bench system to provide a unified heterogeneous data programming interface and memory management with heterogeneous data integration and fusion for users in our developed platform USPIOT (Ubiquitous Service Platform for Internet Of Things) and achieved better results.

关键词： Databases Data integration Humidity Data models Temperature distribution Internet of things

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A data placement strategy based on clustering and consistent hashing algorithm in cloud computing

A data placement strategy based on clustering and consistent...

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International Conference on communications and networking in China (CHINACOM)

作者： Qiang Li Kun Wang Suwei Wei Xuefeng Han Lili Xu Min Gao Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (纸本)9781479959716

To reduce time delay of processing data and improve the efficiency of cloud computing, a clustering algorithm based on the principle of minimum distance is proposed to place user-based and item-based data, update cluster centre and the threshold dynamically. Besides, consistent hashing is combined to solve the fault tolerance and scalability issues. In addition, Case-Based Reasoning (CBR) algorithm and item-based Coordination Filtering (CF) algorithms are used for filling sparse matrix to achieve better effect on the user-based clustering. Simulation results show that compared with data placement strategy based on K-means algorithm, this data placement strategy significantly improves clustering accuracy, greatly reduces delay of processing data and increases database scalability and redundancy, thereby improving the efficiency of cloud computing.

关键词： Clustering algorithms Servers Heuristic algorithms Delay effects Sparse matrices Scalability Cloud computing

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Arbitrary-Oriented Ship Detection Based on Rotation Region Locating networks in Large Scale Remote Sensing Images

Arbitrary-Oriented Ship Detection Based on Rotation Region L...

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International Conference on Image, Vision and Computing (ICIVC)

作者： Xipeng Liu Jianxin Chen Bin Kang Xuguang Zhang Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (纸本)9781728123264

Although deep learning has dominated the ship detection domain, it still has two challenges: arbitrary-oriented densely arranged ships cause detection omissions and large scale image contains redundant areas. This paper proposes an effective convolutional neural network framework for arbitrary-oriented ship detection in large scale and complex scenes. In this framework, we propose Cumulative Feature Pyramid networks for multi-receptive-field feature fusion, which enhances high-level semantic information at all scales. Based on the outputs of Region Proposal networks, Rotation Region Locating network predicts rotation bounding box of arbitrary-oriented ships and adopts rotation intersection over union to avoid the effect of ship dense arrangement. For large scale scenes, No-Ship Area Suppression uses OTSU algorithm to generate binary mask and then filter out non-ship regions to reduce redundant computations. Additionally, we firstly build a remote sensing image dataset for ship detection, which contains 4237 images and over 21200 ships. Experimental comparisons with the state-of-the-art approaches validate the effectiveness, accuracy and robustness of the proposed method.

关键词： Remote sensing Ship detection Deep learning Feature fushion Rotation region proposal Ships remote sensing remote sensing images Scale formation Machine Learning

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Content Centric networking: A New Approach to Big Data Distribution

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ZTE communications 2013年第2期11卷 3-10页

作者： Yi Zhu Zhengkun Mi Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications School of Computer Science and Telecommunication Engineering University of Jiangsu

In this paper, we explore network architecture anal key technologies for content-centric networking （CCN）, an emerging networking technology in the big-data era. We descrihe the structure anti operation mechanism of tl CCN node. Then we discuss mobility management, routing strategy, and caching policy in CCN. For better network performance, we propose a probability cache replacement policy that is based on cotent popularity. We also propose and evaluate a probability cache with evicted copy-up decision policy.

关键词： big data content-centric networking caching policy, mobility management routing strategy

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Design and Optimization of Socket Mechanism for Services in Internet of Things

Design and Optimization of Socket Mechanism for Services in ...

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2013 22nd wireless and Optical communication Conference

作者： Kun Wang Yuhua Zhang Yue Yu Yan Li Key Lab of Broadband Wireless Communication and Sensor Network Technology(Nanjing University of Posts and Telecommunications) Ministry of Education

ISBN: (纸本)9781467356985

It is necessary for a server oriented to the Internet of Things(IOT) applications to provide countless connections with efficient andreliable *** the communication layer should try to lower the *** a highly efficient design for a socket server with buffer pool and a thread pool for concurrent request on the IOT platform is *** reduces the system overhead and buffer usage to the largest extent while faced with a large number of connections and digital *** simulation shows that a socket server with a thread pool and buffer pool could lower the overhead on the context switch of threads as well as the I/O *** creates and destroys threads so as to energize the system.

关键词： IOT platform,thread pool,socket,modeling,optimization,simulation

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A RGB-D Face Recognition Approach without Confronting the Camera

A RGB-D Face Recognition Approach without Confronting the Ca...

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2015 IEEE International Conference on Computer and communications(ICCC 2015)

作者： Wei Zhou Jian-xin Chen Lei Wang Key Lab of Broadband Wireless Communication and Sensor Network Technology (Nanjing University of Posts and Telecommunications) Ministry of Education

Face recognition research mainly focuses on traditional 2D color images, which is extremely susceptible to be affected by external factors such as various viewpoints and has limited recognition accuracy. In order to achieve improved recognition performance, as well as the 3D face holds more abundant information than 2D, we present a 3D human face recognition algorithm using the Microsoft's Kinect. The proposed approach integrates the depth data with the RGB data to generate 3D face raw data and then extracts feature points, identifies the target via a two-level cascade classifier. Also, we build a 3D-face database including 16 individuals captured exclusively using Kinect. The experimental results indicate that the introduced algorithm can not only achieve better recognition accuracy in comparison to existing 2D and 3D face recognition algorithms when the probe face is exactly in front of Kinect sensor, but also can increase 9.3% of recognition accuracy compared to the PCA-3D algorithm when it is not confronting the camera.

关键词： 3D face recognition Kinect RGB-D images XML file classifier

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Secure Multi-period Routing in the Delay Tolerant networks

Secure Multi-period Routing in the Delay Tolerant Networks

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wireless communication and sensor network, Intl Conference on

作者： Jian-Min Bao Feng Wang Jun-Jie Zhang Shu Zhang Kun Wang Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (纸本)9781479970926

The Delay/Disruption Tolerant network (DTN) is characterized with intermittently connectivity and frequent partitions. Due to this, the DTN routing algorithm is very vulnerable to various kinds of malicious attacks. In this paper, combined with many other DTN forwarding approaches, we propose a multi-stage routing forwarding algorithm so as to further improve network throughput. To ensure the security advantages of multi-period routing, we also need to take the efficiency of the routing algorithm into account. The concept of trade-off coefficient is introduced in this paper in order to balance the security and efficiency. Through the security analysis and simulation result, we can reach the conclusion that by setting a reasonable trade-off factor, the mechanism can effectively resist the joint attack and also optimize the network performance.

关键词： Routing Security Throughput Analytical models Algorithm design and analysis network coding Encoding

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An improved binary PSO-based task scheduling algorithm in green cloud computing

An improved binary PSO-based task scheduling algorithm in gr...

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International Conference on communications and networking in China (CHINACOM)

作者： Lili Xu Kun Wang Zhiyou Ouyang Xin Qi Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (纸本)9781479959716

Cloud computing is experiencing a rapid development since a large amount of data need to be addressed. How to carry on the reasonable task scheduling plays a vital role in the efficiency of cloud computing. This paper proposes a green cloud task-scheduling algorithm (GCTA) based on the improved binary particle swarm optimization(BPSO). The main contribution of our work is avoiding matrix operations by using pipelined number for virtual machines and redefining the position and velocity of particle. Simulation shows that the proposed GCTA has less execution time, and reduces resource consumption accordingly.

关键词： Virtual machining Cloud computing Particle swarm optimization Scheduling algorithms Job shop scheduling

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