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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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Design of Intelligent Robot Platform based on Multi-sensor Fusion

Design of Intelligent Robot Platform based on Multi-sensor F...

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2020 International Conference on 5G Mobile Communication and Information Science, MCIS-5G 2020

作者： Dajin, Ya Xiaochun, Lei Yue, Li Junyan, Chen Rongcun, Huang Lin, Lan School of Computer and Information Security Guilin University of Electronic Technology Guilin541004 China Guangxi Colleges and Universities Key Lab. of Intelligent Processing of Computer Images and Graphics Guilin541004 China Guangxi Cooperative Innovation Center of Cloud Computing and Big Data Guilin University of Electronic Technology Guilin541004 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. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Navigation

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

Design of People Flow Monitoring System in Public Place base...

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2020 International Conference on 5G Mobile Communication and Information Science, MCIS-5G 2020

作者： Tianmin, Xiong Xiaochun, Lei Xingwen, Zheng Junyan, Chen Yizhou, Feng School of Computer and Information Security Guilin University of Electronic Technology Guilin541004 China Guangxi Colleges and Universities Key Lab. of Intelligent Processing of Computer Images and Graphics Guilin541004 China Guangxi Cooperative Innovation Center of Cloud Computing and Big Data Guilin University of Electronic Technology Guilin541004 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. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Object detection

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cloud-Assisted Privacy Protection for data Retrieval Against Keyword Guessing Attacks 3rd

Cloud-Assisted Privacy Protection for Data Retrieval Against...

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3rd International Conference on Machine Learning for Cyber Security, ML4CS 2020

作者： Chen, Zhenwei Zhang, Yinghui Han, Gang He, Jiangyong Guo, Rui Zheng, Dong School of Cyberspace Security Xi’an University of Posts and Telecommunications Xi’an710121 China National Engineering Laboratory for Wireless Security Xi’an University of Posts and Telecommunications Xi’an710121 China Westone Cryptologic Research Center Beijing100070 China Guangxi Cooperative Innovation Center of Cloud Computing and Big Data Guilin University of Electronic Technology Guilin541004 China

ISBN: (纸本)9783030622220

Machine learning is more closely linked to data privacy and has obtained rapid development in recent years. As for data privacy, searchable encryption (SE) is widely used as a ciphertext search technology, protecting the privacy of users. However, existing schemes usually support single keyword search, so the remote cloud server (CS) may return some irrelevant results. To address this problem, we propose a server-aided public key encryption scheme with multi-keyword search (SA-PEMKS) scheme. The scheme allows a data user to conduct multiple keyword search in a single search query. Security and performance analysis show that the SA-PEMKS scheme is secure and efficient. © 2020, Springer Nature Switzerland AG.

关键词： data privacy

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A Stepwise Path Selection Scheme Based on Multiple QoS Parameters Evaluation in SDN 17th

A Stepwise Path Selection Scheme Based on Multiple QoS Param...

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17th EAI International Conference on Collaborative computing: Networking, Applications, and Worksharing, CollaborateCom 2021

作者： Liu, Lin Zhou, Jian-Tao Xing, Hai-Feng Guo, Xiao-Yong College of Computer Science Ecological Big Data Engineering Research Center of the Ministry of Education Cloud Computing and Service Software Engineering Laboratory of Inner Mongolia Autonomous Region National and Local Joint Engineering Research Center of Intelligent Information Processing Technology for Mongolian Social Computing and Data Processing Key Laboratory of Inner Mongolia Autonomous Region Big Data Analysis Technology Engineering Research Center of Inner Mongolia Autonomous Region Inner Mongolia University Inner Mongolia Hohhot China College of Computer Science and Technology Inner Mongolia Normal University Inner Mongolia Hohhot China College of Computer Information and Management Inner Mongolia University of Finance and Economics Inner Mongolia Hohhot China

ISBN: (纸本)9783030926342

Nowadays, the best-effort service can not guarantee the quality of service (QoS) for all kinds of services. QoS routing is an important method to guarantee QoS requirements. It involves path selection for flows based on the current network status and the performance criteria of the service requirements. However, it is difficult for proposed solutions to obtain all the available paths owing to not fully considering all the QoS parameters of paths. In this paper, we propose SWQoS, a novel, universal, and stepwise QoS guarantee scheme based on multiple QoS parameter evaluation for selecting the available paths including preferred paths, satisfied paths and reluctant paths in SDN. The experiments show that SWQoS can select all the available paths that meet the performance criteria of the service requirements and have better QoS parameter performance compared with other path selection methods. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Quality of service

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Secure searchable encryption:a survey

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Journal of Communications and Information Networks 2016年第4期1卷 52-65页

作者： WANG Yunling WANG Jianfeng CHEN Xiaofeng State Key Laboratory of Integrated Service Networks(ISN) Xidian UniversityXian 710071China Guangxi Cooperative Innovation Center of Cloud Computing and Big Data Guilin University of Electronic TechnologyGuilin 541004China

cloud computing facilitates convenient and on-demand network access to a centralized pool of ***,many users prefer to outsource data to the cloud in order to mitigate the burden of local ***,storing sensitive data on remote servers poses privacy challenges and is currently a source of ***(Searchable Encryption)is a positive way to protect users sensitive data,while preserving search ability on the server *** allows the server to search encrypted data without leaking information in plaintext *** two main branches of SE are SSE(Searchable Symmetric Encryption)and PEKS(Public key Encryption with Keyword Search).SSE allows only private key holders to produce ciphertexts and to create trapdoors for search,whereas PEKS enables a number of users who know the public key to produce ciphertexts but allows only the private key holder to create *** article surveys the two main techniques of SE:SSE and *** SE schemes are categorized and compared in terms of functionality,efficiency,and ***,we point out some valuable directions for future work on SE schemes.

关键词： cloud storage encrypted data searchable encryption searchable symmetric encryption public key encryption with keyword search.

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Discovering All-chain Set with Direction and Graduality Characteristics over Streaming Time Series

Discovering All-chain Set with Direction and Graduality Char...

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Symposia and Workshops on Ubiquitous, Autonomic and Trusted computing, UIC-ATC

作者： Shaopeng Wang Chunkai Feng Department of Software Engineering Engineering Research Center of Ecological Big Data Ministry of Education Inner Mongolia Engineering Laboratory for Cloud Computing and Service Inner Mongolia discipline inspection and supervision big data laboratory Inner Mongolia University Hohhot China

Since its introduction over five years ago, time series chain has become a fundamental tool for time series analytics, finding diverse uses in dozens of domains. Recent work has generalized the definition of time series chain, and introduced a novel definition of time series chain with directionality and graduality characteristics (TSC-DG) which can significantly enhance both robustness and usability of the original time series chain. However, previous studies on TSCDG process fixed-length time series. In this work, we focus on the issue of all-chain set with direction and graduality characteristics (all-TSCS-DG) mining over streaming time series for the first time, where all-TSCS-DG is the core of current TSCDG researches. We propose an improved Naive algorithm (IN) to solve this problem. Compared to the Naive, the IN guarantees the same space costs and results firstly, secondly is the IN takes two additional optimal strategies to further improve the time efficiency. The basic ideas of these two strategies are both incremental computing. The first one can make the IN update the IB structure at each time-tick incrementally, where the IB is an important data structure that is used to obtain the all-TSCS-DG. The second one makes the IN obtain mining results at current time-tick based on the ones at the last time-tick incrementally. Extensive experiments on real dataset demonstrate the efficiency and effectiveness of the IN.

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Research on Blockchain-based Decentralized Federated Learning

Research on Blockchain-based Decentralized Federated Learnin...

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International Conference on Computer Applications Technology (ICCAT)

作者： Boyuan Han Zhihong Liang Mingming Qin Rongxin Jiang Wei Dai School of Big Data and Intelligent Engineering Southwest Forestry University Kunming China Big Data and Cloud Computing Center Southwest Forestry University Kunming China Yunnan Pu'er Technical School Yunnan Pu'er Technical School Kunming China

The integration of blockchain and federated learning exhibits a highly synergistic relationship. Blockchain, with its assurance of trustworthiness in computational processes and data, combined with federated learning's ability to make data available yet invisible, mutually complement each other and have shown initial advancements across various domains. Consequently, research and analysis of blockchain-based federated learning technology have garnered considerable *** blockchain enhances the federated learning process, it also poses a number of problems, such as increased communication overhead and lack of computational *** article aims to provide a comprehensive examination of the subject. Firstly, it introduces the fundamental concept of federated learning technology, along with privacy protection techniques and the existing threat landscape. Secondly, it analyzes the core principles of blockchain-based federated learning technology, delving into current research status, progress, and outlining the various research directions involved. Furthermore, it conducts an in-depth analysis and summarization of the integration between federated learning and blockchain technology, identifying numerous challenges that need to be addressed within the relevant domains. Finally, it recognizes and analyzes the future development of this combination, emphasizing the need to overcome existing *** summary, this article highlights the amalgamation of federated learning and blockchain technology. It identifies and analyzes the many challenges that require resolution within the pertinent fields, while also offering insights into the future development of this integration.

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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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