主动容错多副本民航存储系统状态转换模型

主动容错机制解决了被动容错冗余问题,实现了硬盘潜在故障的提前预测和主动处理,显著提高了存储系统的可靠性.然而,民航存储系统采用被动容错机制无法全面保障系统可靠性.本文利用主动容错机制的优势,基于硬盘故障预测模型构建了多副本民航存储系统状态转换模型.该模型全面考虑硬盘,节点和机架故障3个因素,采用韦布分布模拟民航存储系统事件的发生.根据系统状态转换模型,本文使用了改进的基于事件驱动的蒙特卡洛仿真方法,对民航存储系统进行了全面的可靠性分析.实验结果表明,本文模型显著提高了民航存储系统的可靠性.另外,敏感性分析得出主动和被动的结合机制有效延缓了系统可靠性下降的趋势,节约了网络带宽资源.     

主动容错副本存储系统的可靠性分析模型

主动容错机制通过预先发现即将故障的硬盘来提醒系统提前迁移备份危险数据,从而显著提高存储系统的可靠性.针对现有研究无法准确评价主动容错副本存储系统可靠性的问题,提出几种副本存储系统的状态转换模型,然后利用蒙特卡洛仿真算法实现了该模型,从而模拟主动容错副本存储系统的运行,最后统计系统在某个运行时期内发生数据丢失事件的期望次...     

一种改进的云存储系统容错机制

在云存储平台下, 提出了一种基于访问统计的自适应容错机制SFMAF, 该机制通过近似最近最少使用算法维护一张文件访问频率表来自适应调整容错方式。SFMAF对于常读取的文件采用副本冗余机制; 对于不常读取的文件采用Reed-Solomon（RS）纠删码容错机制。实验结果表明, SFMAF相对于副本冗余机制, 在CPU和内存使用率可接受范围内的增加上, 减少了系统内部数据的传输流量, 即减少了系统存储空间。     

云存储系统的分析与应用研究

云存储系统是随着社会的发展应运而生的,在人们的生活中发挥着越来越重要的作用。本研究将向大家介绍云存储系统的一些基本概念,并针对其应用提更好的解决方案。     

一个容错计算机的固态存储系统的设计与实现

本文叙述了三模冗余容错计算机固态存储系统的设计和实现，它具有可靠性高、容量大、速度快、重量轻、轻耗低等特点，它解决了容错机的数据的可靠存储和转发处理问题。     

图书馆云存储系统中一种自适应容错策略

云存储的优势吸引着越来越多的图书馆采用云存储解决馆藏数字资源的存储需求。但随着海量数据的增长,云存储节点的失效概率越来越大。单一的容错策略,如单一的复制或纠删码,不可避免地存在一些缺点,不能满足当今容错技术的需要。因此,根据馆藏文献访问的频率和大小,提出了一种自适应切换的容错策略,该策略可以在整个生命周期中动态地选择复制方案或纠删码方案。实验结果表明,该方案较单一复制策略节约了43%的存储空间,较单一纠删码策略提升了52%的节点故障恢复时间。     

云存储系统节能研究综述

云存储系统作为云计算的重要组成部分,是各种云计算服务的基础。但随云存储系统规模的不断扩大和在设计时对能耗因素的忽略,使其日益暴露出高能耗、低效率的问题。因为云存储系统占整个云计算中心能耗的27%～40%,所以无论从降低服务提供商的运营成本,还是从降低能耗以保护环境的角度出发,研究云存储系统中的节能技术都具有很大的现实意义与应用前景。将存储系统中的能耗优化问题分为基于硬件的节能方法与基于调度的节能方法两大类进行讨论;并将基于调度的节能方法分为基于节点调度、基于数据调度和基于缓存预取技术3类进行综合比较;最后,对适应节能的云存储体系结构、节能模式下的QoS保证、节能模式与计算模式的匹配以及纠删码容错技术下的节能研究4个方向进行了展望。     

增强云存储系统安全功能的方法探讨

我国计算机技术快速发展的过程中,云计算属于互联网中较为有效的计算形式,目前已经开始应用到中小企业、个人用户的领域中,能够系统化整合互联网资源,为用户提供相应的网络服务,充分利用既有的计算资源按照用户需求分配资源,服务质量较为良好.云存储系统属于云计算技术中的重要部分,可以根据用户需求进行各种资源的存储,服务商可以借助实...     

非线性系统主动容错控制综述

以故障发生部位为分类视角,分别从传感器故障、执行器故障及其他部件故障3个方面,较为详细地对近5年非线性系统主动容错控制的研究进展情况进行了归纳和总结,重点讨论了执行器故障的容错控制问题,并对所存在的问题与未来的发展趋势进行了探讨。     

基于多模型切换的智能主动容错控制方法研究

针对某些具有可能故障先验知识的非线性系统,采用主动容错控制方法,基于神经网络对系统正常及各种先验故障情形建模,并采用基于神经网络的PID控制方法离线整定出各种故障模式下的控制律,由此建立模型库;在系统实时运行时,依据系统性能容忍度指标和模型失配度指标的计算分析,判断系统所处运行模式,切换与该模式匹配的控制律,从而达到系统主动容错控制的目的.最后将所提出的主动容错控制方法应用于某一非线性系统和线性系统,仿真结果表明了方法的有效性.     

Cost-oriented proactive fault tolerance approach to high performance computing (HPC) in the cloud

Cloud computing offers new computing paradigms, capacity and flexible solutions to high performance computing (HPC) applications. For example, Hardware as a Service (HaaS) allows users to provide a large number of virtual machines (VMs) for computation-intensive applications using the HaaS model. Due to the large number of VMs and electronic components in HPC system in the cloud, any fault during the execution would result in re-running the applications, which will cost time, money and energy. In this paper we presented a proactive fault tolerance (FT) approach to HPC systems in the cloud to reduce the wall-clock execution time and dollar cost in the presence of faults. We also developed a generic FT algorithm for HPC systems in the cloud. Our algorithm does not rely on a spare node prior to prediction of a failure. We also developed a cost model for executing computation-intensive applications on HPC systems in the cloud. We analysed the dollar cost of provisioning spare nodes and checkpointing FT to assess the value of our approach. Our experimental results obtained from a real cloud execution environment show that the wall-clock execution time and cost of running computation-intensive applications in cloud can be reduced by as much as 30%. The frequency of checkpointing of computation-intensive applications can be reduced up to 50% with our FT approach for HPC in the cloud compared with current FT approaches.     

ReliaCloud‐NS: A scalable web‐based simulation platform for evaluating the reliability of cloud computing systems

This paper discusses the implementation, architecture, and use of a graphical web‐based application called ReliaCloud‐NS that allows users to (1) evaluate the reliability of a cloud computing system (CCS) and (2) design a CCS to a specified reliability level for both public and private clouds. The software was designed with a RESTful application programming interface for performing nonsequential Monte Carlo simulations to perform reliability evaluations of a CCS. Simulation results are stored and presented to the user in the form of interactive charts and graphs from within a web browser. The software contains multiple types of CCS components, simulations, and virtual machine allocation schemes. ReliaCloud‐NS also contains a novel feature that evaluates CCS reliability across a range of varying virtual machine allocations and establishes and graphs a CCS reliability curve. This paper discusses the software architecture, the interactive web‐based interface, and the different types of simulations available in ReliaCloud‐NS and presents an overview of the results generated from a simulation.     

公有云存储系统性能评测方法研究

随着云存储系统的迅速发展和广泛使用,许多企业开发者和个人用户将其应用从传统存储迁移至公有云存储系统,因此,云存储系统性能成为企业开发者和个人用户关注的焦点。由于传统测试难以模拟足够多的用户同时访问云存储系统;测试环境构建复杂,测试时间长,准备测试环境成本高;受网络因素及外界其他因素影响,评测结果不稳定。针对以上所述云存储系统性能评测的重点和难点,提出一种“云测试云”的公有云存储系统性能评测方法,该方法通过在云计算平台动态申请足够数量的实例,对公有云存储系统性能进行评测。首先,构建通用的性能评测框架,可动态伸缩申请实例,自动化部署评测工具及负载,控制并发访问云存储系统,自动释放实例及收集并反馈评测结果;其次,提出多维度的性能评测指标,涵盖不同典型应用、不同云存储接口;最后,提出一种可扩展通用的性能评测模型,该模型可以评测常见典型应用的性能,分析云存储性能影响因素,可适用于任何的公有云存储平台。为了验证该方法的可行性、合理性、通用性和可扩展性,利用所提方法对Amazon S3云存储系统进行性能评测,并使用s3cmd验证评测结果的准确性。实验结果表明,评测结果可以为企业开发者和个人用户提供参考意见。     

支持容错QoS的高效分布式文件存储算法

针对现有存储算法无法兼顾文件定制化可靠性保证和系统良好可扩展性这一问题,提出一种全分布式的支持容错QoS(Quality of Service)的文件存储算法。算法允许文件被存储副本数量与其可靠性需求相匹配,无单一故障点与瓶颈点。此外,实验结果表明算法可保持节点间负载均衡,实现系统资源的高效利用。     

AutoProc: An automatic proactive replication scheme for P2P storage

Due to the prevalence of peer departures, P2P storage systems need to constantly generate replicas for high durability. However, few existing systems are able to select the right replication rate that balances replication cost and durability, e.g., minimizing replication cost without threatening the durability target. In this paper, we propose a method called AutoProc to automate the replication process in P2P storage systems. AutoProc employs two key techniques to enable cost-effective replication: correct...     

A self-learning fuzzy approach for proactive resource provisioning in cloud environment

The development of a communication infrastructure has made possible the expansion of the popular massively multiplayer online games. In these games, players all over the world can interact with one another in a virtual environment. The arrival rate of new players to the game environment causes fluctuations and players always expect services to be available and offer an acceptable service-level agreement (SLA), especially in terms of response time and cost. Cloud computing emerged in the recent years as a scalable alternative to respond to the dynamic changes of the workload. In massively multiplayer online games applications, players are allowed to lease resources from a cloud provider in an on-demand basis model. Proactive management of cloud resources in the face of workload fluctuations and dynamism upon the arrival of players are challenging issues. This paper presents a self-learning fuzzy approach for proactive resource provisioning in cloud environment, where key is to predict parameters of the probability distribution of the incoming players in each period. In addition, we propose a self-learning fuzzy autoscaling decision-maker algorithm to compute the proper number of resources to be allocated to each tier in the massively multiplayer online games by applying the predicted workload and user SLA. We evaluate the effectiveness of the proposed approach under real and synthetic workloads. The experimental results indicate that the proposed approach is able to allocate resources more efficiently than other approaches.     

含混合储能微网对配电网可靠性的影响

混合储能可快速平滑微网中分布式电源出力的随机性,从而提升配电网可靠性。提出了一种基于网络划分的蒙特卡洛模拟法,定量研究了含混合储能微网对配电网可靠性的影响。首先建立蓄电池与超级电容组成的混合储能系统模型并制定其充放电策略;在设备发生故障后,根据系统区域划分和负荷削减模型,确定负荷停电原则,采用序贯蒙特卡洛模拟法计算可靠性指标。以改进的IEEE RBTS BUS6系统为算例,对比分析了不同储能方式的微网接入前后的系统可靠性指标,结果表明：含混合储能微网接入配电网,能提高配电网供电的可靠性。     

存储网络自适应容错技术研究

随着网络应用的普及,企业迫切需要构建高可用的存储网络系统。针对此种情况,在研究复杂存储网络高可用系统结构的基础上,设计一种面向恢复的自适应复制协议(ROARP),该协议优于现有的复制协议,能适用于各种复杂的存储网络系统。     

一种云存储系统中重复数据删除机制

基于现有重复数据删除策略,提出了一种基于负载均衡的C/S双端延迟重复数据删除方法.利用基于类型的数据分块方法将数据块分成若干块;利用MD5提取指纹值,与客户端本地的索引表对比指纹,若相同则用指针取代该数据块,具有数据块指纹和数据类型的索引表一同发送至控制器;控制器在收到客户端的请求后,首先根据自己实时监控得到的各服务器的当前状态来选择最佳目标存储节点;服务器端根据数据类型查询不同的索引表以缩小查找范围.对提出的方法的重复数据删除率进行了实验验证,结果表明该机制具有较好的性能表现.