一种高效的协调式检查点算法

为降低设置检查点的开销,提出一种高效的异步存储非阻塞协调式检查点算法。该算法允许多个进程并发地在进程状态信息量较小时设置检查点,只在稳固存储器空闲时进行异步存储,并可同时进行检查点设置及进程执行。实验结果表明,该算法能降低设置检查点的开销,提高系统性能。     

一种低开销非阻塞的协同式检查点算法

协同式检查点设置及卷回恢复技术是一种简单有效的容错手段，被广泛地运用于并行/分布式系统中。为进一步降低协同式检查点算法的开销，该文给出了一个基于可重建检查点的非阻塞协同式检查点算法。并行程序出错导致卷回恢复发生的概率远小于检查点设置概率，该算法利用这一特性，将检查点设置的部分开销转至卷回恢复阶段，降低了容错的开销，提高了系统的可扩展性。     

一种改进的同步检查点设置算法

检查点设置与卷回恢复是集群系统中容错计算的重要手段.同步检查点方法在集群系统中得到了广泛应用.为了提高集群计算系统的工作效率,降低系统的容错开销,根据基于消息驱赶的同步检查点设置算法的性质和在实际应用中并行应用程序的通信特征,通过减小协同过程中的阻塞时间,降低系统中控制消息的数量,对基于消息驱赶的Syncand-Stop算法进行优化.改进的算法有效降低检查点设置的时间和空间开销,减小在系统应用中检查点设置的代价,进一步提高系统可扩展性和应用可靠性.     

一种基于移动计算环境的因果日志卷回恢复算法

由于移动节点的不可靠和无线网络连接的脆弱性,研究移动计算系统容错机制具有重要意义.对可以跨区移动、随时可以与网络断开的自治性很强的移动节点来说,异步的卷回恢复是一种重要的容错手段.现有的移动计算环境下的卷回恢复算法都无法完全实现一致的异步卷回恢复.基于因果消息日志,提出一种新的移动计算环境的卷回恢复算法:通过先行图来记录节点间的消息依赖关系,将异步检查点、基于发送方的暂存消息日志和先行图全部在移动支持站上存储和处理,为移动节点提供一种透明的容错服务,完全消除依赖关系在移动节点之间造成的影响.用形式化的方法证明了系统的一致性.仿真结果表明,在卷回开销达到最低的同时,也显著降低了无错运行时的通信和存储开销.     

基于共享内存的机群服务检查点机制研究

针对既有基于稳定存储的机群服务检查点存在的系统成本高、恢复时间长的问题,提出了一种基于共享内存的机群服务检查点机制;设计了一套面向基于共享内存的检查点信息主-备存储模式的检查点信息管理协议,确保机群服务检查点信息一致性;设计了一套基于单向逻辑环的检查点组管理协议,确保检查点逻辑备份环中检查点进程的成员视图一致性.性能实验结果表明,该检查点机制具有较好的检查点信息读写性能,组管理协议系统开销小,较好地满足了机群服务检查点需求.     

一种基于准同步检查点的虚拟机卷回恢复算法

针对典型的云平台下虚拟化系统的特点,提出了一种结合选择性日志的准同步检查点算法VM_QSC:保持不同虚拟机节点固有的优化检查点周期,通过物理节点Hypervisor选择性地进行虚拟机的消息日志的稳定存储,在全局监控节点维护虚拟机一致线信息,保持全局的一致性。与传统的准同步检查点和同步检查点相比,该算法维持了虚拟机检查点设置的自主性,并显著降低了虚拟化系统的容错开销,可以有效应用于云计算环境下的虚拟资源管理和动态迁移。     

基于Lustre文件系统的MPI检查点系统实现技术与性能测试

基于协同式检查点的回卷恢复是在大规模并行计算机系统中得到采用的一项重要容错技术,其性能开销主要为协同协议和检查点映像存储所决定.描述了一个在MPICH2中实现的应用透明的并行检查点系统,相比已有的技术,该系统有以下特点：1）协同协议操作利用了并行应用的近邻通信特性,通过虚连接方法减少协议的处理开销;2）采用Lustre文件系统简化检查点映像文件管理的复杂性;3）通过并行I/O操作提高性能,优化检查点映像的存储过程.实际应用的测试表明,该检查点系统具有较小的运行时间开销和良好的可扩展性.     

实时分布系统中Out-Tree任务的调度与检查点策略

针对实时分布系统中的Out-Tree任务，提出了一种启发式的调度算（HSA-OT），并开发了一种多处理机上的最优检查点策略。该调度算法能够保证任务的调度长度最小，所需处理器数目尽量少，没有处理机间通信开销。该检查点策略没有检查点全局一致性开销，可保证各处理机的失效率最低。     

基于离散时间距的在线可重构任务调度算法

任务调度是影响动态可重构系统性能的重要因素.针对现有预约算法中由于维护预约资源逻辑单元信息而带来系统额外开销大、任务调度自私性等问题,提出一种基于离散时间距的非预约调度算法.算法的特点在于通过任务紧迫度和时间距信息能够动态更新任务优先级和设置任务的启动时间,从而有效避免了复杂的系统开销和任务调度的自私性.实验表明,该算法能提高任务的调度成功率,而运行时间开销没有明显增加.     

具有O(n)消息复杂度的协调检查点设置算法

协调检查点设置及回卷恢复技术作为一种有效的容错手段,已广泛地运用在集群等并行/分布计算机系统中.为了进一步降低协调检查点设置的时间和空间开销,提出了一种基于消息计数的协调检查点设置算法.该算法无须对底层消息通道的FIFO特性进行假设,并使同步阶段引入的控制消息复杂度由通常的O(n2)降低到O(n),有效地提高了系统的效率和扩展性.     

Utility-based QoS optimisation strategy for multi-criteria scheduling on the grid

The paper presents quality of service (QoS) optimisation strategy for multi-criteria scheduling on the grid, based on a mathematical QoS model and a distributed iterative algorithm. Three QoS criteria are considered, namely payment, deadline and reliability, which are formulated as utility function. The optimisation problem is split into two parts: task optimisation performed on behalf of the user and resource optimisation performed on behalf of the grid. The strategy employs three types of agents: task agents responsible for task optimisation, computation resource and network resource agents responsible for resource optimisation. The agents apply economic models for optimisation purposes. Dynamic programming is used to optimise the total system utility function in terms of an iterative algorithm. The objective of multi-criteria scheduling is to maximise the global utility of the system. This paper proposes an iterative scheduling algorithm that is used to perform QoS optimisation-based multi-criteria scheduling. The proposed QoS optimisation-based multi-criteria scheduling problem solution has been practically examined by simulation experiments.     

Controlling energy without compromising system performance in mobile grid environments

The challenges confronting in mobile grid systems are: limited CPU power, limited memory, small screen, short battery life, and intermittent disconnection. Considering all these limitations, this paper is targeted to control energy consumption without compromising system’s performance in mobile grid. In this paper, we focus on using the mobile devices on the mobile grid environment. Mobile devices can serve two important functions in mobile grid environment either as service consumer or as valuable service providers. The proposed approach is not only to reduce energy consumption, but also to improve system performance in mobile grid environment. Utility functions are used to express grid users’ requirements, resource providers’ benefit function and system’s objectives. Dynamic programming is used to optimize the total utility function of mobile grid. A distributed controlling energy algorithm in mobile grid environment is proposed which decomposes mobile grid system optimization problem into sub-problems. In order to verify the efficiency of the proposed algorithm, in the experiment, the performance evaluation of controlling energy algorithm is conducted.     

基于代理的网格计算中间件

WADE系统是基于代理技术实现的一个可屏蔽异构和分布性的动态自适应的校园计算网格，提出了基于代理技术在校园网络内实现并行计算的方法，详细论述了基于代理的网格计算中间件的体系结构和主要模块功能，阐述了利用代理实现异构编译、协同计算的过程，给出了代理的Java实现方法，利用软件代理实现网格计算中间件，可以解决异构计算平台下多种并行编程环境的协同计算问题，为用户提供统一的服务接口，这将大大增强系统的可用性。     

Collaboration among mobile agents for efficient energy allocation in mobile grid

The use of mobile devices in grid environments may have two interaction aspects: devices are considered as users of grid resources or as grid resources providers. Due to the limitation constraints on energy and processing capacity of mobile devices, their integration into the Grid is difficult. In this paper, we investigate the cooperation among mobile devices to balance the energy consumption and computation workloads. Mobile devices can have different roles such as buyer devices and seller devices. In the mobile grid, the energies of mobile devices are uneven, energy-poor devices can exploit other devices with spare energy. Our model consists of two actors: A buyer device agent represents the benefits of mobile buyer device that intends to purchase energy from other devices. A seller device agent represents the profits of mobile seller device that is willing to sell spare energy to other devices. The objective of optimal energy allocation in mobile grid is to maximize the utility of the system without exceeding the energy capacity, expense budget and the deadline. A collaboration algorithm among mobile agents for efficient energy allocation is proposed. In the simulation, the performance evaluation of collaboration algorithm among mobile agents is conducted.     

烟草移动服务GIS 简易网格监控系统

由于常州烟草一线员工流动性大、工作任务弹性大、绩效成果难以直接衡量,对他们的监控和管理是日常管理中的难点和重点。GIS网格具有丰富的展现、智能、实时、可靠、效果好等优点。明确基于GIS网格技术对一线移动服务监控的必要性,然后进行了系统功能的描述和总体设计,提出了简易GIS网格的实现算法,并对实时监控、网格任务分析、网格绩效分析等系统进行了详细设计。     

Adaptive Execution of Jobs in Computational Grid Environment

In a computational grid, jobs must adapt to the dynamically changing heterogeneous environment with an objective of maintaining the quality of service. In order to enable adaptive execution of multiple jobs running concurrently in a computational grid, we propose an integrated performance-based resource management framework that is supported by a multi-agent system (MAS). The multi-agent system initially allocates the jobs onto different resource providers based on a resource selection algorithm. Later, during runtime, if performance of any job degrades or quality of service cannot be maintained for some reason (resource failure or overloading), the multi-agent system assists the job to adapt to the system. This paper focuses on a part of our framework in which adaptive execution facility is supported. Adaptive execution facility is availed by reallocation and local tuning of jobs. Mobile, as well as static agents are employed for this purpose. The paper provides a summary of the design and implementation and demonstrates the efficiency of the framework by conducting experiments on a local grid test bed.     

逆模型下的高效声源定位算法研究

与波束形成算法相比,广义互相关逆模型宽带声源定位算法提供了空间的高分辨率,但需要更高的计算量。为了提升广义互相关逆模型算法的计算效率,并尽可能保留其分辨率优势,本文提出了一种高效的声源定位算法。该算法首先去除麦克风阵列输出功率较小的网格点来压缩计算网格,其次,在几何因素条件下利用基于密度的聚类进一步压缩网格,最后仅用保留下的点进行计算,从而大大降低了计算规模。真实数据实验证明,本文所提算法能有效提升广义互相关逆模型算法的计算效率。     

Integrate software agents and CORBA in computational grid

This paper presents an Agent-based Computational Grid (ACG), which applies the concept of CORBA and agent to computational grid. The ACG system is used to implement a uniform higher level management of the computing resources and services on the Grid, and provide users with a consistent and transparent interface for accessing such services. In ACG grid, grid services are implemented by CORBA or by grid agent. Grid agents and CORBA objects will interact with each other to achieve user's service request. Our solution is the creation of a bridge between the CORBA and grid agents. The solution provides with the opportunity of considering an agent as a CORBA service and accessing CORBA services even from a grid agent. Thus, in AGC grid, existing legacy systems can be easily exploited as grid services. In this paper, firstly, the features of ACG grid are described, and then the design and implementation are given. Finally, some conclusions are given.     

Tradeoffs between energy consumption and QoS in mobile grid

Mobile grid, which combines grid and mobile computing, supports mobile users and resources in a seamless and transparent way. However, mobility, QoS support, energy management, and service provisioning pose challenges to mobile grid. The paper presents a tradeoff policy between energy consumption and QoS in the mobile grid environment. Utility function is used to specify each QoS dimension; we formulate the problem of energy and QoS tradeoff by utility optimization. The work is different from the classical energy aware scheduling, which usually takes the consumed energy as the constraints; our utility model regards consumed energy as one of the components of measure of the utility values, which indicates the tradeoff of application satisfaction and consumed energy. It is a more accurate utility model for abstracting the energy characteristics and QoS requirement for mobile users and resources in mobile grid. The paper also proposes a distributed energy–QoS tradeoff algorithm. The performance evaluation of our energy–QoS tradeoff algorithm is evaluated and compared with other energy and deadline constrained scheduling algorithm.