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E-Learning system architecture for cloud computing - A review 3

E-Learning system architecture for cloud computing - A revie...

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3rd international conference on Contemporary computing and Informatics, IC3I 2018

作者： Lone, Zahoor Ahmad Chawla, Priyanka Rana, Ajay Lovely Professional University School of Computer Science and Engineering Jalandhar India Amity University School of Computer Science and Engineering Noida India

ISBN: (纸本)9781538668948

The recent past has witnessed the e-learning systems gaining more popularity in view of the technological development in support of e-learning and the number of heterogeneous devices connected with such systems. The field of education has already been affected by the infiltration of digital technology connected with the forecast of internet of Things (IoT) foreseeing approximately fifty billion heterogeneous smart devices to be active by 2020. Cloud computing has a tremendous potential and has attracted educational sector for delivery of educational contents in an economical, secure and reliable way. Today's cloud architecture is composed of distributed computing, grid computing, virtualization technologies and its architecture makes available a flexible execution environments in which different resources can be linked to application and platform components. The continuity of architecture is its capability make alterations in itself and at the same time to retain the strength of objectives and this feature of a cloud system has an impact on the economic withstanding. This ability of cloud systems help in maintaining the technical sustainability. The introduction of Fog computing adds value to this scenario. The interconnection of such a huge number of smart electronic devices is expected to generate large amount of data which sometimes be analyzed in real time. This adds new type of big data and could be called as educational big data. The data generated by different sources such as study material, tests etc. needs well defined mining and analysis techniques in order to get time bound accurate information. The present paper reviews the current state of cloud based e-learning systems, compares the available cloud based e-learning architecture with the aim to enhancing the ability of cloud based e-learning architecture in view of present technologies like internet of Things (IoT), Fog computing(FC) and Big Data Streams. © 2018 IEEE.

关键词： E-learning

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Design of distributed Task Scheduling in East China Power Market Trading System

Design of Distributed Task Scheduling in East China Power Ma...

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China international Electrical and Energy conference (CIEEC)

作者： XiaRgang Li Ping Shao Lin Cheng Min Wu Yuanrui Hong East China Branch Of State Grid Corporation Of China Shanghai China China Electric Power Research Institute Beijing China

ISBN: (数字)9781728116754

ISBN: (纸本)9781728116761

With the advancement of power reform, the scale of inter-provincial power trading in the East China region has been increasing, the scale of transactions has been expanding. More and more parameters are being considered, and the calculation processing logic is more and more complicated. In order to cope with the situation that the market rules change too fast and the complexity is too high, the East China Power Trading System will introduce a distributed technology architecture based on cloud computing and microservices. However, this process from the single-element architecture to the distributed architecture puts higher demands on the multi-task scheduling processing mechanism of the system. Based on the analysis of East China Power Market Trading Business and East China Power Market Trading System, this paper proposes a task scheduling solution based on distributed control strategy with reference to the solution ideas of the internet industry. It solves the scheduling problem of mutual exclusion tasks by using the improved Leader election method and effectively avoids the brain crack problem of the Leader election. Based on this distributed task processing strategy, this paper further elaborates the corresponding engineering solutions. It includes the specific implementation contents of task management interface, task scheduling center, task scheduling client and abnormal monitoring function in East China Power Market Trading System, so as to facilitate the practical application of system design and development personnel in system construction. In addition, the program also proved the feasibility of the program through stress testing and application practice.

关键词： power market trading system task scheduling distributed system TASK SCHEDULING power markets distributed Systems Mechanical systems

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Intel Optane™ technology as Differentiator for internet of Everything and Fog computing

Intel Optane™ Technology as Differentiator for Internet of ...

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3rd international conference on Fog and Mobile Edge computing (FMEC)

作者： Elie, Etienne Intel Corp Santa Clara CA 95051 USA

ISBN: (纸本)9781538658963

Traditional network and cloud solutions cannot address effectively the infrastructure and data architecture challenges introduced by the emergence of the internet of Everything (IoE). IoE creates unprecedented volume of complex data which must be stored, transferred, processed and analyzed in real time for time sensitive applications. Indeed, most of the applications in IoE domain (autonomous driving, health monitoring, banking, industrial control systems ...) are time and quality of service sensitive and need new solutions for data integrity and data availability for successful decision. At Intel, we are working on new computer paradigm and storage technologies such as Intel® Optane™ SSDs and Intel® 3D NAND SSDs that can address some of these challenges. With Intel® Optane™, it is now possible to create a high performance and real time available Software-Defined Infrastructure (SDI) by enabling full dis-aggregate and pool of the underlying hardware resources, creating distributed memory/storage imperatives and giving research community and enterprise the performance and capabilities to benefit from revolutionary technologies such as Fog computing and Artificial Intelligence by dynamically assigning compute, storage and network resource in real-time time sensitive workloads. In this keynote, we will discuss data storage, availability, integrity, quality of service and movement in this compute paradigm shift. We will also touch on how it impacts mobile edge, fog computing and cloud infrastructures. We will then conclude with the challenges and opportunities this new solution will bring.

关键词： Edge computing Computer architecture Real-time systems internet of Things Cloud computing Quality of service

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FPGA hardware implementation of smart home autonomous system based on deep learning 3rd

FPGA hardware implementation of smart home autonomous system...

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3rd international conference on internet of Things, ICIOT 2018 Held as Part of the Services conference Federation, SCF 2018

作者： Alhafidh, Basman M. Hasan Daood, Amar I. Alawad, Mohammed M. Allen, William Department of Electrical and Computer Engineering Florida Institute of Technology MelbourneFL United States Department of Computer Sciences and Cybersecurity Florida Institute of Technology MelbourneFL United States Department of Electrical and Computer Engineering University of Mosul Mosul Iraq Biomedical Sciences Engineering and Computing Group Oak Ridge National Laboratory Oak RidgeTN United States

ISBN: (纸本)9783319943695

The use of deep learning algorithms, as a core element of artificial intelligence, has attracted increased attention from industrial and academic institutes recently. One important use of deep learning is to predict the next user action inside an intelligent home environment that is based on internet of Things (IoT). Recent researcher discusses the benefit of using deep learning based on different datasets to assist their result. However, assuring the best performance to satisfy real-time applications leads us to use a real-world dataset to make sure that the designed system meets the requirements of real-time applications. This paper uses the MavPad dataset which was gathered from distributed sensors and actuators in a real-world environment. The authors use simulation to investigate the performance of a multilayer neural network that predicts future human actions. The authors also present a hardware implementation of the deep learning model on an FPGA. The results showed that the hardware implementation demonstrated similar accuracy with significantly improved performance compared to the software-based implementation due to the exploitation of parallel computing and using optimization techniques to map the designed system into the target device. Additionally, our implementation of FPGA-based neural network system supports its future utilization for other applications. © Springer international Publishing AG, part of Springer Nature 2018.

关键词： internet of things

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A component-based modeling of edge systems computing 3

A component-based modeling of edge systems computing

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3rd international conference on Advanced Aspects of Software Engineering, ICAASE 2018

作者： Sehout, O.N. Ghiat, M. Benzadri, Z. Belala, F. University of Constantine2-Abdelhamid Mehri Faculty of NTIC Algeria LIRE Laboratory University of Constantine2-Abdelhamid Mehri Algeria

internet of Things (IoT) aims to bring every object, such as smart cameras, wearable devices, etc., online, hence generating massive amounts of data that can submerge storage systems. The Cloud computing paradigm is unable to meet these requirements, particularly in some critical applications (as health monitoring, emergency response, etc.) that require low latency, and delay caused by transferring data to the cloud and then back to the application can seriously impact their performances. To overcome this limitation, Edge paradigms, as Fog computing, Edge computing and Mobile Cloud computing, have been proposed, where cloud services are extended to the edge of the network to decrease the latency and network congestion. This paper proposes a software architecture supporting the modelling of Edge computing dedicated systems. The current situation of emerging Edge paradigms is analyzed in detail. An approach based on software component technology is proposed and applied using Fractal components model, which can specify semantics of every-changing dynamic and distributed integration of software components. Furthermore, a case study of the patient monitoring system (PMS-EDGE) along with its application model and network topology is expounded. Copyright © by the paper’s authors.

关键词： Edge computing

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Artificial intelligence platform for heterogeneous computing 3rd

Artificial intelligence platform for heterogeneous computing

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3rd international conference on Smart computing and Communications, SmartCom 2018

作者： Zhang, Haikuo Lu, Zhonghua Xu, Ke Pang, Yuchen Liu, Fang Chen, Liandong Wang, Jue Computer Network Information Center Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China China Internet Network Information Center Beijing100190 China University of Illinois at Urbana-Champaign ChampaignIL61820 United States State Grid Hebei Electric Power Company ShijiazhuangHebei050022 China

ISBN: (纸本)9783030057541

Since the birth of artificial intelligence, the theory and the technology have become more mature, and the application field is expanding. In this paper, we build an artificial intelligence platform for heterogeneous computing, which supports deep learning frameworks such as TensorFlow and Caffe. We describe the overall architecture of the AI platform for a GPU cluster. In the GPU cluster, based on the scheduling layer, we propose Yarn by the Slurm scheduler to not only improve the distributed TensorFlow plug-in for the Slurm scheduling layer but also to extend YARN to manage and schedule GPUs. The front-end of the high-performance AI platform has the attributes of availability, scalability and efficiency. Finally, we verify the convenience, scalability, and effectiveness of the AI platform by comparing the performance of single-chip and distributed versions for the TensorFlow, Caffe and YARN systems. © 2018, Springer Nature Switzerland AG.

关键词： Scalability

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A Scalable Agent-Based Smart Environment for Edge-Based Urban IoT Systems 3rd

A Scalable Agent-Based Smart Environment for Edge-Based Urba...

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3rd international conference on Interoperability in IoT, InterIoT 2017 on conjunction with 4th international conference on Safety and Security in internet of Things, SaSeIoT 2017

作者： Cicirelli, Franco Fortino, Giancarlo Guerrieri, Antonio Spezzano, Giandomenico Vinci, Andrea Via P. Bucci 7-11C RendeCS87036 Italy Department of Informatics Modeling Electronics and Systems University of Calabria Rende87036 Italy

ISBN: (纸本)9783319937960

New internet of Things (IoT) applications are encouraging Smart City and Smart Environments initiatives all over the world, by leveraging big data and ubiquitous connectivity. This new technology enables systems to monitor, manage and control devices, and to create new knowledge and actionable information, by the real-time analysis of data streams. In order to develop applications in the depicted scenario, the adoption of new paradigms is required. This paper suggests combining the emergent concept of edge/fog computing with the agent metaphor, so as to enable designing systems based on the decentralization of control functions over distributed autonomous and cooperative entities, which run at the edge of the network. Moreover, we suggest the adoption of the iSapiens platform as a reference, as it was designed specifically for the mentioned purposes. Multi-agent applications running on top of iSapiens can create smart services using adaptive and decentralized algorithms which exploit the principles of cognitive IoT. © 2018, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： internet of things

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Research on information security technology based on blockchain

Research on information security technology based on blockch...

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IEEE international conference on Cloud computing and Big Data Analysis (ICCCBDA)

作者： Liang Liu Budong Xu Shandong Normal University Jinan China

Information security is the key to the development of modern internet technology. The distributed mechanism, decentralized mechanism, password mechanism and scripted mechanism of the Blockchain present a completely new perspective for the development of internet information security technology. The Blockchain technology redefines the storage and dissemination methods of the information in the network. Neither participant needs to know each other, and nor does it require third-party certification bodies to participate. It records, transmits and stores transferring activities of the information value by distributed technology, ensures that data is not tampered and forged based on an asymmetric cryptographic algorithm, enables all participants reached a consensus on the status of blockchain data information. And from the current industry research on blockchain technology, it expounds the application of blockchain technology in identity authentication, data protection and network security. The Blockchain technology will be a great driving force in the process of information security technology change, and will have a far-reaching impact on the expansion of information security.

关键词： Peer-to-peer computing Authentication distributed databases

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An information divergence based approach to detect flooding DDoS attacks and Flash Crowds 3

An information divergence based approach to detect flooding ...

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3rd international conference on Applied and Theoretical computing and Communication technology (iCATccT)

作者： Kaur, Gursharanjeet Behal, Sunny Shifali SBS State Technical Campus Ferozepur Punjab India Ferozepur College of Engineering and Technology Ferozepur Punjab India

ISBN: (纸本)9781538611449

distributed Denial of Service (DDoS) attacks poses a severe threat to widely used internet-based services and applications. Currently, during in the technology era, the internet is the only real exigent that delivers a glut of services like businesses, banking, communication, education, e-commerce, etc. distributed Denial of Service attack aims to deny access by legitimate users to shared services or resources. Because of the vulnerability of the initial style of the web, attackers can merely mimic the patterns of legitimate network traffic. The prevailing fingerprint or feature-based methods are not appropriate to detect a recent DDoS attack. In this paper our goal is to detect a DDoS attack as well as Flash Crowd using various information distance measures such as Kullbeck-Leibler, Hellinger and Manhattan distance to measure the flow similarity among the traffic. Further the detection parameters such as Detection Rate, Classification Rate, Precision Rate and False Positive Rate is computed and shows that the Kullbeck-Leibler detection metric effectively detects the attack as compared to the other two.

关键词： DDoS attack Flash crowd distance measurement Flow similarity

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Application Research Of Hadoop's Weibo Recommendation System Prototype Based On Customer Dynamic Behavior

Application Research Of Hadoop's Weibo Recommendation System...

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international conference on Smart City and Systems Engineering

作者： Guo Wei-wei Liu Feng Heilongjiang University of Technology JiXi China

ISBN: (纸本)9781728113678;9781728113661

In order to find out the relationship between customer's behavior and customer's focus, analyze the dynamics of recommendation system and dynamic recommendation model based on customer behavior, this paper adopt Hadoop's Weibo recommendation system to classify customer behavior, focus on analyzing and researching the current main internet behaviors, and work out the specific forms of prototype system and main parts of the system, and analyze the specific functions of each module, According to the practice, content and location of micro-blog users, A hierarchical prototype model is established, and the information recommendation is realized through similarity calculation. The results show that the characteristics of high-quality distributed storage system and distributed computing capabilities with speed of Hadoop, which gives customers an access to recommendation of Weibo and friend services in time, realizing the ability to recommend friends to customers, and verifying the system through relevant tests.

关键词： Cloud computing distributed databases Computational modeling Parallel processing Heuristic algorithms Prototypes

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