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共 133 条记录，以下是41-50 订阅

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Priority Based Virtual Machine Allocation and Scheduling for Security in cloud computing 3rd

Priority Based Virtual Machine Allocation and Scheduling for...

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3rd international conference on Smart computing and Informatics (SCI)

作者： Radhika, T. V. Gouda, Krushna Chandra Kumar, S. Sathish Dayananda Sagar Coll Engn Dept Informat Sci & Engn Bangalore Karnataka India AcSIR CSIR Ctr Math Modeling & Comp Simulat C MMACS Wind Tunnel Rd Bangalore Karnataka India RNS Inst Technol Dept Comp Sci & Engn Bangalore Karnataka India

ISBN: (纸本)9789813296909;9789813296893

cloud computing relies on the advancement of distributed computing and virtualization technologies to achieve cost efficiency in the consumption of computing resources. Efficient resource allocation is one of the important concerns for cloud users. To satisfy the need of each cloud user in an efficient manner, provision has to be made to make sure that the resources are available to them at all the time. Optimal resource allocation with minimum wastage and maximizing the profit is considered to be challenging. Also once the resources are allocated, isolation among them is critical from security point of view as there exits various kinds of adversary attacks in the real world. In this paper a novel method has been proposed for priority based dynamic Virtual Machine (VM) allocation on the basis of various parameters such as No. of nodes or processor's request, Time of execution, Importance of user, Amount of storage required etc. and isolation among the allocated virtual machines since the virtualized services, hardware, software and infrastructures share the same physical resources. Also there are chances of adversary users hosted on the same hardware which may lead to various kinds of cross VM attacks and security threats. Finally an approximation technique for resource allocation problem has been addressed which consider each unallocated resource request from user that may lead to penalty for cloud administrator which increases as time elapses. As the resource allocation problem is considered for various applications, particularly for emergency service allocations such as scientific simulations related to cyclone prediction, monsoon prediction, rainfall etc. which needs high performance computational power. Thus allocating the resource request within the predetermined time limit is of primary concern otherwise it may lose its purpose.

关键词： Virtualization Optimal resource allocation Adversary attacks Cross VM attacks Approximation

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Research on Technical Architecture and Overall Scheme of Railway Block Chain Service Platform 3

Research on Technical Architecture and Overall Scheme of Rai...

引用

3rd international conference on Blockchain Technology and applications (ICBTA)

作者： Zhang Xiaodong Li Ping Ma Xiaoning China Acad Railway Sci Inst Comp Technol 2 Daliushu Rd Beijing Peoples R China China Acad Railway Sci Beijing Peoples R China China Acad Railway Sci Inst Comp Technol Beijing Peoples R China

ISBN: (纸本)9781450388962

The block chain has many unique characteristics, like decentralization, stability, openness and transparency. We can apply block chain in many fields of railway to improve the comprehensive efficiency and benefit, such as railway passenger and freight service, engineering construction, big data sharing and so on. With the gradual completion of data service platform, big data lake and cloud computing in China Railway, these foundations can support the railway block chain application. The paper analyzed the development status and existing problems of block chain at home and abroad. Through the multidimensional analysis for the mainstream block chain platform architecture, the thesis gets the architecture selection of the railway block chain platform. Based on the hyperledger fabric, we propose the technical architecture and overall scheme for the railway block chain service platform respectively. The paper also designs the implementation path for the platform application construction. This research plays an important role and significance in promoting the block chain technology applying and developing in the railway field.

关键词： Blockchain Platform Railway Information Planning Technical Architecture Hyperledger Fabric Interconnection

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Machine Learning Techniques and computing technologies for IoT based Smart Healthcare (COVID-19 Case Study)

Machine Learning Techniques and Computing Technologies for I...

引用

Advances in computing, Communication Control and Networking (ICAC3N), international conference on

作者： Mahmood Hussain Mir Sanjay Jamwal Shahidul Islam Qamar Rayees Khan Baba Ghulam Shah Badshah University Rajouri Jammu and Kashmir India

ISBN: (纸本)9781665438124

The exponential growth of smart devices and gadgets connected to the Internet of Things (IoT) produces massive amounts of data. The number of internet-connected devices is predicted to outnumber people by 25 to 50 billion by 2025. The new concept IoT refers to the combination of wired and wireless embedded communication technologies, sensors, actuators (transducers), and internet-connected items. The data generated by these IoT devices is in high velocity, variety, and varsity in accordance with location and time. IoT is generating data so it one of the primary sources of big data. Intelligent analysis and processing need an hour to develop smart IoT applications to tackle this huge volume of data. This article accesses various computing frameworks such as cloud computing, Fog computing and Edge computing environments for smarter IoT applications. This article also presents how machine learning algorithms can be incorporated in IoT data to get better insights. Various machine learning algorithms are explained and how these algorithms can be applied to data to get a higher level of information. This studies key contribution is how computing frameworks can be integrated with machine learning techniques in the healthcare sector to get better insights from the data. Mostly in this article, IoT and machine learning algorithms are discussed with respect to COVID-19. Moreover, the potential application areas and open issues of IoT data analytics and Machine Learning are discussed.

关键词： COVID-19 cloud computing Wireless sensor networks Machine learning algorithms Transducers Machine learning Medical services

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Sound perception in 3d virtual environments: Application to a roman theatre of hispania 3rd

Sound perception in 3d virtual environments: Application to ...

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3rd international conference on Human Interaction and Emerging technologies: Future applications, IHIET 2020

作者： Alayón, Javier Romero-Odero, José A. Galindo, Miguel Nieves, Francisco J. Girón, Sara Departamento de Física Aplicada II Escuela Técnica Superior de Arquitectura Universidad de Sevilla Avenida Reina Mercedes 2 Seville41012 Spain

ISBN: (纸本)9783030553067

The aim of this work is to present the methodology implemented for the assessment of the human perception of sound and of the degree of acoustic comfort of occupants in an ancient Roman theatre. The evaluation is carried out through a visual and acoustic experience in a virtual environment. The textured 3D visual model of the space, and the binaural auralisations based on either on-site empirical measurements or on acoustic simulations, are displayed in a listening room designed with a very short reverberation time and low background noise. By means of sophisticated equipment for 3D virtual environment reproduction to groups of people, this listening room enables the physical ambience to be recreated of the Roman theatre of Cartagena, which is located in the southeast of Hispania (Spain). Groups of people can therefore subjectively assess the intelligibility of speech and the clarity for music of this open-air performance venue. The results accentuate the strong correlation between audio and visual perceptual aspects and contribute towards a more comprehensive understanding of the architectural aural experience. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

关键词： Theaters

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Detection of Data Anomalies in Fog computing Architectures 3rd

Detection of Data Anomalies in Fog Computing Architectures

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3rd international conference on Smart Trends for Information Technology and Computer Communications, SmartCom 2019

作者： Vidyasankar, K. Department of Computer Science Memorial University St. John’sNFA1B 3X5 Canada

ISBN: (纸本)9789811500763

Fog computing architectures provide a new platform for distributed stream processing in Internet of Things (IoT) applications. In a hierarchical infrastructure, processing of stream data arriving from sensors starts at the lowest level edge nodes and proceeds to the intermediate level fog nodes and eventually to the top-level cloud node. The goal is to do as much processing as possible at the lower level nodes and react to unexpected or interesting input values as early as possible. The unexpected values are referred to as anomalies. They may occur due to malfunctioning of sensors, which may be due to accidents or intentional attacks, or changes in the environment. The anomalies must be detected and proper actions must be taken quickly to bring the application to a steady state. We describe a generic framework for detection of data anomalies in a fog hierarchy in this paper. Our framework can be adapted to any application and other fog architectures. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Fog computing

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Key technologies and challenges in IoT Edge computing 3

Key Technologies and challenges in IoT Edge Computing

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3rd international conference on I-SMAC (IoT in Social, Mobile, Analytics and cloud), I-SMAC 2019

作者： Naveen, Soumyalatha Kounte, Manjunath R. School of Computing and IT REVA University Bengaluru India School of Electronics and Communication REVA University Bengaluru India

ISBN: (纸本)9781728143651

In recent years, the tremendous growth of interconnected devices results in a new technology called Internet of Things (IoT). cloud computing assists the IoT applications to store the data and perform computation in order to control and manage the vast amount of data generated by these IoT devices. But the major challenge in cloud computing is to meet requirements of many real-time applications of Internet of Things. Whereas, Edge is a computing architecture that helps to communicate, manage, store, and processes the data that quickly returns the response. This is made possible by moving these functionalities closer to the end users. Edge computing and cloud computing are independent as wells as mutually beneficial to many applications. This paper discusses the overview of IoT, communication technologies and protocols required for IoT, data transfer in IoT. cloud services to store, process and to analyze the data generated from IoT devices are explored. © 2019 IEEE.

关键词： Internet of things

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Big Data Platforms and Tools for Data Analytics in the Data Science Engineering Curriculum 2019

Big Data Platforms and Tools for Data Analytics in the Data ...

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3rd international conference on cloud and Big Data computing (ICCBDC)

作者： Demchenko, Yuri Univ Amsterdam Sci Pk 904 NL-1098 XH Amsterdam Netherlands

ISBN: (纸本)9781450371650

This paper presents experiences of development and teaching courses on Big Data Infrastructure technologies for Data Analytics (BDIT4DA) as a part of the general Data Science curricula. The authors built the discussed course based on the EDISON Data Science Framework (EDSF), in particular, Data Science Body of Knowledge (DS-BoK) related to Data Science Engineering knowledge area group (KAG-DSENG). The paper provides overview of the cloud based platforms and tools for Big Data Analytics and stresses importance of including into curriculum the practical work with clouds for future graduates or specialists workplace adaptability. The paper discusses a relationship between the DSENG BoK and Big Data technologies and platforms, in particular Hadoop based applications and tools for data analytics that should be promoted through all course activities: lectures, practical activities and self-study.

关键词： EDISON Data Science Framework (EDSF) Data Science Body of Knowledge (DS-BoK) Data Science Engineering Big Data Infrastructure technologies Hadoop ecosystem cloud computing

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Computational secure ORAM (COMP SE-ORAM) with [omega](log n) Overhead: Amazon S3 case study-random access location 3

Computational secure ORAM (COMP SE-ORAM) with [omega](log n)...

引用

3rd IEEE international conference on cloud and Fog computing technologies and applications, cloud Summit 2019

作者： Mbelli, Thierry Mbah First National Bank Johannesburg South Africa

ISBN: (纸本)9781728131016

Oblivious RAM (ORAM) is a strong-provable secured approach to accessing cloud stored objects. Many ORAM models have been proposed to improve storage, communication and privacy efficiency of the ORAM constructions with no much attention paid to a holistic approach to the oblivious cloud storage security. Statically secure ORAM models generally have the security overhead of ω(log ^2 n) where n is the memory size. This paper proposes an ORAM model with computational security overhead of ω(log n) using Amazon Simple Storage (Amazon S3) as a storage model. Another benefit of this proposed model is its conceptual simplicity at implementation. The construction of this model is based on the ORAM model proposed by Kai-Min Chung, Zhenming Liu and Rafael Pass. The crucial ramification of this model is to reduce the overhead from ω(log ^2 n) to ω(log n). Using the Amazon S3, security analysis was conducted with the result incurring ω(log n) security overhead. This is achieved by randomizing the location of the storage node. © 2019 IEEE.

关键词： Random access storage

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An Approach to Edge Extraction Based on 3D Point cloud for Robotic Chamfering 3

An Approach to Edge Extraction Based on 3D Point Cloud for R...

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3rd international conference on Artificial Intelligence, Automation and Control technologies (AIACT)

作者： Wang, Yongzhi Du, Zhijiang Gao, Yongzhuo Li, Mingyang Dong, Wei Harbin Inst Technol Harbin Heilongjiang Peoples R China

Inconsistency of workpieces always results in low level automation of subsequent finishing process. As decreasing number of skilled workers, the demands of flexible manufacturing with robots is growing. In this paper, a kind of workpiece with complex free-form surface will be chamfered by industrial robots. Due to the intolerant differences among workpieces, traditional teach-playback method for robot is not appropriate for this application. The edge spline of each workpiece needs to be detected so that trajectories are generated to chamfer. Thus, an approach to edge extraction based on a 3D point cloud obtained by the 3D industrial camera is introduced to solve this problem. A time optimizing method is proposed to accelerate the extraction process. Finally, we decrease computing time from 55 minutes to 300 seconds, and the precision is 0.4180 mm.

关键词： Industrial robots

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cloud computing with Kubernetes cluster elastic scaling 19

Cloud computing with Kubernetes cluster elastic scaling

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3rd international conference on Future Networks and Distributed Systems, ICFNDS 2019

作者： Thurgood, Brandon Lennon, Ruth G. Dept. of Computing Letterkenny Institute of Techology Port Rd. Letterkenny Co. Donegal Ireland

ISBN: (纸本)9781450371636

cloud computing and artificial intelligence (AI) technologies are becoming increasingly prevalent in the industry, necessitating the requirement for advanced platforms to support their workloads through parallel and distributed architectures. Kubernetes provides an ideal platform for hosting various workloads, including dynamic workloads based on AI applications that support ubiquitous computing devices leveraging parallel and distributed architectures. The rationale is that Kubernetes can be used to support backend services running on parallel and distributed architectures, hosting ubiquitous cloud computing workloads. These applications support smart homes and concerts, providing an environment that automatically scales based on demand. While Kubernetes does offer support for auto scaling of Pods to support these workloads, automated scaling of the cluster itself is not currently offered. In this paper we introduce a Free and Open Source Software (FOSS) solution for autoscaling Kubernetes (K8s) worker nodes within a cluster to support dynamic workloads. We go on to discuss scalability issues and security concerns both on the platform and within the hosted AI applications. © 2019 Association for computing Machinery.

关键词： Automation

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