一种基于DAG的MapReduce任务调度算法

Hadoop已成为研究云计算的基础平台,MapReduce是其大数据分布式处理的计算模型。针对异构集群下MapReduce数据分布、数据本地性、作业执行流程等问题,提出一种基于DAG的MapReduce调度算法。把集群中的节点按计算能力进行划分,将MapReduce作业转换成DAG模型,改进向上排序值计算方法,使其在异构集群中计算更精准、任务的优先级排序更合理。综合节点的计算能力与数据本地性及集群利用情况,选择合理的数据节点分配和执行任务,减少当前任务完成时间。实验表明,该算法能合理分布数据,有效提高数据本地性,减少通信开销,缩短整个作业集的调度长度,从而提高集群的利用率。     

纠删码存储下的离线批处理作业性能优化

随着互联网数据的爆发式增长,越来越多的分布式存储系统开始引入纠删码存储机制,以在提供数据可靠性的同时降低存储开销。但纠删码机制的引入改变了数据放置模式,从而影响分布式系统上层业务的数据访问和运行效率。在异构 Hadoop 集群环境中,一类典型的离线批处理作业——MapReduce 应用在条带式纠删码存储模式下需要从多个节点访问数据,该“一对多”的数据访问模式由于节点性能差异造成应用执行效率下降。对此,该文提出了一种基于异构环境的数据放置和任务分 配策略。通过对异构集群中各节点的硬件参数和历史负载进行分析,将同一纠删码条带的数据块尽可能分布在性能相近的节点上;在系统进行任务分配时,针对各节点当前负载和运算能力确定节点的任务并发度,以平衡各节点计算资源的占用情况,从而避免因数据访问或计算过程中的资源竞争产生极端缓慢任务以致降低整个 MapReduce 应用的运行效率。实验结果表明,相比当前 Hadoop 默认的随机数据放置和任务分配策略,该文提出的异构感知数据放置策略和动态任务分配策略能够在不同类型的MapReduce 应用中有效削弱任务的长尾效应,使得作业整体运行时间节约 10.5%～42%,验证了该方案的有效性。     

大数据分析中基于MapReduce的空间权重创建方法研究

大数据空间分析是Cyber-GIS的重要方面。然而,如何利用现有的网络基础设施(比如大规模计算集群)对大数据进行并行分布式空间分析仍然是一大难题。为此,本文提出一种基于MapReduce的空间权重创建方法。该方法依托Hadoop框架组织计算资源,基于MapReduce模式从大规模空间数据集中高效创建出空间权重：大空间数据首先被分为多个数据块,然后将映射器分布给计算集群中的不同节点,以便在数据中寻找出空间对象的相邻对象,最后由约简器从不同节点处收集相关结果并生成权重文件。利用Amazon公司弹性MapReduce的Hadoop框架,从人工空间数据中创建基于邻近概念的权重矩阵进行仿真,实验结果表明,本文方法的性能优于传统方法,解决了大数据的空间权重创建问题。     

异构资源环境下的MapReduce性能优化

针对现有Hadoop难以适应异构资源环境的不足,提出一种自适应MapReduce调度器:CloudMR.基于数据局部性,CloudMR将同一机架内的对进行本地归约合并,减少中间结果中对的数目,从而减少机架间的数据传送.根据资源性能和任务特征,CloudMR动态确定节点任务槽数和数据分配量.对于计算性能高的节点,CloudMR分配较多的任务和数据量,而对于计算性能低的节点,相应地减轻任务和数据量负载.实验表明,在异构环境下,较之现有Hadoop,CloudMR减少了节点间数据传输和备份任务运行,缩短了作业完成时间.     

异构环境中HDFS数据块调度算法的设计与实现

针对Hadoop分布式文件系统(HDFS)的写性能在执行效率上的不足,提出一种在节点性能异构环境中对HDFS数据块进行并发传输的调度算法。该算法实时监控HDFS集群中每个节点的资源状态和内存缓存队列,动态地将接收节点与转发节点进行配对传输,使全系统节点的网卡和磁盘并发工作,缩短了所有副本写入分布式文件系统的时间。将数据写入磁盘后请求下一个数据块,保证数据安全性,同时也使得各个节点获得与自身性能相匹配的副本数,使性能异构的系统能达到较高的写入速度。性能测试结果表明,使用该算法的分布式文件系统的写入性能较原始的HDFS提高了1倍。     

Hadoop异构集群中数据负载均衡的研究

Hadoop平台下,数据的负载均衡对平台性能的发挥有着深远的影响。首先分析默认数据负载均衡的局限性,针对现有默认HDFS(Hadoop Distributed File System)数据负载均衡算法只考虑存储空间利用率,而未考虑节点间异构性的问题,提出一种量化异构集群数据负载均衡的数学模型。该模型根据节点的存储空间及节点性能计算得到各个节点的理论空间利用率,并根据当前集群存储空间利用率动态调整节点最大负载。实验结果表明,提出的数据负载均衡策略能够让异构集群达到更合理的均衡状态,提高集群的效率,并有效减少作业的执行时间。     

基于云计算Hadoop异构集群的并行作业调度算法

针对Hadoop异构集群中计算和数据资源的不一致分布所导致的调度性能较低的缺点,设计了一种基于Hadoop集群和改进Late算法的并行作业调度算法;首先,介绍了基于Hadoop框架和Map-Reduce模型的调度原理,然后,在经典的Late调度算法的基础上,对Map任务和Reduce任务的各阶段执行时间进度比例进行存储和更新,为了进一步地提高调度效率,将慢任务迁移到本地化节点或离数据资源较近的物理节点上,并给了基于改进Late算法的作业调度流程;为了验证文中方法,在Hadoop集群系统上测试,设定1个为Jobtracker主控节点和7个为TaskTracker节点,实验结果表明文中方法能实现异构集群的作业调度,且与其它方法比较,具有较低的预测误差和较高的调度效率。     

一种优化MapReduce系统能耗的数据布局算法

在云计算技术和大数据技术的推动下,IT资源的规模不断扩大,其能耗问题日益显著.研究表明:节点资源利用率不高、资源空闲导致的能源浪费,是目前大规模分布式系统的主要问题之一.研究了MapReduce系统的能耗优化.传统的基于软件技术的能耗优化方法多采用负载集中和节点开关算法,但由于MapReduce任务的特点,集群节点不仅要完成运算,还需要存储数据,因此,传统方法难以应用到MapReduce集群.提出了良好的数据布局可以优化集群能耗.基于此,首先定义了数据布局的能耗优化目标,并提出相应的数据布局算法;接着,从理论上证明该算法能够实现数据布局的能耗优化目标;最后,在异构集群中部署3种数据布局不同的MapReduce系统,通过对比三者在执行CPU密集型、I/O密集型和交互型这3种典型运算时的集群能耗,验证了所提出的数据布局算法的能耗优化效果.理论和实验结果均表明,所提出的布局算法能够有效地降低MapReduce集群的能耗.上述工作都将促进高能耗计算和大数据分析的应用.     

一种异构环境下的基于MapReduce任务调度改进机制

针对在异构环境下采用现有MapReduce任务调度机制可能出现各计算节点间数据迁移和系统资源分配难以管理的问题, 提出一种动态的任务调度机制来改善这些问题。该机制先根据节点的计算能力按比例放置数据, 然后通过资源预测方法估计异构环境下MapReduce任务的完成时间, 并根据完成时间计算任务所需的资源。实验结果表明, 该机制提高了异构环境下任务的数据本地性比例, 且能动态地调整资源分配, 以保证任务在规定时间内完成, 是一种有效可行的任务调度机制。     

混合存储模式下MapReduce作业调度

在异构Hadoop集群场景中, 为了缓和由于纠删码和副本存储模式混合使用, 以及服务器节点本身实时算力差异造成的MapReduce作业处理效率低下的问题, 本文实现了一种根据数据存储情况和节点实时负载来在多并发场景下动态调节MapReduce作业任务分配情况的调度策略. 该策略通过修改当前Hadoop框架中的数据存储选址策略并对节点任务并发量进行动态控制, 在多作业并发时实现更加均衡的作业间资源分配. 实验结果表明, 相较于Hadoop默认的两种作业调度策略, 本文提出的调度模式能够将作业完成时间缩短约17%, 并有效避免部分作业面临的饥饿现象.     

煤矿井下安全监控分站的设计及其仿真实现

为了设计一种具有低成本、低功耗、易操作、功能强且可靠性高的煤矿井下安全分站,针对煤矿安全生产实际,文章提出了采用MCS-51系列单片机为核心、具有CAN总线通信接口的煤矿井下安全监控分站的设计方案;首先给出煤矿井下安全监控分站的整体构架设计,然后着重阐述模拟量输入信号处理系统的设计过程,最后说明单片机最小系统及其键盘、显示、报警、通信等各个组成部分的设计;为验证设计方案的可行性与有效性,使用Proteus软件对设计内容进行仿真验证,设计的煤矿井下安全监控分站具有瓦斯、温度等模拟量参数超标报警功能和电机开停、风门开闭等开关量指示功能;仿真结果表明:设计的煤矿井下安全监控分站具有一定的实际应用价值.     

Call for Papers The 6^th International Conference on Grid and Cooperative Computing

Recent years have seen rapid advances in various grid-related technologies, middleware, and applications. The GCC conference has become one of the largest scientific events worldwide in grid and cooperative computing. The 6th international conference on grid and cooperative computing (GCC2007) Sponsored by China Computer Federation (CCF),Institute of Computing Technology, Chinese Academy of Sciences (ICT) and Xinjiang University ,and in Cooperation with IEEE Computer Soceity ,is to be held from August 16 to 18, 2007 in Urumchi, Xinjiang, China.     

View-based model-driven architecture for enhancing maintainability of data access services

In modern service-oriented architectures, database access is done by a special type of services, the so-called data access services (DAS). Though, particularly in data-intensive applications, using and developing DAS are very common today, the link between the DAS and their implementation, e.g. a layer of data access objects (DAOs) encapsulating the database queries, still is not sufficiently elaborated, yet. As a result, as the number of DAS grows, finding the desired DAS for reuse and/or associated documentation can become an impossible task. In this paper we focus on bridging this gap between the DAS and their implementation by presenting a view-based, model-driven data access architecture (VMDA) managing models of the DAS, DAOs and database queries in a queryable manner. Our models support tailored views of different stakeholders and are scalable with all types of DAS implementations. In this paper we show that our view-based and model driven architecture approach can enhance software development productivity and maintainability by improving DAS documentation. Moreover, our VMDA opens a wide range of applications such as evaluating DAS usage for DAS performance optimization. Furthermore, we provide tool support and illustrate the applicability of our VMDA in a large-scale case study. Finally, we quantitatively prove that our approach performs with acceptable response times.     

A pragmatic multi-method investigation of discrepant technological events: Coping,attributions, and ‘accidental’ learning

Discrepant technological events or situations that entail a problem, a misunderstanding or a difficulty with the Information Technology (IT) being employed, are common in the workplace, and can lead to frustration and avoidance behaviors. Little is known, however, about how individuals cope with these events. This paper examines these events by using a multi-method pragmatic approach informed by coping theory. The results of two studies – a critical incident study and an experiment – serve to build and test, respectively, a theoretical model that posits that individuals use a variety of strategies when dealing with these events: they experience negative emotions, make external attributions, and adopt engagement coping strategies directed at solving the event, eventually switching to a disengagement coping strategy when they feel they have no control over the situation. Furthermore, users’ efforts may result in ‘accidental’ learning as they try to overcome the discrepant IT events through engagement coping. The paper ends with a discussion of the results in light of existing literature, future opportunities for research, and implications for practice.     

The Distributed Time-Triggered Simulation Scheme: Core Principles and Supporting Execution Engine

Distributed real-time simulation is a young technology field but its practice is under increasing demands. In recent years the author and his collaborators have been establishing a new approach called the distributed time-triggered simulation (DTS) scheme which is conceptually simple and easy to use but widely applicable. The concept was initiated in the course of developing a new-generation object-oriented real-time programming scheme called the time-triggered message-triggered object (TMO) programming scheme. Some fundamental issues inherent in distributed real-time simulation that were learned during recent experimental studies are discussed along with some approaches for resolving the issues. An execution engine developed to support both the TMOs engaged in control computation and the TMOs engaged in DTS is also discussed along with its possible extensions that will enable significantly larger-scale DTSs.     

Software-Konfigurationsmanagement in großen Softwareprojekten

Zusammenfassung Mit zunehmender Größe der Softwaresysteme verschärfen sich die für die Software-Herstellung typischen Probleme: Beherrschen großer Objektmengen, Erhalten der Systemkonsistenz, Kontrolle der ständigen Änderungseinflüsse und Gewährleisten einer langen Lebensdauer. Die Disziplin Konfigurationsmanagement bildet den methodischen Ansatz, diese Probleme besser zu beherrschen. Software-Konfigurationsmanagement faßt die Herstellung von Softwaresystemen als eine Abfolge von kontrollierten Änderungen an gesicherten Zwischen- und Endergebnissen auf. Dargestellt werden die Objekte und Funktionen des Software-Konfigurationsmanagements sowie die hierfür in großen Software-Projekten benötigten Methoden, Instanzen und Hilfsmittel.     

Information for Authors

正http://www.zju.edu.cn/jzus http://www.springerlink.com Aim The Journals of Zhejiang University-SCIENCE(A/B/C)are edited by the international board of distinguished Chinese and foreign scientists,and are aimed to present the latest developments and achievements in scientific research in China and     

Editorial:Brain-machine interface(BMI) and cyborg intelligence

正Brain-machine interfaces(BMIs)aim at building a direct communication pathway between the brain and an external device,and represent an area of research where significant progress has been made during the past decade.Based on BMIs,mind information can be read out by neural signals to control     

Information for Authors

正http://www.zju.edu.cn/jzus http://www.springerlink.com Aim The Journals of Zhejiang University-SCIENCE(A/B/C)are edited by the international board of distinguished Chinese and foreign scientists,and are aimed to present the latest developments and achievements in scientific research in China and overseas to the world’s scientific circles,especially to stimulate     

SCIENCE CHINA Information Sciences SUBJECT INDEX TO VOLUME 57(2014)

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