计算网格的资源聚集算法研究

使用备份资源是提高计算网格可用性的重要方法,而资源聚集是选择备份资源的前提。本文对文献[1]中提出的资源聚集算法进行了改进,降低了算法的复杂性,并使得资源聚集更易于实现。     

面向服务网络的Web服务可用性研究

在以服务为中心的下一代互联网络中，Web服务常常会由于节点的动态产生和消失而导致服务的可用性受到影响，如何有效地组织广域网的Web服务从而形成可用的候选服务集合，并在服务可用度不高时有效地进行服务的复制与备份以提高服务的可用性是面向服务网络需要解决的重要问题。文章提出了一种可扩展、动态自适应的高可用性服务模型——HighServer，该模型按Web服务间的关系聚集成多个服务集合，每个服务集合采用生成树的方式组织，根据服务的可用性需求为每个服务集合确定备份服务的数量，分析证明了模型的有效性，并给出了该算法的一个实例。     

基于遗传算法的资源结点选择策略

网格系统中由于采用资源备份策略，资源存在多个副本。用户请求资源时，如何从拥有相同资源的多个结点中选择一部分结点获取资源，达到以相同的代价获得最优质的服务，是一个迫切需要研究的问题。文中综合用户和资源拥有者双方的利益因素，将该问题归结为一个多目标规划问题，并提出了资源动态复制的图模型，进而运用遗传算法，提出了解决该问题的策略，分析显示该算法可以达到满意的结果。     

基于资源角色分类的密集计算网格作业管理

对密集计算网格的资源进行角色分类，采用了基于作业优先级和资源优先级的作业调度算法，设计和实现了网格作业管理模块，为用户提供了一个有效的网格资源的使用方法，实现了对网格资源的优化使用，为网格用户提供了更好的网格资源服务共享。     

一个容错的网格资源选择算法

芝加哥大学提出了一个网格资源选择算法,能够同时满足单一资源选择和多个资源选择的要求。但是,由于算法一开始就选择了资源集合中单机最强的节点,所以很容易陷入局部最优,且算法不具备容错能力。针对这种情况,本文对该算法进行改进,提出了基于基版本／副版本技术的容错资源选择算法。模拟实验表明,算法是有效的。     

一种基于GMA结构的开放式网格资源信息服务

网格是把广域网上大量分布、异构资源进行整合，实现统一视图和统一访问接口的基础设施．资源信息服务在网格中具有重要地位，其作用是感知和监控异构资源，并为上层应用提供资源信息，从而为资源调度和选择系统策略提供依据．传统的主机监控不能适用于网格，现有的网格资源信息服务也存在一定缺点．通过分析网格资源信息服务的一般要求，针对现有系统的不足，基于GGF提出的GMA体系结构，从几个不同方面提出了更适合网格特点，开放性和互操作性较好的改进方案，最后，一方面对资源信息服务的性能策略进行了讨论和理论分析，另一方面以目前实现的原型系统GridEye为基础，进行了资源信息服务的性能测试实验，并对结果进行了分析．     

基于WSRF的集合预报任务调度系统

分析集合预报的任务特点,基于Web服务资源框架(WSRF)设计一种动态自适应的集合预报任务调度系统。给出任务调度算法,根据网格节点的资源变化自适应地选择节点,为每对初值样本的模式预报任务指派CPU资源数目,以缩短预报时间、节省计算成本。实际运行结果验证了该系统的可行性。     

DPSO算法在服务网格资源调度中的应用

服务网格结合了Web服务技术和网格技术,代表了应用网格的发展方向.在这类网格中,有大量的应用在运行,这些应用又共享网格的各种资源,资源优化调度能使这些应用获得最大的性能,也是影响网格计算能否成功的最重要的因素之一.在建立服务网格资源调度数学模型的基础上,应用离散微粒群优化算法(DPSO),在给定约束下寻找服务网格环境下资源和任务问的最优的映射关系,达到资源优化调度的目的.通过MATLAB进行模拟仿真实验,验证了该方法的可行性.     

计算网格应用可用性的度量模型

计算网格是很容易变化的不可靠的计算环境，因此如何保证应用的可用性成为构建网格系统的关键问题之一，而首先要解决的问题是如何对计算网格的可用性进行度量，分析了计算网格可用性的特征，提出从应用的角度度量计算网格可用性的方法，并设计了一种度量计算网格中应用可用性的模型，在这一模型中，应用的可用性用一个串行RBD来描述，每个网格结点上运行的应用的任务的可用性用概率模型描述，以此模型为基础，首先分析了在计算网格中影响应用可用性的关键因素，之后讨论了该度量模型在构建计算网格高可用服务体系结构中的应用。     

基于遗传算法的资源结点选择策略

网格系统中由于采用资源备份策略,资源存在多个副本.用户请求资源时,如何从拥有相同资源的多个结点中选择一部分结点获取资源,达到以相同的代价获得最优质的服务,是一个迫切需要研究的问题.文中综合用户和资源拥有者双方的利益因素,将该问题归结为一个多目标规划问题,并提出了资源动态复制的图模型,进而运用遗传算法,提出了解决该问题的策略,分析显示该算法可以达到满意的结果.     

一种带回馈机制的新型网格资源发现算法的研究

网格资源发现算法是网格资源发现机制的核心,传统的分布式资源发现算法通常只关注正向搜索的成功率,反向的响应报文仅仅用来向资源申请者报告搜索成功与否.本文提出了一种带回馈机制的新型网格资源发现算法,该算法充分利用响应报文与请求报文可能经不同路径返回的特点,在正向搜索失败时,启动反向搜索机制,在一个往返时间里进行二次搜索.模拟实验表明该算法可以较好地提高资源发现成功率,同时并未明显增加整个系统的开销.     

Self-adjustment of resource allocation for grid applications

Grids involve coordinated resource sharing and problem solving in heterogeneous dynamic environments to meet the needs of a generation of researchers requiring large amounts of bandwidth and more powerful computational resources. The lack of resource ownership by grid schedulers and fluctuations in resource availability require mechanisms which will enable grids to adjust themselves to cope with fluctuations. The lack of a central controller implies a need for self-adaptation. Grids must thus be enabled with the ability to discover, monitor and manage the use of resources so they can operate autonomously. Two different approaches have been conceived to match the resource demands of grid applications to resource availability: Dynamic scheduling and adaptive scheduling. However, these two approaches fail to address at least one of three important issues: (i) the production of feasible schedules in a reasonable amount of time in relation to that required for the execution of an application; (ii) the impact of network link availability on the execution time of an application; and (iii) the necessity of migrating codes to decrease the execution time of an application. To overcome these challenges, this paper proposes a procedure for enabling grid applications, composed of various dependent tasks, to deal with the availability of hosts and links bandwidth. This procedure involves task scheduling, resource monitoring and task migration, with the goal of decreasing the execution time of grid applications. The procedure differs from other approaches in the literature because it constantly considers changes in resource availability, especially network bandwidth availability, to trigger task migration. The proposed procedure is illustrated via simulation using various scenarios involving fluctuation of resource availability. An additional contribution of this paper is the introduction of a set of schedulers offering solutions which differ in terms of both schedule length and computational complexity. The distinguishing aspect of this set of schedulers is the consideration of time requirements in the production of feasible schedules. Performance is then evaluated considering various network topologies and task dependencies.     

A self-adaptive Model based on Multi-Objective Programming for Grid Resource Management

Abstract : The growing computational power requirements of grand challenge applications have positioned computational grid as promising next generation computing platform.However, resource management and application with varied requirements in grid environment continue to be a complex undertaking. In order to address complex resource management issues, we provide a self-adaptive model, which is based on multi-objective programming. The model make use of virtues of market mechanism efficiently, meanwhile, the shortcomings of market mechanism, such as too frequent fluctuations of price,are avoided by means of the method of changing prices after trading. Through using atom allocation of resource group, the cooperating allocation is improved, and some problems, such as deadlock of resource and inefficiently occupying resource, are solved. What' s more important, efficiently using various resources in grid system is guaranteed through importing multi-objective programming mechanism in our resource management solution. A frame of resource allocation is given at first, then, the mathematical model of the method is constructed. An algorithm is proposed to get the approximate solution in this paper.     

计算网格中的资源选择与调度算法

针对文中描述的计算网格资源环境模型,构造了一种分布式的层次型任务调度模型,任务调度分为计算资源站点的选择以及资源站点内部的本地调度两层进行。通过研究该调度模型,提出了一种基于双目标衡量函数的资源选择算法,该算法可以通过设置相关参数动态调节响应时间和价格在总目标中所占比重。试验结果表明能够选择综合满足响应时间和价格这两个目标的计算资源,以适应用户的不同需求。     

一种自适应的网格计算资源组织与发现机制

资源发现是网格计算中一个重要的研究问题.计算资源作为支撑网格应用的基础资源,其组织与发现机制尤为重要,但现有的技术和方法在效率、可伸缩性、自适应的动态演化以及对查询方式的支持方面仍有较大的局限性.基于网格应用对计算资源需求特征的深入分析,通过引入计算资源的主属性概念,按照平衡二叉排序树对计算资源进行分类组织,提出基于资源分类树(resource category tree,简称RCT)的资源组织与发现机制.首先,讨论了基于RCT对计算资源的组织机制,包括RCT的基本概念和原理、支持资源动态加入和退出以及资源状态动态变化的自组织机制、负载感知的自适应演化机制和基于备份节点的容错机制;然后,在基于RCT的资源组织结构下,设计了支持4种查询方式的搜索算法,并对算法的复杂度进行了分析;最后,通过多组仿真实验对RCT的性能进行了评估.     

基于经济模型的资源代理

网格计算是为解决大规模资源密集型问题而提出的新一代计算平台,是当前并行和分布处理技术的一个发展方向,而资源管理是计算网格的关键技术之一。对各种各样可利用资源的整合和管理是网格应用的基础,而资源的分布性、动态性、异构性、自治性和需要协调一致性使得网格资源的管理调度成为一个棘手的问题。目前基于市场的经济资源管理和调度算法非常适合计算网格中的资源管理问题,但有调度价格不能更改、负载平衡等问题。文中提出了“网格环境下基于经济模型的资源代理”,依靠多维QoS指导的调度策略和经济模型的启发式调节资源价格,改进和优化计算网格资源的分配。     

A resource management and fault tolerance services in grid computing

In grid computing, resource management and fault tolerance services are important issues. The availability of the selected resources for job execution is a primary factor that determines the computing performance. In this paper, we propose a resource manager for optimal resource selection. Our resource manager automatically selects the set of optimal resources among candidate resources that achieves optimal performance using a genetic algorithm. Typically, the probability of a failure is higher in the grid computing than in a traditional parallel computing and the failure of resources affects job execution fatally. Therefore, a fault tolerance service is essential in computational grids. And grid services are often expected to meet some minimum levels of Quality of Service (QoS) for a desirable operation. To address this issue, we also propose a fault tolerance service that satisfies QoS requirements. We extend the definition of failures from the conventional notion of failures in distribute systems in order to provide a fault tolerance service that deals with various types of resource failures, which include process failures, processor failures, and network failures. We also design and implement a fault detector and a fault manager. The implementation and simulation results indicate that our approaches are promising in that (1) the resource manager finds the optimal set of resources that guarantees efficient job execution, (2) the fault detector detects the occurrence of resource failures and (3) the fault manager guarantees that the submitted jobs complete and the performance of job execution is improved due to job migration even if some failures occur.     

Aligning block permutation methods for topology transformation on computational grids

Many traditional parallel matrix computing algorithms are performed on regular resource topologies, such as mesh. However, the grid resource topology is often irregular in practice. In this paper, we present a transformation algorithm of grid resource topology for achieving virtual meshes. And on the virtual mesh, these traditional parallel algorithms can be performed in a modern computational grid environment. The basic idea of our topology transformation is to align the basic blocks of grid computational resources through permutations in a virtual mesh. Designing a cost function of heuristic search scheme for the transformation, we use it to fully exploit the computational and communicational abilities of grid resources. The experiment results show that our aligning block permutation can significantly reduce the time complexity of search tree. They also show that the heuristic search scheme can effectively find the block permutation that makes better use of computational and communicational abilities of grid resources.     

计算网格的资源分发和发现机制

1 引言计算网格的资源管理系统是为实现计算网格系统资源共享所应提供的最主要的服务之一。计算网格资源管理系统的基本功能是接受来自计算网格范围内的机器的资源请求,并且把特定的资源分配给资源请求者,并且合理地调度相应的资源,使请求资源的作业得以运行。资源分发、资源发现和资源的调度构成了计算网格资源管理系统的最主要的内容。资源分发和资源发现提供方法,通过该方法,在计算网格内部的机器能够形成一个可用的资源和其状态的一个视图。资源