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Research on SDN Multi Controller Deployment based on K-means++

Journal of Physics: Conference Series 2020年第1期1606卷

作者： Li Yue Chen Junyan Liang Chuxin Lei Xiaochun School of computer and information security Guilin University of Electronic Technology Guilin 541004 China Guangxi cloud computing and big data collaborative innovation center Guilin 541001 China Guangxi key laboratory of image and graphic intelligent processing Guilin 541004 China

In large-scale SDN network, a single centralized controller can not meet the demand, and multiple controllers are needed to deal with the problem, which leads to the problem of multi control balanced deployment. In this paper, the topology of SDN switches and links is known. The main research contents are as follows: the mathematical model of SDN multi controller deployment is established, and the appropriate network topology is selected and the multi controller deployment problem is solved. In the research, the number of controllers needed in the network and the switches managed by each controller is determined by the algorithm results, and the mapping relationship between controllers and switches is established. By analyzing the deployment results of the same network topology under different algorithms, the influence of different clustering algorithms on the experimental results is obtained. At the same time, the better deployment experiment results are simulated.

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Finding map regions with high density of query keywords

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Frontiers of information technology & Electronic Engineering 2017年第10期18卷 1543-1555页

作者： Zhi YU Can WANG Jia-jun BU Xia HU Zhe WANG Jia-he JIN Alibaba-Zhejiang University Joint Institute of Frontier Technologies Zhejiang Provincial Key Laboratory of Service Robot College of Computer Science and Technology Zhejiang University Hangzhou 310027 China Hangzhou Science and Technology Information Research Institute Hangzhou 310001 China

We consider the problem of finding map regions that best match query keywords. This region search problem can be applied in many practical scenarios such as shopping recommendation, searching for tourist attractions, and collision region detection for wireless sensor networks. While conventional map search retrieves isolate locations in a map, users frequently attempt to find regions of interest instead, e.g., detecting regions having too many wireless sensors to avoid collision, or finding shopping areas featuring various merchandise or tourist attractions of different styles. Finding regions of interest in a map is a non-trivial problem and retrieving regions of arbitrary shapes poses particular challenges. In this paper, we present a novel region search algorithm, dense region search(DRS), and its extensions, to find regions of interest by estimating the density of locations containing the query keywords in the region. Experiments on both synthetic and real-world datasets demonstrate the effectiveness of our algorithm.

关键词： Map search Region search Region recommendation Spatial keyword search Geographic information system Location-based service

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Sparse Low-Rank Component Coding for Face Recognition with Illumination And Corruption

Sparse Low-Rank Component Coding for Face Recognition with I...

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IEEE International Conference on Acoustics, Speech and Signal processing

作者： Shicheng Yang Ying Wen Lianghua He Shanghai Key Laboratory of Multidimensional Information Processing Department of Computer Science and Technology East China Normal University Shanghai China Department of Computer Science and Technology Tongji University Shanghai China

ISBN: (纸本)9781538646595

Sparse representation-based classification shows a good performance for face recognition in recent years, but it can not be suitable for face recognition with illumination and corruption, which are often presented in the practical applications. To solve the problem, in this paper, we propose a novel SRC based method for face recognition named sparse low-rank component coding (SLC). In SLC, we utilize the low-rank component from training dataset to construct dictionary. The dictionary composed of low-rank component is able to describe the face feature better, especially for training samples with illumination and corruption. Our recognition rule is based on the minimum class-wise reconstruction residual which leads to a substantial improvement on the performance of SLC. Extensive experiments on benchmark face databases demonstrate that the proposed method consistently outperforms the other sparse representation based approaches for face recognition with illumination and corruption.

关键词： Face recognition sparse representation classification low-rank component illumination and corruption Facial Recognition illumination sparse representation Lighting vandalism corruption CCL21 gene STANFORD LINEAR COLLIDER DETECTOR Face Low-rank coal

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Seam carving algorithm based on saliency 1st

Seam carving algorithm based on saliency

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1st International Conference on Smart Vehicular technology, Transportation, Communication and Applications, VTCA 2017

作者： Lin, Wen Zhang, Fuquan Lian, Renbao Xu, Lin Chen, Xueyun Kuang, Linghong School of Electronic Information Science Fujian Jiangxia University Fuzhou University Town Fuzhou350108 China School of Software Beijing Institute of Technology Beijing100081 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350121 China Innovative Information Industry Research Institute Fujian Normal University Fuzhou350300 China Institute of Information Engineering Longyan University Town DongXiao XinLuo District Longyan364012 China School of Information Science and Engineering Fujian University of Technology Fuzhou University Town Fuzhou350118 China

ISBN: (纸本)9783319707297

This paper proposes a seam carving algorithm based on saliency. This algorithm makes saliency detection to the source image. Images are classified according to the gray-scale of saliency detection. Adding different energy protection methods, it can protect the foreground area of a subject and detailed areas of the edge. Then the cumulative energy map is calculated. According to the principle of deleting the minimum energy pixel, single pixel-wide carves chosen to be deleted or copied. The experimental result shows that the algorithm avoids image restoration caused by extracting too many pixels in saliency area and non equal-ratio scaling. It reduces the deformed structures caused by displacement of edge pixel and also improves the integrity of algorithm. © Springer International Publishing AG 2018.

关键词： Pixels

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Parallel Multi-Label Propagation Based on Influence Model and Its Application to Overlapping Community Discovery

Parallel Multi-Label Propagation Based on Influence Model an...

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作者： Qiu, Qirong Guo, Wenzhong Chen, Yuzhong Guo, Kun Li, Rongrong School of Economics and Management Fuzhou University Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou350116 China College of Mathematics and Computer Science Fuzhou University Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Key Laboratory of Spatial Data Mining and Information Sharing Ministry of Education Fuzhou350116 China

Finding communities in networks is one of the challenging issues in complex network research. We have to deal with very large networks that contain billions of vertices, which makes community discovery a computationally intensive work. Moreover, communities usually overlap each other, which greatly increases the difficulty of identifying the boundaries of communities. In this paper, we propose a parallel multi-label propagation algorithm (PMLPA) that enhances traditional multi-label propagation algorithm (MLPA) in two ways. First, the critical steps of MLPA are parallelized based on the MapReduce model to get higher scalability. Second, new label updating strategy is used to automatically determine the most valuable labels of each vertex. Furthermore, we study the improvement of PMLPA through considering the influence of vertices and labels on label updating. In this way, the importance of each label can be described with higher precision. Experiments on artificial and real networks prove that the proposed algorithms can achieve both high discovering accuracy and high scalability. © 2017 World Scientific Publishing Company.

关键词： Complex networks

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Time domain acoustic scattering from locally perturbed flat substrates 1st

Time domain acoustic scattering from locally perturbed flat ...

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1st International Conference on Smart Vehicular technology, Transportation, Communication and Applications, VTCA 2017

作者： Chen, Bo Zhang, Fuquan Xu, Lin Liu, Minghui College of Science Civil Aviation University of China Tianjin China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou China School of Software Beijing Institute of Technology Beijing China Innovative Information Industry Research Institute Fujian Normal University Fuzhou China School of Criminal Investigation and Counter Terrorism People’s Public Security University of China Beijing China

ISBN: (纸本)9783319707297

This paper is concerned with the analysis of the time domain acoustic scattering from locally perturbed flat substrates. For this three dimensional scattering problem with unbounded scatterer, boundary integral equation is directly established on the boundary of the unbounded scatterer without application of the symmetric continuation. The well-posedness of the time domain boundary integral equation is proved. © Springer International Publishing AG 2018.

关键词： Boundary integral equations

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Double time slot RFID anti-collision algorithm based on gray code 5

Double time slot RFID anti-collision algorithm based on gray...

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5th International Conference on information Science and Cloud Computing, ISCC 2017

作者： Deng, Hongwei Li, Lang Wang, Hui School of Computer Science and Technology Hengyang Normal University School of Information Science and Engineering Central South University Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hunan 421002 China

To solve the radio frequency identification problem, an anti-collision algorithm based on the Gray code (BSGC) was developed. The proposed algorithm reduces the effort required to search for tag prefixes in accordance with Gray code regulations and enhances the identification speed through efficient division and branching of the collision tags. The results of simulation and subsequent analysis of the proposed algorithm confirm that it effectively reduces the number of collisions and transmission delays, enhances the throughput rate, and increases the tag identification efficiency. © Copyright owned by the author(s).

关键词： Radio frequency identification (RFID)

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An improved Chinese text multi-label classification method based on CNN

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Journal of Physics: Conference Series 2020年第1期1619卷

作者： Yuanxia Xin Zhi Zhang Collage of Computer Science and Technology Wuhan University of Science and Technology Wuhan 430065 Hubei China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan 430065 Hubei China Big Data Science and Engineering Research Institute Wuhan University of Science and Technology Wuhan 430065 Hubei China

Text multi-label classification technology can accurately and quickly classify text information into related categories or topics, and help people quickly locate the required content in massive information resources, which is of great significance in application. As the traditional classification algorithm is faced with the problems of low classification accuracy due to the low correlation of data labels, unbalanced label data and few short text feature words, this paper firstly performs hierarchical pre-processing on label data to transform multi-label classification into hierarchical text multi-classification. At the same time, an improved multi-label classification algorithm Multi-label Convolutional Neural Networks (ML-CNN) is proposed. Based on the TensorFlow framework, a CNN model is designed and different training models are constructed for each level of label classification. According to the number of classification levels, the output of the upper level label is stitched to the original input tail as the next level of input. Experiments on the description information of 500,000 Chinese products with labels, show that the improved algorithm will significantly improve the classification accuracy and the accuracy of each level can reach more than 88%, which proves the feasibility and effectiveness of the algorithm.

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A Multiscale Superpixel-Level Salient Object Detection Model Using Local-Global Contrast Cue

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Journal of Shanghai Jiaotong university(Science) 2017年第1期22卷 121-128页

作者：穆楠徐新王英林张晓龙 School of Computer Science and Technology Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan University of Science and Technology School of Information Management and Engineering Shanghai University of Finance and Economics

The goal of salient object detection is to estimate the regions which are most likely to attract human's visual attention. As an important image preprocessing procedure to reduce the computational complexity, salient object detection is still a challenging problem in computer vision. In this paper, we proposed a salient object detection model by integrating local and global superpixel contrast at multiple scales. Three features are computed to estimate the saliency of superpixel. Two optimization measures are utilized to refine the resulting saliency map. Extensive experiments with the state-of-the-art saliency models on four public datasets demonstrate the effectiveness of the proposed model.

关键词： salient object detection superpixel multiple scales local contrast global contrast TP 391.4 A

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An object classification method based on the improved bacterial foraging optimisation algorithm

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International Journal of Wireless and Mobile Computing 2017年第2期12卷 166-173页

作者： Zeng, Zhigao Guan, Lianghua Yi, Shengqiu Zhu, Yanhui Liu, Qiang Tong, Qi Zeng, Sanyou College of Computer and Communication Hunan University of Technology Hunan412007 China Intelligent Information Perception and Processing Technology Hunan Province Key Laboratory Hunan China Department of Computer Science China University of GeoSciences Wuhan Hubei China

This paper proposes a new object classification method based on an improved bacterial foraging optimisation algorithm. Firstly, a dynamic step size is used instead of the fixed step size of the chemotaxis. Secondly, the fixed elimination-dispersal probability is replaced by the dynamic probability. Features are extracted to distinguish the objects, such as pedestrians, cars and pets. Ultimately, all the objects are classified using the improved bacterial foraging optimisation algorithm. The experimental results prove that the effectiveness of the object classification method proposed in this paper is better than that of other algorithms. Copyright © 2017 Inderscience Enterprises Ltd.

关键词： Optimization

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