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检索条件"任意字段=International Symposium Distributed Computing and Applications Business Engineering and Science"

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SmartVM: A Multi-Layer Microservice-Based Platform for Deploying SaaS

SmartVM: A Multi-Layer Microservice-Based Platform for Deplo...

引用

IEEE international symposium on Parallel and distributed Processing with applications and IEEE international Conference on Ubiquitous computing and Communications (ISPA/IUCC)

作者： Xi Zheng Jiaojiao Jiang Yuqun Zhang Yao Deng Min Fu Tianlei Zheng Xiao Liu Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China School of Software and Electrical Engineering Swinburne University of Technology Melbourne Australia School of Information Technology Deakin University Melbourne Australia Data61 CSIRO Sydney Australia School of Computing and Information Systems The University of Melbourne Melbourne Australia

ISBN: (纸本)9781538637913

With the advent of Software-as-a-Service (SaaS), SaaS developers are facing many challenges associated with the multi-tenancy and the dramatically increased number of users. In order to achieve resource-optimized, on-demand dynamic scaling across multiple tenants, and reduce costs, in this paper, a new platform, named SmartVM, is created to enable SaaS developer to create, customize, and deploy SaaS solutions in a multi-tier microservice-based manner. We develop an e-commerce SaaS prototype to evaluate effectiveness and efficiency of SmartVM. The results show that the SmartVM deployments outperforms the conventional monolithic and microservice deployments in smart monitoring, cost reduction, and resource optimization.

关键词： Containers Monitoring business Software as a service Australia Scalability Measurement

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In-memory distributed matrix computation processing & optimization 33

In-memory distributed matrix computation processing & optimi...

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33rd IEEE international Conference on Data engineering, ICDE 2017

作者： Yu, Yongyang Tang, Mingjie Aref, Walid G. Malluhi, Qutaibah M. Abbas, Mostafa M. Ouzzani, Mourad Purdue University United States Qatar University Qatar Qatar Computing Research Institute HBKU Qatar

ISBN: (纸本)9781509065431

The use of large-scale machine learning and data mining methods is becoming ubiquitous in many application domains ranging from business intelligence and bioinformatics to self-driving cars. These methods heavily rely on matrix computations, and it is hence critical to make these computations scalable and efficient. These matrix computations are often complex and involve multiple steps that need to be optimized and sequenced properly for efficient execution. This paper presents new efficient and scalable matrix processing and optimization techniques for in-memory distributed clusters. The proposed techniques estimate the sparsity of intermediate matrix-computation results and optimize communication costs. An evaluation plan generator for complex matrix computations is introduced as well as a distributed plan optimizer that exploits dynamic cost-based analysis and rule-based heuristics to optimize the cost of matrix computations in an in-memory distributed environment. The result of a matrix operation will often serve as an input to another matrix operation, thus defining the matrix data dependencies within a matrix program. The matrix query plan generator produces query execution plans that minimize memory usage and communication overhead by partitioning the matrix based on the data dependencies in the execution plan. We implemented the proposed matrix processing and optimization techniques in Spark, a distributed in-memory computing platform. Experiments on both real and synthetic data demonstrate that our proposed techniques achieve up to an order-of-magnitude performance improvement over state-ofthe-Art distributed matrix computation systems on a wide range of applications. © 2017 IEEE.

关键词： Matrix algebra

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In-memory distributed Matrix Computation Processing and Optimization

In-memory Distributed Matrix Computation Processing and Opti...

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IEEE 33rd international Conference on Data engineering (ICDE)

作者： Yu, Yongyang Tang, Mingjie Aref, Walid G. Malluhi, Qutaibah M. Abbas, Mostafa M. Ouzzani, Mourad Purdue Univ W Lafayette IN 47907 USA Qatar Univ Doha Qatar HBKU Qatar Comp Res Inst Doha Qatar

ISBN: (纸本)9781509065431

The use of large-scale machine learning and data mining methods is becoming ubiquitous in many application domains ranging from business intelligence and bioinformatics to self-driving cars. These methods heavily rely on matrix computations, and it is hence critical to make these computations scalable and efficient. These matrix computations are often complex and involve multiple steps that need to be optimized and sequenced properly for efficient execution. This paper presents new efficient and scalable matrix processing and optimization techniques for in-memory distributed clusters. The proposed techniques estimate the sparsity of intermediate matrix-computation results and optimize communication costs. An evaluation plan generator for complex matrix computations is introduced as well as a distributed plan optimizer that exploits dynamic cost-based analysis and rule-based heuristics to optimize the cost of matrix computations in an in-memory distributed environment. The result of a matrix operation will often serve as an input to another matrix operation, thus defining the matrix data dependencies within a matrix program. The matrix query plan generator produces query execution plans that minimize memory usage and communication overhead by partitioning the matrix based on the data dependencies in the execution plan. We implemented the proposed matrix processing and optimization techniques in Spark, a distributed in-memory computing platform. Experiments on both real and synthetic data demonstrate that our proposed techniques achieve up to an order-of-magnitude performance improvement over state-of-the-art distributed matrix computation systems on a wide range of applications.

关键词： Matrix computation query optimization distributed computing

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Enabling Community Health Care with Microservices

Enabling Community Health Care with Microservices

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IEEE international symposium on Parallel and distributed Processing with applications and IEEE international Conference on Ubiquitous computing and Communications (ISPA/IUCC)

作者： Richard Hill Dharmendra Shadija Mo Rezai School of Computing and Engineering University of Huddersfield United Kingdom Department of Computing Sheffield Hallam University United Kingdom

ISBN: (纸本)9781538637913

Microservice architectures (MA) are composed of loosely coupled, coarse-grained services that emphasise resilience and autonomy, enabling more scalable applications to be developed. Such architectures are more tolerant of changing demands from users and enterprises, in response to emerging technologies and their associated influences upon human interaction and behaviour. This article looks at microservices in the Internet of Things (IoT) through the lens of agency, and using an example in the community health care domain explores how a complex application scenario (both in terms of software and hardware interactions) might be modelled.

关键词： Medical services Computer architecture Internet of Things business Monitoring Service-oriented architecture

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A Survey of Security Concerns, Mechanisms and Testing in Cloud Environment

A Survey of Security Concerns, Mechanisms and Testing in Clo...

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international Conference on Electronics, Communication and Aerospace Technology

作者： Harikrishna Pillutla Amuthan Arjunan Department of Computer Science and Engineering Pondicherry Engineering College Pondicherry INDIA

ISBN: (纸本)9781538609668

distributed computing is a form of computing in which a group of independent systems are connected to a computer network. Cloud computing is one of the emerging domain in the field of Computer science. With the help of cloud computing, the computing services can be delivered over the internet. Before the advent of cloud computing, the business applications were found to be complicated, expensive and the software and hardware requirements of these applications were daunting. These issues were resolved in cloud computing since the hardware and software are maintained by the cloud vendors. Another advantage of using cloud computing is that it follows pay-per-use technology which means that the user only pays for the resources he/she consumes. The main goal of the security principles in cloud computing is to ensure that the Confidentiality, Integrity, and Availability of the data are preserved. This paper presents an extensive survey of the security threats;its countermeasures and testing that are available in cloud computing.

关键词： Cloud computing Security TaaS Cloud Testing

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A New Approach of Location and Navigation Services System Design In Complex Indoor Scenes Based on the Android Mobile computing Platform

A New Approach of Location and Navigation Services System De...

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2017 16th international symposium on distributed computing and applications to business,engineering and science（DCABES 2017）

作者： Guo Yucheng You Rou School of Computer Science and Technology Wuhan University of Technology School of Engineering and Science Huazhong University of Science and Technology

The emerging mobile platform has provided convenient facilities for indoor navigation software *** paper has focuses on design and realization a navigation system based on the Android mobile computing platform in complex indoor scenes,which takes the two-dimensional code for positioning,then generates a route with color partition by A*algorithm,in order to realize the indoor positioning and non-GPS *** system has innovated upon the method of indoor navigation.

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Attribute-Based Encryption with Personalized Search

Attribute-Based Encryption with Personalized Search

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IEEE international symposium on Parallel and distributed Processing with applications and IEEE international Conference on Ubiquitous computing and Communications (ISPA/IUCC)

作者： Qiang Zhang Guojun Wang Qin Liu Tao Peng School of Information Science and Engineering Central South University Changsha China College of Computer Science and Electronic Engineering Hunan University Changsha China

ISBN: (纸本)9781538637913

With the development of cloud computing, more and more enterprises will outsource their sensitive data for sharing in a cloud. However most existing works follow the model of “one size fits all” over encrypted outsourced cloud data, and ignore personalized search intention. Therefore, it is important to,,,, design a searchable encryption scheme that supports personalized search and fine-grained access control. In this paper, for the first time, we build a user interest model for an individual user according to the department the user belongs to and his search history. To address the limitations of the model of "one size fits all" and access control, we propose attribute-based encryption with personalized search (AEPS) which is suitable to multi-user sharing cloud computing search services.

关键词： Encryption Cloud computing Access control Servers Electronic mail Computational modeling

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A few of the most popular models for heterogeneous parallel programming

A few of the most popular models for heterogeneous parallel ...

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2017 16th international symposium on distributed computing and applications to business,engineering and science（DCABES 2017）

作者： Gang Xie Ya-lin Zhang Institute of Computer Applications China Academy of Engineering Physics

In this paper we consider the problem of programming for heterogeneous computer systems consist of CPUs and various accelerating devices such as *** introduce a few of the most popular models for heterogeneous parallel programming,including Open CL(Open computing Language),CUDA(Compute Unified Device Architecture),Open ACC,Open HMPP(Hybrid Multicore Parallel Programming),C++ AMP(accelerated massive parallelism),HPL(Heterogeneous Programming Library),etc.

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Proceedings - 9th international symposium on distributed computing and applications to business, engineering and science, DCABES 2010: Preface

Proceedings - 9th International Symposium on Distributed Com...

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Proceedings - 9th international symposium on distributed computing and applications to business, engineering and science, DCABES 2010 2010年 xv-xvi页

作者： Guo, Qingping Lai, Choi-Hong Douglas, Craig Wuhan University of Technology China University of Greenwich United Kingdom University of Wyoming United States

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OFL: A Language for Cloud Orchestration

OFL: A Language for Cloud Orchestration

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IEEE international symposium on Parallel and distributed Processing with applications and IEEE international Conference on Ubiquitous computing and Communications (ISPA/IUCC)

作者： Flora Amato Aniello Castiglione Nicola Mazzocca Francesco Moscato Vincenzo Moscato DIETI University of Naples Federico II Naples NA Italy Department of Computer Science University of Salerno Salerno Italy Department. of Scienze Politiche University of Campania “Luigi Vanvitelli” Caserta Italy

ISBN: (纸本)9781538637913

The increasing complexity of Cloud Architecture and the introduction of new paradigms like Internet of Things introduced the problem of creating Value Added Services by composition, not only of Resources, but of Services too. In this work we describe an architectural solution for Orchestration at all Cloud Layers. Here we described a language for orchestrating both resources and services in Cloud. The language manages composition of services and resources in order to create composite service based on Cloud Design Patterns. It is based on a Workflow language for description of composition and it enables verification of composite services by means of Model Driven engineering techniques, providing a precious and easy-to-use tool for Cloud engineering.

关键词： Cloud computing Quality of service Semantics Ontologies Computer architecture Skeleton Electronic mail

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