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A structure of intelligent grain network information platform based on cloud computing 17

A structure of intelligent grain network information platfor...

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2nd international conference on internet of things, Data and Cloud computing (ICC)

作者： He, Jianwei Zhang, Dexian Henan Univ Technol 100 Lianhua St Zhengzhou Peoples R China

ISBN: (纸本)9781450347747

The construction of intelligent grain network is an important part of the national grain protection, and information platform is an important foundation to support the construction of Intelligent Grain Network. In order to make full use of the computing resources, to meet the needs of reliable storage and efficient management of all the information, the information platform structure of intelligent grain network based on cloud computing is proposed. In this paper, the architecture of the platform is presented, and the feasibility, advantages and problems of the new method are analyzed. According to the characteristics of intelligent grain network state monitoring, combined with the Hadoop cloud computing technology, this paper proposes the solution of intelligent grain network monitoring cloud computing platform. Research on cloud computing virtualization, distributed storage and parallel programming model and other issues, can achieve reliable intelligent grain network mass information storage and fast parallel processing.

关键词： Cloud computing intelligent grain network virtualization distributed storage parallel processing

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Demo abstract: Fog computing for improving user application interaction and context awareness 2

Demo abstract: Fog computing for improving user application ...

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2nd IEEE/ACM international conference on internet-of-Things Design and Implementation, IoTDI 2017

作者： Saurez, Enrique Gupta, Harshit Ramachandran, Umakishore Mayer, Ruben Georgia Institute of Technology AtlantaGA United States Institute for Parallel and Distributed Systems University of Stuttgart Stuttgart Germany

ISBN: (纸本)9781450349666

Newgenerations of cloud applications are increasingly complex and pose lower latency requirements. The latter is forcing the industry to reduce network latency by adding computation nodes near the edge of the network, also known as Fog computing. To utilize the Fog nodes efficiently, the dynamic placement and migration of application components must be supported. To this end, a Fogaware application programming and deployment framework, called Foglets, has been proposed. This demonstration shows how the Foglets framework can be easily used to deploy applications in the Fog computing infrastructure: A video streaming application allows a moving user to continue watching a video on the closest available screen. © 2017 ACM.

关键词： Fog computing

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Security issues in cloud computing and its counter measure 2

Security issues in cloud computing and its counter measure

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2nd IEEE international conference on Recent Trends in Electronics, Information and Communication technology, RTEICT 2017

作者： Nayak, Akshay A. Sridhar, N.K. Poornima, G.R. Shivashankar Department of Electrical and Computer Engineering University of Arizona TucsonAZ85721 United States Department of Electronics and Communication Engineering Sri Venkateshwara College of Engineering Bengaluru Karnataka India

ISBN: (纸本)9781509037049

The Cloud computing is one of the most important on internet of Services and computer infrastructure. More and more industries have begun to explore cloud computing. Cloud computing is a developing technique in a distributed computing system that increases the scalability and flexibility in processing due to the ability to decrease the time for calculation. However, the high flexibility and portability of cloud have caused a number of security concerns, the security issue is a big threat in cloud computing. Data security can be defined as a confidentiality and integrity of data maintained by an organization. It is, therefore, necessary to solve this security issue to enable extensive use of cloud computing. This paper mainly deals with cloud computing and analyzes security issues in cloud computing and the countermeasure which can be taken to resolve the issues of security in cloud computing. © 2017 IEEE.

关键词： Cloud security

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A Secure Cloud Framework for ICMetric Based IoT Health Devices 17

A Secure Cloud Framework for ICMetric Based IoT Health Devic...

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2nd international conference on internet of things, Data and Cloud computing (ICC)

作者： Tahir, Ruhma Tahir, Hasan Sajjad, Ali McDonald-Maier, Klaus Univ Essex Wivenhoe Pk Colchester Essex England British Telecom Ltd Adastral Pk Ipswich Suffolk England

ISBN: (纸本)9781450347747

Wearable devices are an important part of internet of things (IoT)with many applications in healthcare. Prevalent security concerns create a compelling case for a renewed approach by incorporating the ICMetric technology in IoT healthcare. The ICMetric technology is a novel security approach and uses the features of a device to form the basis of cryptographic services like key generation, authentication and admission control. Cryptographic systems designed using ICMetric technology use unique measurable device features to form a root of trust. This paper uses the MEMS bias in a body wearable Shimmer sensor to create a device ICMetric. The ICMetric identity is used to generate cryptographic key to perform encryption and decryption of patients data which is being communicated to health professionals. The cloud based component of the proposed framework provides much needed distributed data processing and availability. The proposed schemes have been simulated and tested for conformance to high levels of security and performance.

关键词： Cryptography security ICMetric internet of Things cloud computing secure healthcare systems

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Resource scheduling in cloud computing using back propagation algorithm 2

Resource scheduling in cloud computing using back propagatio...

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2nd international conference On Emerging Computation and Information Technologies, ICECIT 2017

作者： Ashwini, B.C. Nijagunarya, Y.S. Department of Computer Science Siddaganga Institute of Technology Tumkur India

ISBN: (纸本)9781538610947

Cloud computing is also called as internet-based computing. Cloud computing is one of the distributed computing system. Its main principle is, to use the resources optimally for achieving higher efficiency. Cloud computing is mainly used to solve vast scale issues. IT assets gave by cloud system, then again, are devoted to providing back-end preparing abilities and client based access to these capabilities. In cloud computing technology, clients lease the resources and only pay for what they use. Cloud computing users should be particular while choosing cloud service providers. Main advantage of cloud computing is 'agility'. Scheduling of resources is one of the tough problem in cloud computing. The main task of Scheduling is, to assign the resources for the user request, so that the task can be finished in minimum time. In this paper Multiple Artificial Neural Network (MANN) is used for allocating the resources for the user requests. Thus with the help of Multiple Artificial Neural Network, scheduling of resources in cloud computing can be improved. © 2017 IEEE.

关键词： Neural networks

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Job Scheduling in Cloud Datacenters Using Enhanced Particle Swarm Optimization 2

Job Scheduling in Cloud Datacenters Using Enhanced Particle ...

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2nd international conference for Convergence in technology (I2CT)

作者： Chatterjee, Amlan Levan, Matthew Lanham, Crosby Zerrudo, Mishael Calif State Univ Dominguez Hills Dept Comp Sci Carson CA 90747 USA

ISBN: (纸本)9781509043071

Scheduling continues to be a predominant area of research in computer science, especially with the advent of cloud computing and internet-scale applications, which require global dissemination and high-availability to meet the variable demand of users from geographically distributed locations. While there are various algorithms which address the problem of scheduling, the issue of assigning compute jobs to servers in cloud data centers is particularly challenging, given its combinatorial nature. Operating systems utilize basic scheduling algorithms such as first fit, worst lit, best fit, round robin, and priority for determining the order in which processes are sent to the central processing unit and memory, disk space and other resources are allocated to be utilized. In datacenters, however, scheduling becomes more difficult due to increased complexity of the infrastructure and time-constraints of cloud platforms in general. Therefore, to address the issue of job scheduling on cloud datacenters, algorithms inspired by the natural world, such as particle swarm optimization, ant colony optimization, artificial bee colony, and others have been proposed. In this paper we explore the particle swarm optimization algorithm further, and study the effects of changing the social and cognitive value contributions in the convergence of the algorithm towards a solution. We also implement the naive scheduling algorithms for the cloud datacenters as well, and perform a comparison with the particle swarm optimization algorithm. All the implementations are done using CloudSim, a simulator for cloud computing platforms, and the results are shown. It can be concluded that the advanced algorithms indeed perform better than the na ve ones;however, the social and cognitive constants do not influence the solution for the particle swarm optimization technique significantly.

关键词： Scheduling Particle Swarm Optimization Cloud computing Cloud Datacenter CloudSim

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distributed Faulty Sensor Node Detection in Wireless Sensor Networks based on Copula Theory 17

Distributed Faulty Sensor Node Detection in Wireless Sensor ...

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2nd international conference on internet of things, Data and Cloud computing (ICC)

作者： Lalem, Farid Bounceur, Ahcene Euler, Reinhardt Hammoudeh, Mohammad Kacimi, Rahim Ghalem, Sanaa Kawther Univ Bretagne Occidentale 20 Ave Victor Le Gorgeu F-29238 Brest France Manchester Metropolitan Univ Manchester Lancs England Univ Toulouse IRIT UPS F-31000 Toulouse France Univ Oran 1 Oran 78229 Algeria Lab RIIR Oran 78229 Algeria

ISBN: (纸本)9781450347747

Wireless Sensor Networks (WSNs) are arising from the proliferation of Micro-Electro-Mechanical Systems (MEMS) technology as an important new area in wireless technology. They are composed of tiny devices which monitor physical or environmental conditions such as temperature, pressure, motion or pollutants, etc. Moreover, the accuracy of individual sensor node readings is decisive in WSN applications. Hence, detecting nodes with faulty sensors can strictly influence the network performance and extend the network lifetime. In this paper, we propose a new approach for faulty sensor node detection in WSNs based on Copula theory. The obtained experimental results on real datasets collected from real sensor networks show the effectiveness of our approach.(1)

关键词： Wireless Sensor Networks Copulas Faulty sensors Failure nodes

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Protecting an Automobile Network Using distributed Firewall System 17

Protecting an Automobile Network Using Distributed Firewall ...

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2nd international conference on internet of things, Data and Cloud computing (ICC)

作者： Rizvi, Syed Willett, Jonathan Perino, Donte Vasbinder, Tyler Marasco, Seth Penn State Univ Dept Informat Sci & Technol Altoona PA 16601 USA

ISBN: (纸本)9781450347747

As the automobile industry continues to incorporate more technology into cars, the security of the "automobile network" portion of that technology is in need of tremendous improvement. The communications between the in-vehicle infotainment (IVI) systems and the essential safety systems (e.g., anti-lock brake systems) should remain secure. However, there are few to no security measures currently implemented in an automobile network. This implies that if an attacker could break into a modern vehicle's IVI system, they could possibly endanger drivers, passengers, and others. Any of the integral mechanisms of the vehicle connected to the IVI system could be open to vulnerabilities. To protect automobile networks from threats, we present a novel Hybrid Security System (HSS). The proposed HSS uses the distributed firewalls to filter malicious content (e.g., data packets) placed at each module and an electronic control unit (ECU). The HSS creates two layers of defense within an automobile network that allows flexibility for manufactures who want extra security for their cars without causing abandonment or redesigning their current security architectures. Our proposed HSS is unique from other existing solutions in that it operates on a universal platform that can reach across all automobile manufacturers.

关键词： Automobile security network security firewalls packet filtering threats attacks CAR security

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AFT: Adaptive Fibonacci-based Tuning Protocol for Service and Resource discovery in the internet of Things 2

AFT: Adaptive Fibonacci-based Tuning Protocol for Service an...

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2nd international conference on Fog and Mobile Edge computing (FMEC)

作者： Albalas, Firas Mardini, Wail Al-Soud, Majd Jordan Univ Sci & Technol Dept Comp Sci Irbid Jordan

ISBN: (纸本)9781538628591

This paper explores Adaptive Fibonacci-based Tuning Protocol for Service and Resource discovery in the internet of Things (AFT). Through using constrained application protocol (CoAP), internet of Things (IoT) can support Machines to Machines (M2M) communications. CoAP has centralized and distributed operation modes to discover resources. In the centralized mode, resource directory (RD) is used to maintain and host updated services description of each resource in the network. RD requires periodical updates by other nodes. However, regularly updates resulted in additional signaling overhead, drain the node's battery and reduce the overall network lifetime. Hence, the proposed AFT intelligently varies and adjusts the update frequency of the services using Fibonacci sequence. We evaluated the performance using an inclusive experiments' number performed by employing emulated Tmote Sky motes in the COOJA environment. The results prove that the proposed AFT protocol consistently accomplished the lowest control overhead that ultimately increased the energy saving of the resources. They also confirm that this AFT protocol outperforms its traditional counterpart by 75% regarding the overall network lifetime.

关键词： internet of Things (IoT) Fibonacci sequence Service Discovery (SD) Resource Discovery Wireless Sensors CoAP Energy

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Students' Performance Tracking in distributed Open Education using Big Data Analytics 17

Students' Performance Tracking in Distributed Open Education...

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2nd international conference on internet of things, Data and Cloud computing (ICC)

作者： Hussein, Ashraf S. Khan, Hamayun A. Arab Open Univ Fac Comp & Engn Kuwait Kuwait

ISBN: (纸本)9781450347747

The field of Big Data Analytics (BDA) is advancing rapidly, and it is finding adoption in diverse areas such as Health, Commerce, Logistics, Retail and Manufacturing to name a few. Adoption of BDA techniques in the field of Higher Education is new, and it is steadily increasing. In this work, BDA techniques have been applied to track the Key Academic Performance Indicators (KAPIs) related to students at the Arab Open University (AOU) and to support the corresponding decisions in this regard. Since the AOU is a Pan Arab multi-campus distributed institution operating in 8 countries and makes extensive use of a wide range of cloud based applications to manage the students' life cycle, hence it is an ideal candidate for adoption of BDA techniques to track students' KAPIs across the AOU multiple country campuses. In order to achieve this objective, we have used IBM Watson Analytics (WA) platform to track the students' KAPIs. As a pilot project, we have focused in this work on the Information technology and computing (ITC) academic programme across the AOU. The Exploration and Business Intelligence BDA capabilities of WA have enabled us to analyze and track the academic KAPIs of the ITC students across AOU country campuses while the Predictive Analytics (PA) has led to identifying the dominant factors behind some of our problems such as students drop out rates. One of the most promising outcomes is the decision support dashboards such as the one related to the Student Risk Factor (SRF). By identifying At Risk Students, such dashboard can act as an "Early Alert System" to enable the AOU management to take corrective action to provide needed support to such students.

关键词： Big Data Analytics educational data analytics Watson Analytics Student Information Systems Academic Key Performance Indicators

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