上海网格中间件中基于负载平衡的调度框架

在网格环境中,实现动态的负载平衡在服务调度中起到了非常关键的作用。然而,网格环境中的资源的动态性决定了它难以被监控,自治性又决定了它难以被集中管理。为在网格中间件中实现服务调度的负载平衡,提供了一些具有参考价值的解决方案。介绍设计和实现调度框架的动机以及需要解决的问题,并深入探讨在上海网格中间件中设计和实现调度框架的思路,以及达到动态负载平衡的具体方案。     

基于人工免疫的网格资源任务调度算法

目前,网格计算作为一种新的计算范式正在兴起。资源调度是其中的一个重要研完领域。该文以AIS的克隆选择算法为基础,给出了基于人工免疫系统的网格资源调度算法。首先,对网格资源任务调度问题给出了形式化描述,随后用结构化的语言对算法进行了说明,最后通过仿真实验对算法的有效性以及算法参数对性能的影响进行了验证。     

基于Web的网格系统的实现

介绍了一种基于Web的网格系统的实现，并阐述了网格中使用的关键技术，提出了网格资源分级管理与全局调度的思想。     

基于中间件的校园网格应用探讨

对高等院校的校园网格应用进行了分析,提出了一个基于网格技术的校园网格的框架。     

基于双层中间件的网格数据库访问与集成

网格数据库访问与集成是网格数据库重要的研究领域.研究该领域的主要有全球网格论坛(Global Grid Forum,GGF)中的数据库访问与集成服务工作组(Database Access and Integration Services Working Group,DAIS-WG)和合作编程工作的小组OGSA-DAI(Open Grid Services Architecture-Data Access and Integration),此外还有其他一些研究组织.本文设计了一种基于双层中间件的数据库集成和访问模型(AIGD-DMMS).     

计算网格的中间件

因特网的出现使得数以千万计的各种类型的计算机连接组成一个集成的分布式系统,从而可以为科学计算、商业、教育及信息服务、娱乐等提供大量的应用服务。但人们一直用因特网只进行电子邮件及软件等的通信和信息检索,很少使用它进行真正意义上的计算。随着先进的网络技术特别是高速网络技术和先进的计算结构的出现,使得有可能建造一个大规模的高性能分布式计算环境——计算网格。     

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。     

网格计算中基于信任机制的动态任务调度

提出了一种基于信任机制的动态任务调度模型,该模型通过MDS（Monitoring and Discovery Service）和NWS（Network Weather Service）组件完成资源信息的收集与反馈,并借鉴现实人类社会中人与人之间的信任关系模型引入信任机制,对数据存储系统采用DSRL(Dynamic Self adaptive distributed Replica Location)方法,对出错节点上的任务采用动态迁移方法。在任务调度策略中对Min min算法进行改进,提出了基于信任机制的Trust Min min算法,提高了网格计算的有效性。最后,采用SimGrid工具包对该模型和算法进行了仿真,验证了算法的合理性和高效性。     

混合算法在网格任务调度中的应用研究

研究网格任务优化调度问题,针对需求的复杂和网格系统具有异构性和动态性,导致网络任务调度过程相当困难.传统调度算法调度效率低、资源负载不平衡.为了提高任务调度效率,降低资源负载不平衡性,提出一种混合的网格任务调度优化算法.首先采用遗传算法全局搜索能力快速形成初始解,然后将遗传算法的调度结果作为蚁群算法的初始信息素分布,最后利用蚁群算法所正反馈性机制迅速地形成任务调度的最优解.仿真结果表明,混合算法减少网格任务调度系统任务完成时间,提高了任务调度效率,为网格设计提供了依据.     

基于OGSA网格的分层式网格任务调度器设计

文章根据网格任务调度的需求、网格任务调度的特点,在充分分析一般网格任务调度的过程等的基础上,另外考虑到了网格计算环境的一些特点,比如虚拟化、分层次及自治的本质特征,以及在工作流任务协同需求下网格任务的资源依赖、粗粒度、重复执行等特性的前提下,改进设计了一种网格工作流任务主从式分层调度模型,并给出了调度策略和调度算法实现。该调度器模型在实际的网格工作流任务协同系统中得到了较好的应用效果。     

Programming Grid Applications with GRID Superscalar

The aim of GRID superscalar is to reduce the development complexity of Grid applications to the minimum, in such a way that writing an application for a computational Grid may be as easy as writing a sequential application. Our assumption is that Grid applications would be in a lot of cases composed of tasks, most of them repetitive. The granularity of these tasks will be of the level of simulations or programs, and the data objects will be files. GRID superscalar allows application developers to write their application in a sequential fashion. The requirements to run that sequential application in a computational Grid are the specification of the interface of the tasks that should be run in the Grid, and, at some points, calls to the GRID superscalar interface functions and link with the run-time library.GRID superscalar provides an underlying run-time that is able to detect the inherent parallelism of the sequential application and performs concurrent task submission. In addition to a data-dependence analysis based on those input/output task parameters which are files, techniques such as file renaming and file locality are applied to increase the application performance. This paper presents the current GRID superscalar prototype based on Globus Toolkit 2.x, together with examples and performance evaluation of some benchmarks.     

Research of Grid Middleware Based on P-S

Study the technology of grid middleware based on P-S, and illustrates the interrelated-technical question in details,such as term-matching, location-transparency and fault-tolerance., so get better availability, flexibility and extendibility of the application.     

P-GRADE: A Grid Programming Environment

P-GRADE provides a high-level graphical environment to develop parallel applications transparently both for parallel systems and the Grid. P-GRADE supports the interactive execution of parallel programs as well as the creation of a Condor, Condor-G or Globus job to execute parallel programs in the Grid. In P-GRADE, the user can generate either PVM or MPI code according to the underlying Grid where the parallel application should be executed. PVM applications generated by P-GRADE can migrate between different Grid sites and as a result P-GRADE guarantees reliable, fault-tolerant parallel program execution in the Grid. The GRM/PROVE performance monitoring and visualisation toolset has been extended towards the Grid and connected to a general Grid monitor (Mercury) developed in the EU GridLab project. Using the Mercury/GRM/PROVE Grid application monitoring infrastructure any parallel application launched by P-GRADE can be remotely monitored and analysed at run time even if the application migrates among Grid sites. P-GRADE supports workflow definition and co-ordinated multi-job execution for the Grid. Such workflow management can provide parallel execution at both inter-job and intra-job level. Automatic checkpoint mechanism for parallel programs supports the migration of parallel jobs inside the workflow providing a fault-tolerant workflow execution mechanism. The paper describes all of these features of P-GRADE and their implementation concepts.     

基于OGSA的网格编程技术

目前,网格技术作为一种新的计算范式正在兴起。网格论坛组织提出的OGSA正成为网格应用的通用和标准化的体系结构,其核心就是网格服务,它是Web Service和网格技术的结合。本文对该体系结构进行了概述,并对网格程序的编写模式进行了归纳和总结。     

一种网格环境下的多级资源调度策略

网格计算是近年来得到快速发展的技术,其目标是把因特网整合成一种超大规模的巨大计算机系统,以实现各种资源的全面共享,阐述了网格调度的基本概念,分析了各种资源调度策略,并提出一种基于分布式调度算法的多级资源调度策略。通过对模拟仿真实验中三种技术指标的分析,表明了该算法的高效性。     

A Secure Grid Medical Data Manager Interfaced to the gLite Middleware

The medical community is producing and manipulating a tremendous volume of digital data for which computerized archiving, processing and analysis is needed. Grid infrastructures are promising for dealing with challenges arising in computerized medicine but the manipulation of medical data on such infrastructures faces both the problem of interconnecting medical information systems to Grid middlewares and of preserving patients’ privacy in a wide and distributed multi-user system. These constraints are often limiting the use of Grids for manipulating sensitive medical data. This paper describes our design of a medical data management system taking advantage of the advanced gLite data management services, developed in the context of the EGEE project, to fulfill the stringent needs of the medical community. It ensures medical data protection through strict data access control, anonymization and encryption. The multi-level access control provides the flexibility needed for implementing complex medical use-cases. Data anonymization prevents the exposure of most sensitive data to unauthorized users, and data encryption guarantees data protection even when it is stored at remote sites. Moreover, the developed prototype provides a Grid storage resource manager (SRM) interface to standard medical DICOM servers thereby enabling transparent access to medical data without interfering with medical practice.     

Ninf-G: A Reference Implementation of RPC-based Programming Middleware for Grid Computing

GridRPC, which is an RPC mechanism tailored for the Grid, is an attractive programming model for Grid computing. This paper reports on the design and implementation of a GridRPC programming system called Ninf-G. Ninf-G is a reference implementation of the GridRPC API which has been proposed for standardization at the Global Grid Forum. In this paper, we describe the design, implementations and typical usage of Ninf-G. A preliminary performance evaluation in both WAN and LAN environments is also reported. Implemented on top of the Globus Toolkit, Ninf-G provides a simple and easy programming interface based on standard Grid protocols and the API for Grid Computing. The overhead of remote procedure calls in Ninf-G is acceptable in both WAN and LAN environments.     

网格环境下基于启发式智能算法的任务调度研究

网格环境中的资源和任务情况异常复杂,因此计算任务在各种资源之间的调度成为了一个关键的问题,启发式智能算法被证明是解决这类问题的有效算法.本文提出将遗传算法和改进的蚂蚁算法融合起来解决网格环境下的任务调度.