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New Architecture Design of Cloud computing Using Software Defined Networking and Network Function Virtualization Technology 4th

New Architecture Design of Cloud Computing Using Software De...

引用

4th international conference of Reliable Information and Communication Technology (IRICT)

作者： Bahashwan, Abdullah Ahmed Anbar, Mohammed Abdullah, Nibras Univ Sains Malaysia USM Natl Adv IPv6 Ctr Nav6 Gelugor 11800 Penang Malaysia

ISBN: (纸本)9783030335823;9783030335816

Cloud computing is a new technology model that consists of a pool of configurable resource and multiple data centers in distributed areas. It offers a service over the internet for users using virtual data, and who share resources for storing and accessing data from anywhere. Cloud computing supports big-scale platforms that consist of thousands of servers and hundreds of switches. Currently, the cloud is suffering from many issues in term of management, security and other essential aspects. This paper discusses integrating Software Defined Networking (SDN), with Network Function Virtualization (NFV) based on cloud computing, to eliminate some of the existing security issues faced by cloud computing. This research paper proposes a new architecture design by taking advantage of the NFV technology to build a virtual security mechanism such as Network Intrusion Detection System (NIDS).

关键词： Software-defined networking (SDN) Network Function Virtualization (NFV) Based in Cloud computing

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An IoT Edge computing System Architecture and its Application

An IoT Edge Computing System Architecture and its Applicatio...

引用

2020 IEEE international conference on Networking, Sensing and Control, ICNSC 2020

作者： Chen, Shichao Li, Qijie Zhang, Hua Zhu, Fenghua Xiong, Gang Tang, Ying Macau University of Science and Technology State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences China Beijing University of Technology State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Beijing Aerospace Smart Manufacturing Technology Development Co. Ltd Platform Research and Development Department Beijing China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Engineering Research Center of Intelligent Systems and Technology Institute of Automation Cloud Computing Center Chinese Academy of Sciences Beijing China Rowan University Department of Electrical and Computer Engineering GlassboroNJ United States Institute of Smart Education Qingdao Academy of Intelligent Industries Qingdao China

ISBN: (纸本)9781728168531

As the number of devices connected to the Internet of things (IoT) surges, the amount of data explodes. Therefore it not only increases the bandwidth load of data transmission but also aggravates the computing and storage load of a cloud platform. At the same time, the traditional computing paradigm centered on cloud computing cannot meet the real-time requirements in many application scenarios. The emergence of edge computing can solve the problems of realtime data processing and network bandwidth occupation in the current IoT scene. In this paper, according to the characteristics of IoT, such as fragmented data, heterogeneous network, and limited energy consumption, the architecture of an IoT edge computing system is constructed to suit better an IoT scene. In addition, the application of edge computing key technologies such as virtualization, edge intelligence, computing offload, collaborative scheduling and micro-services in resource-constrained IoT scenarios is analyzed in detail. Finally, the functions and application of energy consumption monitoring and optimization to a central air-conditioning system are analyzed and summarized, which is a typical application of edge computing in the context of the IoT. © 2020 IEEE.

关键词： Edge computing

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Multitask Deep Learning for Edge Intelligence Video Surveillance System 18

Multitask Deep Learning for Edge Intelligence Video Surveill...

引用

18th IEEE international conference on Industrial Informatics (INDIN)

作者： Li, Jiawei Zheng, Zhilong Li, Yiming Ma, Rubao Xia, Shu-Tao Tsinghua Univ Tsinghua Shenzhen Int Grad Sch Shenzhen Peoples R China Tsinghua Univ Dept Comp Sci & Technol Beijing Peoples R China Bright Dream Robot Co Ltd Country Garden Grp Foshan Peoples R China Peng Cheng Lab PCL Res Ctr Networks & Commun Shenzhen Peoples R China

ISBN: (纸本)9781728149646

From the mutual empowerment of two high-speed development technologies: artificial intelligence and edge computing, we propose a tailored Edge intelligent Video Surveillance (EIVS) system. It is a scalable edge computing architecture and uses multitask deep learning for relevant computer vision tasks. Due to the potential application of different surveillance devices are widely different, we adopt a smart IoT module to normalize the video data of different cameras, thus the EIVS system can conveniently found proper data for a specific task. In addition, the deep learning models can be deployed at every EIVS nodes, to make computer vision tasks on the normalized data. Meanwhile, due to the training and deploying of deep learning model are usually separated, for the related tasks in the same scenario, we propose to collaboratively train the depth learning models in a multitask paradigm on the cloud server. The simulation results on the publicly available datasets show that the system continuously supports intelligent monitoring tasks, has good scalability, and can improve performance through multitask learning.

关键词： intelligent video surveillance system edge computing deep learning multitask learning

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Preserve Security to Medical Evidences using Blockchain Technology

Preserve Security to Medical Evidences using Blockchain Tech...

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international conference on intelligent computing and Control Systems (ICICCS)

作者： Rupa, Ch Midhunchakkaravarthy, Divya Lincoln Univ Coll Kota Baharu Kelantan Malaysia Lincoln Univ Coll Ctr Post Grad Studies Acad & Student Affairs Petaling Jaya Selangor Malaysia

ISBN: (纸本)9781728148762

Advanced privacy preservation approaches are used to be protecting sensitive and important data of various application areas like Communication systems, Healthcare, Education and Financial Sector. In the Healthcare area, the important and sensitive task is a medical certificate that acts as medical evidence of a person which helps for many purposes. Deception in issuance as well as in verification of medical certificates has existed for a long time in health care centers due to lack of reliable mechanisms. In the issue of medical evidence to a person, needs to consider a method which has advanced features like transparency, immutable, reliable and decentralized properties. Hence, in this paper, blockchain technology is used to design and develop a model with advanced features for reducing forgery in medical pieces of evidence. In this approach, a regulatory body will authorize the Health care centers (Hospitals) for issuing medical certificates to the required persons in a decentralized approach. Here smart contract system helps to verify the certificate authenticity from any authorized one in the world. The main strength of the paper gives the Blockchain-based model as a solution to the issue related to proof of a certificate of medical evidence.

关键词： Medical Evidence Blockchain smart Contract Regulatory Body Immutable transparency

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Easy-to-Deploy Living Activity Sensing System and data Collection in General Homes 18

Easy-to-Deploy Living Activity Sensing System and Data Colle...

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IEEE international conference on Pervasive computing and Communications (PerCom)

作者： Matsui, Tomokazu Onishi, Kosei Misaki, Shinya Fujimoto, Manato Suwa, Hirohiko Yasumoto, Keiichi Nara Inst Sci & Technol Ikoma Nara 6300192 Japan RIKEN Ctr Adv Intelligence Project Chuo Ku Tokyo 1030027 Japan

ISBN: (纸本)9781728147161

Emergence of smart appliances and high performance IoT devices is promoting studies on more functional and intelligent home services using these devices. Especially, in developed countries including Japan with aging population and declining birthrate, it is urgent to develop technologies to monitor living situations of residents including elderly persons and improve their quality of life (QoL) through home services based on the activity recognition technology. However, activity recognition systems in general require many types/number of sensors and hence they are difficult to deploy and operate. In this paper, we propose a system consisting of low-cost and easy-to-deploy sensors based on energy harvesting that can collect data of resident's activities of daily living (ADL) for months without maintenance. The system was deployed in 10 homes of senior citizens where we collected ADL data for two months each. We also estimated the ADLs from the collected data by using long short-term memory (LSTM), a deep learning model. As a result, ADLs could be estimated at high recall rate of 82.4% on average and hence we found that the proposed system has high applicability to actual services.

关键词： daily activity recognition IoT machine learning LSTM simple installation sensing system

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Effective information extraction algorithm of dynamic logistics big data based on SVM

Effective information extraction algorithm of dynamic logist...

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1st international conference on Big data analytics for Cyber-Physical System in smart City, BDCPS 2019

作者： Fan, Bixia Rao, Xin Hubei Business College Wuhan430079 China

ISBN: (纸本)9789811525674

With the advent of the era of big data, data plays a more and more important role. At the same time, the massive data also contains a variety of invalid information. The existing data information extraction methods do not perform well in dealing with this kind of data, which makes the results deviate greatly. To solve these problems, this paper proposes an efficient information extraction algorithm based on SVM for dynamic logistics big data. First of all, considering the unstructured characteristics of logistics dynamic big data, preprocessing data, including cleaning data, data specification and transformation, as well as data dimensionality reduction, to facilitate subsequent operations. Then, the approximate support vector regression function is used to mine the information features effectively. Through the simulation experiment, the results show that the accuracy of the proposed algorithm is about 82.3%, which is significantly higher than the other two algorithms. This shows that the method proposed in this paper has obvious effect on the effective information extraction of logistics big data. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Support vector machines

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Efficient Image Watercolorization Based on smart Phones

Efficient Image Watercolorization Based on Smart Phones

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2020 international conference on High Performance Big data and intelligent Systems, HPBD and IS 2020

作者： Zhang, Huijuan Xiao, Xuezhong School of Computer Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (纸本)9781728165110

Image watercolorization is a hot research topic in the field of non-photorealistic rendering. There are many methods proposed to simulate the various features of watercolor painting including edge darkening, pigment dispersion, turbulence, and paper texture. However, almost all of them are implemented for desktop systems and cannot be directly transplanted to mobile devices. From the view of resultant effects and computing efficiency, an image watercolorization framework is proposed for smart phones, which employs several existing image processing algorithms to simulate the visual features of watercolor painting. Finally, the method is optimized in parallel to improve the efficiency. The experiments show the presented method has good performance. © 2020 IEEE.

关键词： Efficiency

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An intelligent Dimming Algorithm of Streetlight Based on Fuzzy Neural Network 16

An Intelligent Dimming Algorithm of Streetlight Based on Fuz...

引用

16th IEEE international Wireless Communications and Mobile computing conference, IWCMC 2020

作者： Xue, Yunpeng Zhang, Yan Shuxue, Peng School of Electronics Information Engineering Beihang University Beijing100191 China

ISBN: (纸本)9781728131290

In recent years, the IoT(Internet of things) industry has developed rapidly. As an important part of the IoT, smart streetlights have been widely used in cities around the world. More and more smart streetlights are being deployed with NB-IoT(Narrow Band Internet of Things) or Lora, which bring great convenience to streetlights management. The existing system is limited to reporting sensor data and error information of streetlight, but still adopts the traditional methods in brightness control, such as all- brightness or half-brightness in midnight, which has some shortcomings such as insufficient data utilization and less intelligent dimming algorithm, resulting in the street lamp failing to achieve the expected energy-saving effect. In this paper, an intelligent dimming algorithm of streetlight based on fuzzy neural network is designed. Combining advantages of fuzzy control and neural network, the algorithm can analyze the road information uploaded by the sensing layer and output the dimming signal. The simulation results show that, compared with the traditional method, the algorithm is more energy efficient and more consistent with human eye habits. © 2020 IEEE.

关键词： Fuzzy neural networks

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Methods for implementing the concept of "smart City" based on Bayesian intelligent Technologies 23

Methods for implementing the concept of "Smart City" based o...

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23rd international conference on Soft computing and Measurement, SCM 2020

作者： Prokopchina, S.V. Department of System Analysis in Economics Financial University under the Government of the Russian Federation 49 Leningradsky Prospekt Moscow125993 Russia

Information systems based on Bayesian intelligent technologies make it possible to implement monitoring, control and management tools within the framework of the "smart City" concept. Such tasks are connected, on the one hand, with the processing of large arrays of various types of information, on the other hand, with difficult conditions for solving problems due to uncertainty. This article discusses the methodological aspects of the application of the regularizing Bayesian approach and Bayesian technologies focused on uncertainty and information processing both in the form of data and in the form of various knowledge. It is shown that such systems can be implemented in the form of intelligent cognitive networks with the processing of different types of measurement, statistical, reporting information, integrated with the assessments and decisions of experts and specialists. Examples of using the proposed approach and technologies for solving applied problems of digitalization of urban economy are given. © 2020 Institute of Physics Publishing. All rights reserved.

关键词： smart city

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Dynamic vulnerability detection approaches and tools: State of the Art 4

Dynamic vulnerability detection approaches and tools: State ...

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4th international conference on intelligent computing in data Sciences (ICDS)

作者： Zaazaa, Oualid El Bakkali, Hanan Mohammed V Univ Rabat IT Ctr ENSIAS Smart Syst Lab Rabat Morocco

ISBN: (纸本)9781728180847

Vulnerabilities are everywhere around us. Every device we use in our daily life include a software that may contain vulnerabilities. The growth use of software and devices to automate some of our daily life actions is making these programs more complex and more connected to the internet, which increase the risk of cyber-attacks. To reduce this risk, multiple programming companies are trying to use different approaches to find these vulnerabilities. Some are using static approaches during the software development life cycle while others are using dynamic analysis approaches to find vulnerabilities once the application is correctly working. Unfortunately, both approaches still suffer from multiple limitation and still need improvement. In this paper, we are discussing some of the most recent dynamic approaches and the efficient of the tools that use them.

关键词： Vulnerability detection Dynamic analysis artificial intelligence Symbolic execution

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