弹性Web Cache集群的自适应负载均衡策略

在Web cache集群中,Web突发请求的频繁出现引发资源供给不足,造成系统性能显著下降.为有效处理Web突发请求,构建了同时使用本地资源和云资源的弹性Web cache集群.在弹性Web cache集群中,为提升系统性能,降低费用,提出一种自适应的负载模型.该模型可以动态自适应地调整,能够有效适用于异构Web cache集群.考虑到云结点的网络延迟,修正该模型得到云结点负载模型.基于以上负载模型,构造弹性Web cache集群的自适应负载均衡策略.与其他负载均衡策略相比较,使用该自适应负载均衡策略能够在弹性Web cache集群中实现高效的负载均衡.     

高性能气象数据存储集群及在线扩展技术应用

为了满足气象数据快速增长和高效应用的业务需求,设计采用基于SAN和GPFS的高性能存储集群进行数据存储,并随着数据量的快速增长,实现灵活在线扩展以满足数据存储需求.结合国家级气象资料存储检索系统、省级风能资源数据库共享服务系统和风能资源数值模拟系统的存储设计,阐述基于SAN和GPFS技术的存储集群架构,并重点介绍存储集群的在线扩展技术的实现.基于SAN和GPFS的存储集群在线扩展技术包含在线扩展服务器节点、在线扩展存储容量和在线扩展文件系统容量三方面,实现了气象数据存储系统随着业务数据变化的灵活扩展,使系统具备优秀的扩展性和适应性.     

多层服务器集群容量规划启发方法研究

本文研究了多层服务器集群系统的容量规划问题,提出以吞吐优化为目标的增量式服务器资源配置算法SHISA.该方法基于闭环排队网络模型求解系统的稳态性能指标,利用请求队列长度、资源利用率及有效响应时间等启发信息指导服务器的增量配置过程.对不同启发信息下算法的求解能力进行了敏感性分析.     

一种基于周期性特征的数据中心在线负载资源预测方法

以Web服务、流式计算为代表的在线负载是数据中心的主要负载之一。在线负载请求到达的波动性驱动其资源需求的动态变化。因此,快速、准确的在线负载资源预测是数据中心合理分配资源、保障负载执行效率的关键。然而,既有在线负载资源预测方法或无法进行长期准确的预测,或依赖于海量样本数据并具有较大的时间开销。为此,提出了一种基于请求周期性特征的在线负载资源预测方法PRP。PRP面向在线负载请求的周期性特征,采用自相关函数识别负载资源使用的变化周期;基于变化周期进行资源使用样本序列分割及资源使用子序列分类;最终基于分类子序列采用线性加权方法预测在线负载的资源需求。实验结果表明,PRP在预测准确度和时间开销方面有较大的提升。     

基于在线负载预测的动态集群节能配置策略

动态集群配置中的调节方式大多基于特定的物理实验模型而非数学模型描述。针对上述问题,提出基于预测的动态集群配置策略,根据网络中服务请求的历史信息,采用最小均方误差预测未来时刻服务请求情况,根据负载请求与集群处理能力决定服务器规模的增减,动态调节服务器集群中计算机的开启与关断。实验结果证明了该调度策略的可行性和优越性。     

自适应称重集群系统的设计与实现

针对物流业对集群电子秤设备的称重数据自动化管理的需求,给出了一种自适应解决方案.该方案基于C320Turbo 控制器并采用自定义的通信协议和状态法的软件设计,妥善地解决了在线秤台的自由连接、称重数据的自动集群并行下载以及某秤台请求和响应等问题.该系统已投入使用,应用实践证明了其各项性能均满足设计要求.     

Web集群中基于负载均衡的QoS-aware请求调度算法

集群技术已成为目前提高网络服务质量的有效手段.集群系统的设计主要涉及任务调度与资源调度两方面,而现有的大部分算法都是只孤立地考虑其中一个方面.针对这种不足提出了一种基于负载均衡的QoS-aware请求调度算法,该算发引入一个以任务服务类别与负载为自变量的接纳概率二元函数Pa作为连接任务调度与资源调度的桥梁.Pa随着负载的增加,Pa非增变化,对于不同QoS需求的队列,Pa的变化速率不同,这样就可以达到在不同负载情况下动态地为各服务类分配带宽的目的.最后通过仿真实验验证了其正确性.     

基于Kubernetes云平台的弹性伸缩方案设计与实现

容器技术可为多个业务需求及其依赖组件提供独立的应用资源,在现实生产环境中由于容器中的业务需求不断变化,使得与其对应的应用资源在线负载处于动态变化中,面临固定资源容量规划不能满足在线负载变化的困境。为解决该问题,设计一种基于Kubernetes云平台的弹性伸缩方案。该方案通过集成Prometheus监控系统来自定义指标与采集业务指标,并结合HPA、VPA等组件,实现包括自定义指标和不同维度伸缩方法相结合的最佳弹性伸缩方法。通过集成Grafana页面显示和报警等组件,实现实时查看弹性伸缩状态变化以及伸缩预警功能,以实时观测集群健康状态,使得集群操作更加友好、便于维护。实验结果表明,在不同压力测量测试下,该弹性伸缩方案具有随负载增加扩大集群规模的作用,能够增强应用集群的高可用能力。     

一种共享存储视频服务器集群的请求调度策略

在VOD服务器集群中,对用户服务请求的合理调度是提高集群整体性能的关键技术之一.本文针对共享存储结构下的服务器机群,在请求调度算法LoadCache-rep基础上进行改进,提出一种基于视频节目点播集中度的调度策略,该策略通过将相近的点播请求调度至相同服务器上以充分利用服务器的缓存机制,同时兼顾均衡各服务器间的负载.并根据实时负载变化对请求进行迁移以消除VCR操作对负载分布的影响.仿真试验表明,该策略能有效提高视频服务器集群的运行性能.     

弹性Web Cache集群设计与实现

为在Web cache系统中实现弹性资源供给,提出了同时使用本地资源和云计算资源的弹性Web cache集群。阐述弹性Web cache集群的设计目标、功能模块、数据处理流程;实现基于Linux内核程序的弹性Web cache集群软件平台;对弹性Web cache集群进行性能测试。实验证明,弹性Web cache集群能够实现高效的负载均衡,有效处理Web突发请求和热点对象问题,显著改善系统可靠性和可用性。     

Task complexity analysis and QoS management for mapping dynamic video-processing tasks on a multi-core platform

This paper addresses efficient mapping and reconfiguration of advanced video applications onto a general purpose multi-core platform. By accurately modeling the resource usage for an application, allocation of processing resources on the platform can be based on the actually needed resources instead of a worst-case approach, thereby improving Quality-of-Service (QoS). Here, we exploit a new and strongly upcoming class of dynamic video applications based on image and content analysis for resource management and control. Such applications are characterized by irregular computing behavior and memory usage. It is shown that with linear models and statistical techniques based on the Markov modeling, a rather good accuracy (94?C97%) for predicting the resource usage can be obtained. This prediction accuracy is so good that it allows resource prediction at runtime, thereby leading to an actively controlled system management.     

Robust control reconfiguration of resource allocation systems with Petri nets and integer programming

Supervisory control reconfiguration can handle the uncertainties including resource failures and task changes in discrete event systems. It was not addressed to exploit the robustness of closed-loop systems to accommodate some uncertainties in the prior studies. Such exploitation can cost-efficiently achieve reconfigurability and flexibility for real systems. This paper presents a robust reconfiguration method based on Petri nets (PNs) and integer programming for supervisory control of resource allocation systems (RASs) subject to varying resource allocation relationships. An allocation relationship is seen as a control specification while the execution processes requiring resources as an uncontrolled plant. First, a robust reconfiguration mechanism is proposed. It includes updating the P$P$-invariant-based supervisor and evolving the state of the closed-loop system. The latter adapts to the control specification changes by the self-regulation of the closed-loop system’s state. Next, two novel integer programming models for control reconfiguration are proposed, called a reconfiguration model with acceptability and reconfiguration one with specification correction. Since both models integrate the firability condition of transitions, no additional efforts are required for the state reachability analysis. Finally, a hospital emergency service system is used as an example to illustrate them.     

一种能耗感知的虚拟集群CPU资源自动再配置方法

系统虚拟化技术可以动态再配置应用环境的计算资源.当前动态资源配置方法主要关注于保证具有动态负载应用的服务质量.这些方法受应用性能驱动并常常增加资源控制系统的响应延迟.针对上述问题提出了以资源使用状态为驱动的资源再配置方法(resource-use-status-drivenresource reconfigurationscheme,RUSiC),自动适应动态负载变化来满足应用性能的资源需求.RUSiC被设计成2层架构的资源再配置模型,基于实时的资源使用状态,及时用较小的开销为应用调整合适的资源配置.同时,RUSiC也考虑到电能的有效使用,在资源的新配置中通过尽可能减少激活物理节点的数量避免大量不必要的电能消耗及相关的冷却费用.实验数据表明,在应用负载变化时,RUSiC能快速监测并响应变化的资源需求,并在保证应用性能的前提下,使用较小数量的激活物理节点.     

Formal approach to agent-based dynamic reconfiguration in Networks-On-Chip

A Network-On-Chip (NoC) platform is an emerging topology for large-scale applications. It provides a required number of resources for critical and excessive computations. However, the computations may be interrupted by faults occurring at run-time. Hence, reliability of computations as well as efficient resource management at run-time are crucial for such many-core NoC systems. To achieve this, we utilize an agent-based management system where agents are organized in a three-level hierarchy. We propose to incorporate reallocation and reconfiguration procedures into agents hierarchy such that fault-tolerance mechanisms can be executed at run-time. Task reallocation enables local reconfiguration of a core allowing it to be eventually reused in order to restore the original performance of communication and computations. The contributions of this paper are: (i) an algorithm for initial application mapping with spare cores, (ii) a multi-objective algorithm for efficient utilization of spare cores at run-time in order to enhance fault-tolerance while maintaining efficiency of communication and computations at an adequate level, (iii) an algorithm integrating the local reconfiguration procedure and (iv) formal modeling and verification of the dynamic agent-based NoC management architecture incorporating these algorithms within the Event-B framework.     

Resource management and task partitioning and scheduling on a run-time reconfigurable embedded system

There are many design challenges in the hardware-software co-design approach for performance improvement of data-intensive streaming applications with a general-purpose microprocessor and a hardware accelerator. These design challenges are mainly to prevent hardware area fragmentation to increase resource utilization, to reduce hardware reconfiguration cost and to partition and schedule the tasks between the microprocessor and the hardware accelerator efficiently for performance improvement and power savings of the applications.In this paper a modular and block based hardware configuration architecture named memory-aware run-time reconfigurable embedded system (MARTRES) is proposed for efficient resource management and performance improvement of streaming applications. Subsequently we design a task placement algorithm named hierarchical best fit ascending (HBFA) algorithm to prove that MARTRES configuration architecture is very efficient in increased resource utilization and flexible in task mapping and power savings. The time complexity of HBFA algorithm is reduced to O(n) compared to traditional Best Fit (BF) algorithm’s time complexity of O(n²), when the quality of the placement solution by HBFA is better than that of BF algorithm. Finally we design an efficient task partitioning and scheduling algorithm named balanced partitioned and placement-aware partitioning and scheduling algorithm (BPASA). In BPASA we exploit the temporal parallelism in streaming applications to reduce reconfiguration cost of the hardware, while keeping in mind the required throughput of the output data. We balance the exploitation of spatial parallelism and temporal parallelism in streaming applications by considering the reconfiguration cost vs. the data transfer cost. The scheduler refers to the HBFA placement algorithm to check whether contiguous area on FPGA is available before scheduling the task for HW or for SW.     

Multi-level reconfigurable architectures in the switch model

In this paper, we propose a concept for multi-level reconfigurable architectures with more than two levels of reconfiguration, and study these architectures theoretically and experimentally. The proposed architectures are extensions of 2-level reconfigurable architectures where the reconfiguration operations on the lowest level correspond to the reconfiguration operations of standard 1-level reconfigurable architectures, and the reconfigurable units are simple switches. It is shown that finding an optimal number of reconfiguration levels and a corresponding reconfiguration scheme that minimizes the number of reconfiguration bits for a given algorithm can be done in polynomial time. But finding the optimal number of reconfiguration levels is NP-hard for heterogeneous multi-level architectures, where the number of reconfiguration levels varies for the different reconfigurable units. Experimental results for different test applications show that 3–4 reconfiguration levels are optimal with respect to the number of reconfiguration bits needed. The number of reconfiguration bits is reduced by 35–86% compared to 1-level reconfiguration and by 8–34% compared to 2-level reconfiguration. The heterogeneous architecture reduces the number of necessary reconfiguration bits by additional 1–5% and also needs less SRAM cells.     

Configuration Reusing in On-Line Task Scheduling for Reconfigurable Computing Systems

Reconfigurable computing systems can be reconfigured at runtime and support partial reconfigurability which makes us able to execute tasks in a true multitasking manner.To manage such systems at runtime,a reconfigurable operating system is needed.The main part of this operating system is resource management unit which performs on-line scheduling and placement of hardware tasks at runtime.Reconfiguration overhead is an important obstacle that limits the performance of on-line scheduling algorithms in reconfigurable computing systems and increases the overall execution time.Configuration reusing (task reusing) can decrease reconfiguration overhead considerably,particularly in periodic applications or the applications in which the probability of tasks recurrence is high.In this paper,we present a technique called reusing-based scheduling (RBS),for on-line scheduling and placement in which configuration reusing is considered as a main characteristic in order to reduce reconfiguration overhead and decrease total execution time of the tasks.Several experiments have been conducted on the proposed algorithm.Obtained results show considerable improvement in overall execution time of the tasks.     

基于FPGA 的局部动态可重构技术研究

可重构技术作为嵌入式系统中软硬件结合的设计方法,在可靠性、系统高集成度方面有很大优势。现场可编辑门 阵列(Field Programmable Gate Array,FPGA)不仅可以满足这些客观需求,还加强了系统的自适应性,降低了开发成本。 文章介绍了动态局部重构的实现方法,并在早期获取部分可重构(Early Access Partial Reconfiguration,EAPR)方法的基础 上加以改进。之后使用 Xilinx 生产的 Virtex-ML403 开发板实现整个设计,验证该方法的有效性,保证系统的稳定,在实 际应用的实现中有利于对资源有效的管理和合理的利用。     

Design of reconfiguration mechanism for holonic manufacturing systems based on formal models

One of the key design issues of holonic manufacturing systems (HMS) is to effectively respond to resource failures based on the flexible holonic architecture. The objective of this paper is to propose a viable design methodology to implement reconfiguration mechanism in HMS. A reconfiguration mechanism is developed to accommodate changes based on collaboration of holons without leading to chaos at the shop floor. To deal with resource failures in HMS, an impact function is defined to characterize the impact of resource failures on different holons in a holarchy. A collaborative reconfiguration mechanism based on an impact function is proposed to effectively reconfigure the systems to achieve minimal cost solutions. The design and implementation methodology combines contract net protocol for negotiation of holons, Petri net for the representation of individual product holons and resource holons and FIPA-compliant agent platform for publication/discovery of holons. A simulation system is developed to verify the proposed reconfiguration mechanism.