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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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Malicious Website Detection Based on URLs Static Features

Malicious Website Detection Based on URLs Static Features

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2018 International Conference on Modeling, Simulation and Optimization(MSO 2018)

作者： Chun-ming WU Min LI Li YE Xian-chun ZOU Bao-hua QIANG School of Computer and Information Science Southwest University Guangxi Cooperative Innovation Center of Cloud Computing and Big Data Guilin University of Electronic Technology

Real-time and effectiveness are two basic requirements in URL-based malicious website detection. Based on the analysis of malicious URLs construction pattern, this paper puts forward a method to detect malicious website based on URLs static features. All features used in classification are extracted using statistic and there is no need to online access to obtain additional information about website, which reduces detection time greatly. At the same time, a feature reduction method is given in feature vector construction. Combined with reasonable selection of machine learning algorithm, our method can achieve both high accuracy and high efficiency. A series of comparative experiments proved the effectiveness of our method.

关键词： Malicious URL Static features Feature extraction Machine learning

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Real-time network traffic classification based on CDH pattern matching 14

Real-time network traffic classification based on CDH patter...

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14th International Conference on Computational Intelligence and Security, CIS 2018

作者： Li, Xunzhang Wang, Yong Ke, Wenlong Feng, Hao School of Computer Science and Information Security Guilin University of Electronic Technology Guilin Guangxi541004 China School of Information and Communication Guilin University of Electronic Technology Guilin Guangxi541004 China Guangxi Cooperative Innovation Center of Cloud Computing and Big Data Guilin University of Electronic Technology Guilin Guangxi541004 China Guangxi Colleges and Universities Key Laboratory of Cloud Computing and Complex Systems Guilin University of Electronic Technology Guilin Guangxi541004 China

ISBN: (纸本)9781728101699

In recent years, with the rapid development of the Internet, the data scale of application behavior and application traffic have exploded. How to classify the real-time traffic of network becomes a big challenge. How to balance the accuracy and real-time of traffic classification is a difficult problem in technology. Therefore, this paper proposes a pattern matching real-time traffic classification method named PM, which first uses jpcap to accept network traffic data in real time, and then uses pattern matching to perform real-time matching traffic characteristics to achieve traffic classification. Among them, the use of the distributed message system kafka and the parallel computing framework Spark significantly improve the execution efficiency of the program. The experimental results show that PM has good performance in terms of accuracy. © 2018 IEEE.

关键词： Pattern matching

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Schema-driven performance evaluation for highly concurrent scenarios 23rd

Schema-driven performance evaluation for highly concurrent s...

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23rd International Conference on database Systems for Advanced Applications, DASFAA 2018

作者： Zhang, Jingwei Feng, Li Yang, Qing Lin, Yuming Guangxi Cooperative Innovation Center of Cloud Computing and Big Data Guilin University of Electronic Technology Guilin541004 China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin541004 China Guangxi Key Laboratory of Automatic Measurement Technology and Instrument Guilin University of Electronic Technology Guilin541004 China

ISBN: (纸本)9783319914541

Online applications needs to support highly concurrent access and to response to users as soon as possible. Two primary factors make the above requirements to be a technical challenge, one is the large user base, the other is the sharp rise in traffic caused by some specific activities, such as ticketing on *** during Spring Festival season, shopping on *** during its dual 11 promotions, etc. For the latter, a core focus is how to expand the performance of those existing hardware and software and then to ensure the quality of services when a sharp rise on access happened. Since database schemas have a direct link with data access granularity, etc., this paper considers database schemas as an important factor for performance optimization on highly concurrent access and also covers other elements affecting access performance, such as cache, concurrency, etc., to analyze the performance factors for databases. Extensive experiments are designed to conduct both performance testing and analyzing under different schemas. The experimental results show that a reasonable configuration can contribute a good database performance, which provides factual basis for optimizing highly concurrent applications. © Springer International Publishing AG, part of Springer Nature 2018.

关键词： database systems

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Time-based trajectory data partitioning for efficient range query 23rd

Time-based trajectory data partitioning for efficient range ...

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23rd International Conference on database Systems for Advanced Applications, DASFAA 2018

作者： Yue, Zhongwei Zhang, Jingwei Zhang, Huibing Yang, Qing Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin541004 China Guangxi Cooperative Innovation Center of Cloud Computing and Big Data Guilin University of Electronic Technology Guilin541004 China Guangxi Key Laboratory of Automatic Measurement Technology and Instrument Guilin University of Electronic Technology Guilin541004 China

ISBN: (纸本)9783319914541

The popularity of mobile terminals has given rise to an extremely large number of trajectories of moving objects. As a result, it is critical to provide effective and efficient query operations on large-scale trajectory data for further retrieval and analysis. Considering data partition has a great influence on processing large-scale data, we present a time-based partitioning technique on trajectory data. This partitioning technique can be applied on the distributed framework to improve the performance of range queries on massive trajectory data. Furthermore, the proposed method adopts time-based hash strategy to ensure both the partition balancing and less partitioning time. Especially, existing trajectory data are not required to be repartitioned when new data arrive. Extensive experiments on three real data sets demonstrated that the performance of the proposed technique outperformed other partitioning techniques. © Springer International Publishing AG, part of Springer Nature 2018.

关键词： Trajectories

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Multi-scale quantum harmonic oscillator algorithm with individual stabilization strategy 9th

Multi-scale quantum harmonic oscillator algorithm with indiv...

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9th International Conference on Swarm Intelligence, ICSI 2018

作者： Wang, Peng Li, Bo Jin, Jin Mu, Lei Xin, Gang Huang, Yan Ye, Xing Gui College of Computer Science and Technology Southwest Minzu University Chengdu610225 China Chengdu Institution of Computer Application of China Academy of Science Chengdu610041 China University of Chinese Academy of Sciences Beijing100049 China Huaiyin Normal University Huaiyin223300 China Cloud Computing and Big Data Center China Unicom Fujian Branch Fuzhou350007 China

ISBN: (纸本)9783319938141

Multi-scale quantum harmonic oscillator algorithm (MQHOA) is a novel global optimization algorithm inspired by wave function of quantum mechanics. In this paper, a MQHOA with individual stabilization strategy (IS-MQHOA) is proposed utilizing the individual steady criterion instead of the group statistics. The proposed strategy is more rigorous for the particles in the energy level stabilization process. A more efficient search takes place in the search space made by the particles and improves the exploration ability and the robustness of the algorithm. To verify its performance, numerical experiments are conducted to compare the proposed algorithm with the state-of-the-art SPSO2011 and QPSO. The experimental results show the superiority of the proposed approach on benchmark functions. © Springer International Publishing AG, part of Springer Nature 2018.

关键词： Stabilization

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Design of Intelligent Robot Platform based on Multi-sensor Fusion

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

作者： Ya Dajin Lei Xiaochun Li Yue Chen Junyan Huang Rongcun Lan Lin School of computer and information security Guilin University of Electronic Technology Guilin 541004 China Guangxi Colleges and Universities Key Laboratory of Intelligent Processing of Computer Images and Graphics Guilin 541004 China Guangxi Cooperative Innovation Center of cloud computing and Big Data Guilin University of Electronic Technology Guilin 541004 China

The mobile robot adapts to the more complicated indoor and outdoor environments, and can expand its scope of application. In order to reduce the influence of the cumulative error caused by navigation in complex environments, the indoor mobile robot that combines Inertial Measurement Unit (IMU) and encoder fusion is designed and implemented. In view of the limitations of the traditional single lidar scheme, a Multi-sensor Fusion scheme is proposed to achieve indoor map construction, path planning, multi-point navigation and other functions, and a MSIF KartoSLAM (Multi-sensor Information Fusion) algorithm is proposed, which combines the KartoSLAM algorithm and Multi-sensor information to achieve map construction in complex environments. Through comprehensive testing in the indoor environment, the results show that the Multi-sensor Fusion scheme is superior to the traditional single lidar scheme, and can achieve higher accuracy in mapping and navigation. At the same time, the robot platform can also be combined with the Internet of Things technology and integrated into intelligent housing system.

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Design of People Flow Monitoring System in Public Place based on MD-MCNN

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

作者： Xiong Tianmin Lei Xiaochun Zheng Xingwen Chen Junyan Feng Yizhou School of computer and information security Guilin University of Electronic Technology Guilin 541004 China Guangxi Colleges and Universities Key Laboratory of Intelligent Processing of Computer Images and Graphics Guilin 541004 China Guangxi Cooperative Innovation Center of cloud computing and Big Data Guilin University of Electronic Technology Guilin 541004 China

Due to the limitation of hardware resources, the traditional people flow monitoring system based on computer vision in public places can't meet different crowd-scale scenarios. Therefore, a people flow monitoring system based on MD-MCNN algorithm is designed, which is an application system combining the improved SSD object detection algorithm MNSSD and MCNN density map regression algorithm. In the initial stage, the system uses MNSSD for accurate detection and counting. If the people flow gradually reaches a certain threshold, the system automatically uses MCNN to estimate people flow until the people flow falls below the threshold. Through the experimental verification, the system can realize the people flow statistics of low-density and high-density people in different scenarios, and can be applied on the existing embedded platform. This scheme can be extended to smart cities, smart scenic spots, smart transportation and other fields.

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A Face Recognition Method Based on CNN

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Journal of Physics: Conference Series 2019年第1期1395卷

作者： Zhiming Xie Junjie Li Hui Shi Department of Information Engineering Shanwei Polytechnic Shanwei 516600 Guangdong China The Research Institute of Cloud Computing and Data Center Project Design Shanwei Innovation Industrial Design & Research Institute Shanwei 516600 Guangdong China The Professional Committee Cloud Computing and Big Data in Higher Vocational College Higher Education Institute in Guangdong Province Shanwei 516600 Guangdong China

The traditional face recognition technology is more complicated for the extraction of facial image features and the selection of classifiers, and the recognition rate is not high. With the continuous maturity of the convolutional neural network from handwritten digit recognition to face recognition, A face recognition algorithm that tests CNN using the Python+Keras framework. The method mainly involves two aspects. One is to observe the influence on the network by changing the number of neurons in the hidden layer; the other is to observe the influence on the network by changing the number of feature maps of the convolutional layer 1 and the convolutional layer 2. The best CNN model is 36-76-1024 through multiple sets of experimental tests. The model can automatically extract facial image features and classify them. Using adam optimizer and softmax classifier for face recognition can make training faster convergence and more. Effectively improve accuracy and use the Dropout method to avoid overfitting. The experimental results show that the recognition rate of the CNN model on the olivettifaces face database is 97.5%. When the optimal CNN model is used, the average recognition rate is close to 100%, which verifies the validity and accuracy of the algorithm and model.

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Small Evolution Antenna Design Method Based on Dynamic Hill Climbing Algorithm and Orthogonal Experiment

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Journal of Physics: Conference Series 2019年第1期1395卷

作者： Hui Shi Junjie Li Zhiming Xie Department of Information Engineering Shanwei Polytechnic Shanwei 516600 Guangdong China The Research Institute of Cloud Computing and Data Center Project Design Shanwei Innovation Industrial Design & Research Institute Shanwei 516600 Guangdong China The Professional Committee Cloud Computing and Big Data in Higher Vocational College Higher Education Institute in Guangdong Province Shanwei 516600 Guangdong China

Small-scale evolution antennas have the advantages of high gain, wide bandwidth and small size, and have broad application prospects in the aerospace field. Aiming at the complex high-dimensional and dynamic problems of aerial antenna modeling, a dynamic hill-climbing algorithm based on orthogonal design is designed and implemented to simulate and optimize the single-span antenna in high-frequency operation mode. In the optimization problem, this paper defines a new individual comparison mechanism, which can reflect the number of violations of constraints and the degree of violation of each constraint, making the comparison of individuals more reasonable. The antenna simulation results demonstrate the effectiveness and feasibility of using dynamic evolutionary algorithms for antenna design.

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