云计算环境下面向数据密集型应用的数据布局策略与方法

云计算环境下面向流程的数据密集型应用已被广泛应用于多个领域.面对多数据中心的云计算环境,这类应用在数据布局方面遇到了新的挑战,主要表现在如何减少跨数据中心的数据传输、如何保持数据间的依赖性以及如何在提高效率的同时兼顾全局的负载均衡等.针对这些挑战,文中提出一种三阶段数据布局策略,分别针对跨数据中心数据传输、数据依赖关系和全局负载均衡三个目标对数据布局方案进行求解和优化.实验显示,文中提出的数据布局策略具有良好的综合性能,特别是在降低流程执行过程中由跨数据中心数据传输所导致的时间开销方面,效果尤为明显.     

LTSS: Load-Adaptive Traffic Steering and Forwarding for Security Services in Multi-Tenant Cloud Datacenters

Currently, different kinds of security devices are deployed in the cloud datacenter environment and tenants may choose their desired security services such as firewall and IDS (intrusion detection system). At the same time, tenants in cloud computing datacenters are dynamic and have different requirements. Therefore, security device deployment in cloud datacenters is very complex and may lead to inefficient resource utilization. In this paper, we study this problem in a software-defined network (SDN) based multi-tenant cloud datacenter environment. We propose a load-adaptive traffic steering and packet forwarding scheme called LTSS to solve the problem. Our scheme combines SDN controller with TagOper plug-in to determine the traffic paths with the minimum load for tenants and allows tenants to get their desired security services in SDN-based datacenter networks. We also build a prototype system for LTSS to verify its functionality and evaluate performance of our design.     

云计算在中小企业的应用前景分析

云计算作为一项迅速发展的信息技术目前已应用在国内外诸多领域并得到了充分的利用,但是对于目前国内的一些中小型企业来说,仍然处于一种谨慎观望缓步发展的状态.本文介绍了云计算基本原理及发展现况,探讨了云计算技术应用在中小型企业中的实际意义,以及目前阻碍云计算技术在中小型企业进一步发展和应用的主要原因.     

Supporting Cost-Effective Fault Tolerance in Distributed Message-Passing Applications with File Operations

In this paper we present an approach to reliable distributed computing, which incorporates fault tolerance into applications at low cost, in terms of both run-time performance and programming effort required to construct reliable application software. In our model fault tolerance is based on distributed consistent checkpointing and rollback-recovery integrated with a user-level reliable transmission protocol. By employing novel techniques 8and algorithms, our approach is distinguished from other consistent checkpointing schemes by the following features: first, minimum communication overhead for constructing a consistent distributed checkpoint and catching messages in transit during checkpointing; second, tolerance to message losses due to site failures or unreliable non-FIFO networks; and third, efficient checkpointing and recovery of persistent state, i.e., user files. Based on the model, a software library prototype called Libra has been implemented for supporting fault tolerance in distributed message-passing applications with file operations. The library provides an easy to use programming interface including message-passing and file I/O primitives, which hides the complexity of both fault-tolerant network communications and checkpointing and recovering user files from the application level. Experience with a number of long-running distributed applications shows that Libra can provide fault tolerance in a cost-effective manner.     

云计算的基础结构设计和云应用服务

云计算是基于云结构的信息技术资源消费与利用系统,也是基于互联网的链路传输系统与终端服务系统的集成应用模型。典型的云服务模型包括Saa S/Aaa S、Iaa S、Paa S、Daa S,这些参考模型同时组成云系统应用服务基础架构。云计算开发标准与规则是云结构发展与云数据库的开发参考基准,也是云管理与云进化的参考结构。云系统服务质量关系云应用发展,而云管理的服务配置与监视服务提供反馈信息。云应用服务维护运行与数据安全是云安全提供的基础保障服务。云备份作为领导性企业云的高级服务功能应能适应云灵活多变性与容灾免灾设计,文中深入分析云数据备份技术应用与程序算法,细述实用数据应用处理方法。动态开发环境是企业云对云计算开放研究平台,在全球推进云环境的开发测试。云计算风险分析与管理同时促进云应用进化。     

云计算与云存储技术的企业应用分析

作为以互联网为计算平台的云计算,将会更广泛地涉及到海量数据处理任务.海量数据处理指的是对大规模数据的计算和分析.在互联网时代,互联网数据的统计和分析很多是海量数据级别的,为企业的数据储存提供了重要的服务.本文分析了云计算的应用类型,介绍了云计算的基础设施,深入分析了云计算与企业应用之间的关系.     

Special Feature Microcomputer Applications in Japan

JEIDA, the Japan Electronic Industries Development Association, recently surveyed the state of the applications art in Japan. The most striking features of the study were its scope and the richness of the answers obtained.     

浅议云计算在高校中的应用

云计算是一种基于分布式的计算,以用户为中心,数据存在于云海之中,你可以在任何时间（Anytime）、任何地点（Anywhere）以某种便捷的方式安全地获得它或与他人分享。云计算使得Intemet变成每个人的数据存储中心、数据计算中心,本章具体讨论在高校中的应用。     

反求工程中点云数据的二次曲面特征提取技术

基于点的连通性及同一特征面测量点几何特征相似性，在特征曲面拟合误差控制下，实现了散乱数据二次曲面的区域分割．工程应用实例表明：文中方法稳定可靠，可显著提高反求CAD建模效率与重建模型精度。     

浅析云计算及其应用

云计算是一种创新的商业计算服务,云计算是将计算任务分配到云网平台中,为各种应用系统提供计算、存储以及各类软件服务。本文首先概述了云计算的定义和构成,并介绍了云计算的特点,最后探讨了云计算的应用问题。     

混合云环境下基于模糊理论的科学工作流数据布局策略

混合云环境下,合理的数据布局策略对科学工作流的高效执行至关重要.传统的科学工作流数据布局策略主要基于确定性环境,而在实际网络环境中,由于不同数据中心之间的负载不同、带宽波动和网络拥塞等原因以及计算机自身的特性,数据传输时间存在不确定性.为了解决该问题,基于模糊理论,以最小化数据模糊传输时间为目标,提出了一种基于遗传算法算子的模糊自适应离散粒子群优化算法(Fuzzy Adaptive Discrete Particle Swarm Optimization Algorithm Based on Genetic Algo-rithm Operators,FGA-DPSO),对科学工作流数据进行合理布局,同时满足数据集的隐私要求和数据中心的容量限制.实验结果表明,该算法能够有效地减少混合云环境下科学工作流的数据模糊传输时间.     

Extending Science Gateway Frameworks to Support Big Data Applications in the Cloud

Cloud computing offers massive scalability and elasticity required by many scientific and commercial applications. Combining the computational and data handling capabilities of clouds with parallel processing also has the potential to tackle Big Data problems efficiently. Science gateway frameworks and workflow systems enable application developers to implement complex applications and make these available for end-users via simple graphical user interfaces. The integration of such frameworks with Big Data processing tools on the cloud opens new opportunities for application developers. This paper investigates how workflow systems and science gateways can be extended with Big Data processing capabilities. A generic approach based on infrastructure aware workflows is suggested and a proof of concept is implemented based on the WS-PGRADE/gUSE science gateway framework and its integration with the Hadoop parallel data processing solution based on the MapReduce paradigm in the cloud. The provided analysis demonstrates that the methods described to integrate Big Data processing with workflows and science gateways work well in different cloud infrastructures and application scenarios, and can be used to create massively parallel applications for scientific analysis of Big Data.     

云计算机在手机软件的应用理论研究与实现

就云计算机在手机软件的应用理论研究及实现进行了深入的分析和探讨,具有一定的参考价值。     

云计算应用及其安全问题研究

随着全球信息化进程的不断演进,云计算成为继分布式计算、并行计算、网格计算之后的一种新的互联网服务模式,受到业界和政府的广泛关注.我们从云计算的概念定义和发展现状出发,从服务模式的角度分析提出了云计算服务的典型特征,深入分析了云计算服务可能存在的安全问题,进而提出了公有云管理服务规范体系.该规范体系可以作为企业加强安全防护手段、用户按需选择云计算服务,以及建立第三方云计算安全评估、监测和管理平台的参考和依据,从而起到促进云计算产业安全、有序发展的作用.     

CA-DAG: Modeling Communication-Aware Applications for Scheduling in Cloud Computing

This paper addresses performance issues of resource allocation in cloud computing. We review requirements of different cloud applications and identify the need of considering communication processes explicitly and equally to the computing tasks. Following this observation, we propose a new communication-aware model of cloud computing applications, called CA-DAG. This model is based on Directed Acyclic Graphs that in addition to computing vertices include separate vertices to represent communications. Such a representation allows making separate resource allocation decisions: assigning processors to handle computing jobs, and network resources for information transmissions. The proposed CA-DAG model creates space for optimization of a number of existing solutions to resource allocation and for developing novel scheduling schemes of improved efficiency.     

云计算环境下的分布存储应用及安全机制

云计算环境下,对数据存储提出了新的要求,不仅要在容量空间上满足,更要在安全性能上满足.文章首先简单分析了数据库的类型,以及分布式存储在办公室系统中的应用,然后其安全机制加以研究,介绍了几种安全技术.     

移动云计算及其军事应用探讨

计算机与通信技术的不断融合促进了移动云计算的产生与发展.阐述了移动云计算的概念和实质,探讨了移动云计算的服务模型,指出了我国发展移动云计算的重要意义,提出了移动云计算在军事领域应用的几点设想,并对移动云计算用于军事领域进行了展望.     

增强的典型相关分析及其在人脸识别特征融合中的应用

在传统的典型相关分析(CCA)基础上,定义了类别相关性,提出了增强典型相关分析(ECCA)方法.对于一个模式空间的2个观测空间(对任意模式都有2种观测向量),ECCA能够找到这2个观测空间对类别而言更有意义的相关子空间,且同时保持了投影分量的无关性.实验结果表明,ECCA优于CCA,GCCA融合方法.     

Double Auction-based Scheduling of Scientific Applications in Distributed Grid and Cloud Environments

Economy models have long been considered as a promising complement to the classical distributed resource management not only due of their dynamic and decentralized nature, but also because the concept of financial valuation of resources and services is an inherent part of any such model. In its broadest sense, scheduling of scientific applications in distributed Grid and Cloud environments can be regarded as a market-based negotiation between a scheduling service optimizing user-centric objectives (execution time, budget), and a resource manager optimizing provider-centric metrics (resource utilization, income, job throughput). In this paper, we propose a new instantiation of the negotiation protocol between the scheduler and resource manager using a market-based Continuous Double Auction (CDA) model. We analyze different scheduling strategies that can be applied and identify general strategic patterns that can lead to a fast and cheap work ow execution. In the experimental study, we demonstrate that under certain circumstances one can benefit by applying an aggressive scheduling strategy.     

基于点云几何特征的错误匹配点对剔除算法

针对点云配准过程中存在错误匹配点对的问题,提出一种基于点云几何特征的双阈值剔除算法。依据点云几何特征在刚体变换过程中的平移旋转不变性,在初始匹配点集基础上,借助k近邻方法选取各查询点的近邻点并构成三点对,根据点间距离不变特性完成点对的初步筛选。在此基础上,采用曲面变分描述该三点对所在局部区域的几何特征,通过分析三点对的协方差矩阵,完成匹配点的最终筛选。实验结果表明,该方法可以有效剔除错误匹配点,且具有较高的配准精度。