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检索条件"任意字段=13th International Conference on Distributed Computing and Internet Technology, ICDCIT 2017"

共 228 条记录，以下是51-60 订阅

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Research on the Privacy Security and Defense Strategies on the internet of things Platform

Research on the Privacy Security and Defense Strategies on t...

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international conference on Cyber Security Intelligence and Analytics (CSIA)

作者： Bian, Qian Wang, Zhenduo Wang, Yingqiang Zhang, Weigang Xian Siyuan Univ Sch Telecommun Xian 710038 Shaanxi Peoples R China Changan Univ Xian 710064 Shaanxi Peoples R China

ISBN: (纸本)9783030152352;9783030152345

With the maturity and development of the internet of things technology, some security and privacy protection issues have emerged slowly. At present, various networks such as the mobile communication network, the wireless sensor network and some terminal devices still have many technical shortcomings, and the privacy security of objects is also threatened. therefore, this paper takes the security and privacy protection of the internet of things as the research direction, and analyzes the privacy protection model technologies and methods of the internet of things.

关键词： internet of things platform Privacy security Defense strategy New technology

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A distributed DBSCAN Algorithm for Massive Data in Cyber Physical and Social computing 13

A Distributed DBSCAN Algorithm for Massive Data in Cyber Phy...

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2020 IEEE Congress on Cybermatics: 13th IEEE international conferences on internet of things, ithings 2020, 16th IEEE international conference on Green computing and Communications, GreenCom 2020, 13th IEEE international conference on Cyber, Physical and Social computing, CPSCom 2020 and 6th IEEE international conference on Smart Data, SmartData 2020

作者： Zhang, Wei Chen, Xiaohui Sun, Jiajun Xi, Qian Computer Science and Technology Huaiyin Normal University Huai'an223300 China

ISBN: (纸本)9781728176475

Density-based Spatial Clustering of Applications with Noise (called DBSCAN) finds clusters of various shapes and is not affected by noise, so it is widely used in the field of data mining. In Cyber Physical and Social computing, massive data needs to be analyzed and processed, and the standard linear DBSCAN algorithm is difficult to effectively apply to the processing of massive datasets. In order to employ the DBSCAN algorithm to process massive datasets, this paper proposes a distributed DBSCAN algorithm (called D-DBSCAN). the following works are implemented in the D-DBSCAN algorithm: First, the dataset is stored on multiple storage nodes in a distributed manner to handle massive datasets. Second, a local Eps-neighbors search is performed on the storage nodes to achieve parallel processing of massive data. Finally, the data returned by the storage and compute nodes are merged to obtain a global Eps-neighbors result. In the experimental part, a series of different simulated datasets was used to verify the effectiveness of the D-DBSCAN algorithm. the experimental results show that the D-DBSCAN algorithm based on distributed storage and computation effectively improves the ability and scalability of the DBSCAN algorithm to process massive data. the D-DBSCAN algorithm can be easily deployed in cloud-edge computing environments to handle massive amounts of data in Cyber Physical and Social computing. © 2020 IEEE.

关键词： Metadata

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computing Service Scheme with Idle Virtual Machine Based on OpenStack 13th

Computing Service Scheme with Idle Virtual Machine Based on ...

引用

13th international conference on Multimedia and Ubiquitous Engineering (MUE) / 14th international conference on Future Information technology (Future Tech)

作者： Jeon, Jueun Kim, Seungchul Yu, Gisung Kim, Hyun-Woo Jeong, Young-Sik Dongguk Univ Dept Multimedia Engn Seoul South Korea Baewha Womens Univ Dept Informat Secur Seoul South Korea

ISBN: (纸本)9789813292444;9789813292437

Virtual machine provides cloud computing services that offer computing resources to users through the internet based on virtualization technology. Generally, supercomputing or grid computing has been used to process a large scale job in scientific, technology, and engineering application problems. Currently, services for large scale parallel processing through idle virtual machines in cloud computing are not provided. Previously, the utilization rate of computing resources in cloud computing was low when users do not use virtual machines anymore or for a long period of time since all the rights in relation to the use of virtual machine are given to users. this study proposes a scheme that increase resource utilization of idle virtual machines and process a large scale job through the idle virtual machines. Basically, idle virtual machines are identified based on virtual machines created through OpenStack, and idle virtual machine-computing service (IVM-CS) is proposed.

关键词： Cloud computing service OpenStack Virtual machine computing resource distributed computing

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Computation Offloading and Content Caching with Traffic Flow Prediction for internet of Vehicles in Edge computing 13

Computation Offloading and Content Caching with Traffic Flow...

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13th IEEE international conference on Services computing (SCC) / 13th IEEE international conference on Web Services (ICWS)

作者： Fang, Zijie Xu, Xiaolong Dai, Fei Qi, Lianyong Zhang, Xuyun Dou, Wanchun Nanjing Univ Informat Sci & Technol Sch Comp & Software Nanjing Peoples R China Southwest Forestry Univ Sch Big Data & Intelligence Engn Kunming Yunnan Peoples R China Qufu Normal Univ Sch Informat Sci & Engn Qufu Shandong Peoples R China Macquarie Univ Dept Comp N Ryde NSW Australia Nanjing Univ State Key Lab Novel Software Technol Nanjing Peoples R China

ISBN: (纸本)9781728187860

the development of the internet of Vehicles (IoV) enables numerous emerging in-vehicle applications to accommodate users with various contents, thus enhancing their traveling experiences. In IoV, content decoding tasks are typically offloaded to edge servers for implementation, as edge computing is an admirable paradigm to provide low-latency services. However, as different vehicular users may request the same contents, processing these contents repeatedly leads to the waste of storage, computation and bandwidth resources. therefore, fine-grained computation offloading and content caching are demanded in IoV. In this paper, a joint optimization method for computation offloading and content caching based on traffic flow prediction, named COC, is proposed. Firstly, traffic flow covered by each edge server is predicted by a modified deep spatiotemporal residual network (ST-ResNet). Secondly, the non-dominated sorting genetic algorithm III (NSGA-III) is leveraged to realize the many-objective optimization to shorten the execution time and reduce the energy consumption of computation and transmission in IoV. Finally, evaluated by real-world big data from Nanjing China, COC shows a great reduction in execution time and energy consumption of transmission and computation compared to other methods.

关键词： computation offloading content caching edge computing IoV traffic flow prediction

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Peer-to-Peer Based Web of things Resource Management 13th

Peer-to-Peer Based Web of Things Resource Management

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13th international conference on Complex, Intelligent, and Software Intensive Systems (CISIS)

作者： Li, Yangqun Nanjing Univ Posts & Telecommun Jiangsu Key Lab Broadband Wireless Commun & Inter Nanjing 210003 Peoples R China Nanjing Univ Posts & Telecommun Sch Internet Things Nanjing 210003 Peoples R China

ISBN: (纸本)9783030223540;9783030223533

More and more devices provide resources and services under the environment of internet of things (IoT). the location-based P2P distributed computing technology is adopted to implement the effective management of the Web of things (WoT) resources, satisfying reliability, robustness and flexibility of the system. In order to effectively implement resource lookup in the context of massive resources, the probabilistic topic model is used to model IoT resource description and then the resulting topic model and geolocations are used as resource ID for resource storage and resource discovery, realizing distributed management of resources. And on this basis, the ROA style life cycle management for WoT resources under the P2P environment is provided. Finally, the feasibility of the system is proved by simulation experiments.

关键词： internet of things

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A Semantic Web Service Oriented Middleware Framework for internet of things 13

A Semantic Web Service Oriented Middleware Framework for Int...

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13th international conference on Intelligent Computation technology and Automation, ICICTA 2020

作者： Lian, Mengjia Yang, Dongsheng Yin, Zhenyu Liu, Jingyu Li, Mingshi Chai, Anying University of Chinese Academy of Sciences Beijing100049 China Shenyang Institute of Computing Technology Chinese Academy of Sciences Shenyang110168 China

ISBN: (纸本)9781728186665

With the continuous access of a large number of diverse devices in the internet of things, the scope of application areas is gradually expanding. In order to solve the problem of heterogeneity and scale of device entities and data in the internet of things, the paper combines web services and semantic technology to build an internet of things middleware oriented to semantic web services. the middleware is mainly to serve the internet of things resources and data semantics, and shields the differences by using the standardized and unified description of the ontology model. Pub/sub communication is used to improve the efficiency of massive data distribution, and through a series of operations such as service registration, discovery and composition, combined with the quality of service to select the most appropriate service for the application to complete user demands. Finally, semantic reasoning can be carried out according to knowledge rules to improve the application of the internet of things, making it more intelligent. © 2020 IEEE.

关键词： Middleware

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An Auction-Based Incentive Mechanism with Blockchain for IoT Collaboration 13

An Auction-Based Incentive Mechanism with Blockchain for IoT...

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13th IEEE international conference on Services computing (SCC) / 13th IEEE international conference on Web Services (ICWS)

作者： Cheng, Guanjie Deng, Shuiguang Xiang, Zhengzhe Chen, Yan Yin, Jianwei Zhejiang Univ Coll Comp Sci & Technol Hangzhou Peoples R China

ISBN: (纸本)9781728187860

the prosperous development of IoT has created tremendous opportunities to improve people's lives. Essentially, the core property of the IoT applications is the ability to perform collaborative tasks with data supplied by separate IoT managers. However, the fulfillment of collaborative tasks is driven by the participations of the IoT managers. Generally, the willingness can be activated with appropriate profit (or incentive cost). thus, an efficient incentive mechanism is needed to motivate the IoT managers to participate in the collaboration. In this paper, we present a reverse auctionbased incentive mechanism with the goal of minimizing and stabilizing incentive costs while maintaining adequate participants. To prevent the incentive cost explosion, a droppers recruiting scheme is leveraged to attract the inactive participants. A price verification strategy is designed to avoid bid cheating. Furthermore, we introduce blockchain to orchestrate the interactions between collaborative parties, so as to protect their privacy. Finally, we show the feasibility and efficiency of our proposed framework with simulation experiments and theoretical analysis.

关键词： internet of things (IoT) incentive mechanism blockchain smart contracts auction mechanism

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Research and Design of Square Kilometer Array Astronomical Data Management Model Based on Fabric 13

Research and Design of Square Kilometer Array Astronomical D...

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作者： Fu, Jinhua Xu, Jie Zhang, Shulin Zhang, Chen State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou University of Light Industry Zhengzhou China Zhengzhou University of Light Industry Zhengzhou China Qinghai University Department of Computer Technology and Applications Xining China

ISBN: (纸本)9781728176475

At present, how to safely share data among different participants has become a huge challenge. the reliable traceability of SKA data is a powerful technical tool for controlling its security and sharing. In order to solve the problem of high management cost and low data credibility of traditional centralized big data management system, SKA data management and credible traceability model design based on Hyperledger Fabric were studied. In this paper, the overall framework and architecture of SKA data management are studied and designed, and the key technologies such as big data storage scheme, big data transmission, big data processing, blockchain metadata storage, alliance chain member allocation, traceability query, contribution mechanism and data sharing are discussed. distributed architecture, Hyperledger Fabric alliance chain technology, database technology, Golang network programming, Rust asynchronous programming, Java Web and *** are comprehensively adopted. the functions of SKA data transmission, processing, storage, traceability query and data sharing are designed. the functions of transmission, processing, storage, management, sharing and credible traceability of SKA data management system are realized, which provides a reference for the design and implementation of SKA data management system based on blockchain. © 2020 IEEE.

关键词： Metadata

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Multi-objective Cross-layer Resource Scheduling for internet of things in Edge-Cloud computing 13

Multi-objective Cross-layer Resource Scheduling for Internet...

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IEEE 13th international conference on Cloud computing (CLOUD)

作者： Mo, Ruichao Dai, Fei Liu, Qi Dou, Wanchun Xu, Xiaolong Nanjing Univ Informat Sci & Technol Sch Comp & Software Nanjing Peoples R China Southwest Forestry Univ Sch Big Data & Intelligence Engn Kunming Yunnan Peoples R China Nanjing Univ State Key Lab Novel Software Technol Nanjing Peoples R China

ISBN: (纸本)9781728187808

Nowadays, Edge computing is being introduced as a powerful paradigm to collaborate with the cloud to provide sufficient computing resources for IoT to implement intelligent analysis and data mining. Generally, due to the edge nodes are closer to mobile users, the access latency and the cost of using cloud services are effectively reduced. However, the implementation of cross-layer resource scheduling between edge nodes and servers deployed in the cloud to meet service requirements (i.e., shortest completion time, maximum resource utilization, lower energy consumption, etc.) still faces great challenges. To address this challenge, a cross-layer resource scheduling method, named CRSM, for the IoT applications is proposed in this paper. Technically, the Pareto archived evolution strategy (PAES) is employed to optimize the time cost of IoT applications, resource utilization and energy consumption of edge node. then, the technique for order preference by similarity to ideal solution (TOPSIS) and the multiple criteria decision making (MCDM) are leveraged to acquired the optimal cross-layer resource scheduling strategy. Finally, the comprehensive analysis of CRSM is introduced in detail.

关键词： Edge-cloud computing Cross-layer IoT Resource scheduling PAES

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Robust Speaker Identification of IoT based on Stacked Sparse Denoising Auto-encoders 13

Robust Speaker Identification of IoT based on Stacked Sparse...

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作者： Wang, Zhifeng Duan, Surong Zeng, Chunyan Yu, Xinguo Yang, Yang Wu, Helin Hubei Research Center for Educational Informationization Central China Normal University Wuhan China CCNU Wollongong Joint Institute Central China Normal University Wuhan China Hubei Key Laboratory for High-efficiency Utilization of Solar Energy Operation Control of Energy Storage System Hubei University of Technology Wuhan China

ISBN: (纸本)9781728176475

Robust speaker identification of internet of things (IoT) becomes an active research problem in the field of biometrics, and it has wide applications in commercial fields and public security. In order to improve the robustness of speaker identification of IoT, we propose a novel Stacked Sparse Denoising Auto-encoder (SSDAE) for robust speaker identification in this paper. Firstly, the i-vector features are estimated based on the universal background model and total variability space model. For the second stage, sparsity constraints and corrupting operations are fused together into the general auto-encoder, and then the single sparse denoising auto-encoder is constructed. then, the SSDAE is built with multi-hidden sparse denoising auto-encoder layers by layer wisely stacking operation. In the final layer of the designed deep neural network, the Softmax layer is included for classification purpose. the experimental results have shown that the proposed robust speaker identification method achieves better performance in robust speaker identification task than the state-of-the-art approaches for different kinds and levels of noisy inputs. © 2020 IEEE.

关键词： internet of things

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