一种基于CCM构件模型的计算网格平台

如何聚合网络中分布异构的计算资源来解决大规模的科学计算问题,和如何减少并行程序设计的复杂性,一直是网格计算研究的难点之一。文章提出了一种基于CORBA构件技术的计算网格新思想,构造了一个计算网格的模型(CCGM)。该模型能够充分地利用构件技术带来的可组装和易管理的特性来形成网格计算。并通过问题的抽象定义和使用ParIDL工具将问题的定义映射到CCGM之上,简化了计算网格应用的开发。通过测试和分析CCG(ComponentbasedComputationalGrid)系统,表明CCG系统具有较好的加速比。     

GMarte: Grid middleware to abstract remote task execution

Grid computing technologies are now being largely deployed with the widespread adoption of the Globus Toolkit as the industrial standard Grid middleware. However, its inherent steep learning curve discourages the use of these technologies for non‐experts. Therefore, to increase the use of Grid computing, it is important to have high‐level tools that simplify the process of remote task execution. In this paper we introduce a middleware, developed on top of the Java Commodity Grid, which offers an object‐oriented, user‐friendly application programming interface, from the Java language, which eases remote task execution for computationally intensive applications. Copyright © 2006 John Wiley & Sons, Ltd.     

A Grid-based Virtual Reactor: Parallel performance and adaptive load balancing

We address the problem of porting parallel distributed applications from static homogeneous cluster environments to dynamic heterogeneous Grid resources. We introduce a generic technique for adaptive load balancing of parallel applications on heterogeneous resources and evaluate it using a case study application: a Virtual Reactor for simulation of plasma chemical vapour deposition. This application has a modular architecture with a number of loosely coupled components suitable for distribution over the Grid. It requires large parameter space exploration that allows using Grid resources for high-throughput computing. The Virtual Reactor contains a number of parallel solvers originally designed for homogeneous computer clusters that needed adaptation to the heterogeneity of the Grid. In this paper we study the performance of one of the parallel solvers, apply the technique developed for adaptive load balancing, evaluate the efficiency of this approach and outline an automated procedure for optimal utilization of heterogeneous Grid resources for high-performance parallel computing.     

GridBLAST: a Globus‐based high‐throughput implementation of BLAST in a Grid computing framework

Improvements in the performance of processors and networks have made it feasible to treat collections of workstations, servers, clusters and supercomputers as integrated computing resources or Grids. However, the very heterogeneity that is the strength of computational and data Grids can also make application development for such an environment extremely difficult. Application development in a Grid computing environment faces significant challenges in the form of problem granularity, latency and bandwidth issues as well as job scheduling. Currently existing Grid technologies limit the development of Grid applications to certain classes, namely, embarrassingly parallel, hierarchical parallelism, work flow and database applications. Of all these classes, embarrassingly parallel applications are the easiest to develop in a Grid computing framework. The work presented here deals with creating a Grid‐enabled, high‐throughput, standalone version of a bioinformatics application, BLAST, using Globus as the Grid middleware. BLAST is a sequence alignment and search technique that is embarrassingly parallel in nature and thus amenable to adaptation to a Grid environment. A detailed methodology for creating the Grid‐enabled application is presented, which can be used as a template for the development of similar applications. The application has been tested on a ‘mini‐Grid’ testbed and the results presented here show that for large problem sizes, a distributed, Grid‐enabled version can help in significantly reducing execution times. Copyright © 2005 John Wiley & Sons, Ltd.     

Grid Computing in China

Grid computing presents a new trend to distributed computation and Internet applications, which can construct a virtual single image of heterogeneous resources, provide uniform application interface and integrate widespread computational resources into super, ubiquitous and transparent aggregation. In the adoption of Grid computing, China, who is facing more resource heterogeneity and other specific demands, has put much effort on both research and practical utilization. In this paper, we introduce the major China Grid research projects and their perspective applications. First we give the overview of the four government-sponsored programs in Grid, namely the China National Grid, ChinaGrid, NSFC Grid, and ShanghaiGrid. Then we present six representative ongoing Grid systems in details, which are categorized into Grid middleware and Grid application. This paper provides the general picture of Grid computing in China, and shows the great efforts, devotion and confidence in China to use Grid technology to boost the society, economics and scientific research.     

A Pricing Mechanism for Resource Management in Grid Computing

We consider the problem of efficient resource allocation in a grid computing environment. Grid computing is an emerging paradigm that allows the sharing of a large number of a heterogeneous set of resources. We propose an auction mechanism for decentralized resource allocation. The problem is modeled as a multistage stochastic programming problem. Convergence of the auction allocations to the social optimum is established. Numerical experiments illustrate the efficacy of the method.     

Introduce: An Open Source Toolkit for Rapid Development of Strongly Typed Grid Services

Service-oriented architectures and applications have gained wide acceptance in the Grid computing community. A number of tools and middleware systems have been developed to support application development using Grid Services architectures. Most of these efforts, however, have focused on low-level support for management and execution of Grid services, management of Grid-enabled resources, and deployment and execution of applications that make use of Grid services. Simple-to-use service development tools, which would allow a Grid service developer to leverage Grid technologies without needing to know low-level details, are becoming increasingly important for wider application of the Grid. In this paper, we describe an open-source, extensible toolkit, called Introduce, that supports easy development and deployment of Web Services Resource Framework (WSRF) compliant services. Introduce is designed to reduce the service development and deployment effort by hiding low level details of the Globus Toolkit and to enable the implementation of strongly typed services. In strongly typed services, a service produces and consumes data types that are well-defined and published in the Grid. This enables data-level syntactic interoperability so that clients and services can access and consume data elements programmatically and correctly. We expect that enabling strongly typed Grid services while lowering the difficulty of entry to the Grid via toolkits like Introduce will have a major impact to the success of the Grid and its wider adoption as a viable technology of choice in the commercial sector as well as in academic, medical, and government research.     

网格计算的研究新进展

网格计算诞生了一个全新的领域,它以大规模的资源协作共享、创新的应用以及高性能计算的特点,区别于传统的分布式计算。文章简述了网格计算的定义、特点、功能和基本体系结构,重点综述了网格的研究新进展及其商业化应用前景,分析了当前网格研究的发展趋势及其我国的对策。     

Dynamicity in distributed applications: issues, problems and the ASSIST approach

Dynamic reconfiguration refers to the ability of changing properties and structure of a distributed system, while it is running. It is essential when designing applications that need to adapt to unpredictable events, run on non-dedicated environments; for which configuration cannot be statically determined, or may change at runtime. Grid computing also gave new emphasis to the topic, being based on dynamic environments by definition. The first part of this work tries to give a definite organization to known literature and existing experiments, providing a general overview of the problem. Then we describe our approach to dynamicity in the context of the ASSIST programming environment and show how it is able to provide users with many of the required abstractions to develop adaptive, high-performance, distributed applications.     

Achieving efficiency, quality of service and robustness in multi-organizational Grids

Scalability, flexibility, quality of service provisioning, efficiency and robustness are the desired characteristics of most computing systems. Although the emerging Grid computing paradigm is scalable and flexible, achieving both efficiency and quality of service provisioning in Grids is a challenging task but is necessary for the wide adoption of Grids. Grid middleware should also be robust to uncertainties such as those in user-estimated runtimes of Grid applications. In this paper, we present a complete middleware framework for Grids that achieves user satisfaction by providing QoS guarantees for Grid applications, cost effectiveness by efficiently utilizing resources and robustness by intelligently handling uncertain runtimes of applications.     

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.     

Labs of the World, Unite!!!

eScience is rapidly changing the way we do research. As a result, many research labs now need non-trivial computational power. Grid and voluntary computing are well-established solutions for this need. However, not all labs can effectively benefit from these technologies. In particular, small and medium research labs (which are the majority of the labs in the world) have a hard time using these technologies as they demand high visibility projects and/or high-qualified computer personnel. This paper describes OurGrid, a system designed to fill this gap. OurGrid is an open, free-to-join, cooperative Grid in which labs donate their idle computational resources in exchange for accessing other labs’ idle resources when needed. It relies on an incentive mechanism that makes it in the best interest of participants to collaborate with the system, employs a novel application scheduling technique that demands very little information, and uses virtual machines to isolate applications and thus provide security. The vision is that OurGrid enables labs to combine their resources in a massive worldwide computing platform. OurGrid is in production since December 2004. Any lab can join it by downloading its software from .     

Integrating Computing Resources on Multiple Grid-Enabled Job Scheduling Systems Through a Grid RPC System

We present a framework for a parallel programming model by remote procedure calls, which bridge large-scale computing resource pools managed by multiple Grid-enabled job scheduling systems. With this system, the user can exploit not only remote servers and clusters, but also the computing resources provided by Grid-enabled job scheduling systems located on different sites. This framework requires a Grid remote procedure call (RPC) system to decouple the computation in a remote node from the Grid RPC mechanism and uses document-based communication rather than connection-based communication. We implemented the proposed framework as an extension of the OmniRPC system, which is a Grid RPC system for parallel programming. We designed a general interface to easily adapt the OmniRPC system to various Grid-enabled job scheduling systems, including XtremWeb, CyberGRIP, Condor and Grid Engine. We show the preliminary performance of these implementations using a phylogenetic application. We found that the proposed system can achieve approximately the same performance as OmniRPC and can handle interruptions in worker programs on remote nodes. Yoshihiro Nakajima is a Research Fellow of the Japan Society for the Promotion of Science     

Enhanced Dynamic Hierarchical Replication and Weighted Scheduling Strategy in Data Grid

The Data Grid provides massive aggregated computing resources and distributed storage space to deal with data-intensive applications. Due to the limitation of available resources in the grid as well as production of large volumes of data, efficient use of the Grid resources becomes an important challenge. Data replication is a key optimization technique for reducing access latency and managing large data by storing data in a wise manner. Effective scheduling in the Grid can reduce the amount of data transferred among nodes by submitting a job to a node where most of the requested data files are available. In this paper two strategies are proposed, first a novel job scheduling strategy called Weighted Scheduling Strategy (WSS) that uses hierarchical scheduling to reduce the search time for an appropriate computing node. It considers the number of jobs waiting in a queue, the location of the required data for the job and the computing capacity of the sites Second, a dynamic data replication strategy, called Enhanced Dynamic Hierarchical Replication (EDHR) that improves file access time. This strategy is an enhanced version of the Dynamic Hierarchical Replication strategy. It uses an economic model for file deletion when there is not enough space for the replica. The economic model is based on the future value of a data file. Best replica placement plays an important role for obtaining maximum benefit from replication as well as reducing storage cost and mean job execution time. So, it is considered in this paper. The proposed strategies are implemented by OptorSim, the European Data Grid simulator. Experiment results show that the proposed strategies achieve better performance by minimizing the data access time and avoiding unnecessary replication.     

QoS guided Min-Min heuristic for grid task scheduling

Task scheduling is an integrated component of computing.With the emergence of Grid and ubiquitous computing,new challenges appear in task scheduling based on properties such as security,quality of service,and lack of central control within distributed administrative domains.A Grid task scheduling framework must be able to deal with these issues.One of the goals of Grid task scheduling is to achivev high system throughput while matching applications with the available computing resources.This matching of resources in a non-deterministically shared heterogeneous environment leads to concerns over Quality of Service (QoS).In this paper a novel QoS guided task scheduling algorithm for Grid computing is introduced.The proposed novel algorithm is based on a general adaptive scheduling heuristics that includes QoS guidance.The algorithm is evaluated within a simulated Grid environment.The experimental results show that the nwe QoS guided Min-Min heuristic can lead to significant performance gain for a variety of applications.The approach is compared with others based on the quality of the prediction formulated by inaccurate information.     

Grid Economics in Departmentalized Enterprises

The application of Grid technology is finally spreading from engineering and natural science-related industrial sectors to other industries with a high demand for computing applications. However, the diffusion of Grid technology within these sectors is often hindered by a lack of the incentive to share the computational resources across departments or branches even within the same enterprise. A promising way of overcoming these barriers is the introduction of a pricing mechanism for the use of Grid-based resources. This work introduces such a pricing approach to Grid computing and provides three simulation scenarios to illustrate the effectiveness of such an economized Grid solution. The simulation results indicate that the pooling of information technology resources can produce a reduction of 33% in cost compared to individual and dedicated servers. However, with a price-based allocation of computing resources, a further 10% of cost reduction can be achieved by introducing an auction mechanism. Therefore we claim that there is huge cost reduction potential in departmentalized enterprises beyond the savings that can be achieved by a utility-based allocation of computing resources, if economically measured allocation methods are combined with advanced refining and learning methods in the allocation process.     

Experimenting Active Reliable Multicast on Application-Aware Grids

The ever growing needs for computation power and accesses to critical resources have launched in a very short time a large number of grid projects and many realizations have been done on dedicated network infrastructures. On Internet-based infrastructures, however, there are very few distributed or interactive applications (MPI, DIS, HLA, remote visualization) because of insufficient end-to-end performances (bandwidth, latency, for example) to support such an interactivity. For the moment, computing resources and network resources are viewed separately in the Grid architecture and we believe this is the main bottleneck for achieving end-to-end performances. In this paper, we promote the idea of a Grid infrastructure able to adapt to the applications needs and thus define the idea of application-aware Grid infrastructures where the network infrastructure is tightly involved in both the communication and processing process. We report on our early experiences in building application-aware components based on active networking technologies for providing a low latency and a low overhead multicast framework for applications running on a computational Grid. Performance results from both simulations and implementation prototypes confirm that introducing application-aware components at specific location in the network infrastructure can succeed in providing not only performances for the end-users but also new perspectives in building a communication framework for computational Grids.     

Bioinformatics algorithm development for Grid environments

A Grid environment can be viewed as a virtual computing architecture that provides the ability to perform higher throughput computing by taking advantage of many computers geographically dispersed and connected by a network. Bioinformatics applications stand to gain in such a distributed environment in terms of increased availability, reliability and efficiency of computational resources. There is already considerable research in progress toward applying parallel computing techniques on bioinformatics methods, such as multiple sequence alignment, gene expression analysis and phylogenetic studies. In order to cope with the dimensionality issue, most machine learning methods either focus on specific groups of proteins or reduce the size of the original data set and/or the number of attributes involved. Grid computing could potentially provide an alternative solution to this problem, by combining multiple approaches in a seamless way. In this paper we introduce a unifying methodology coupling the strengths of the Grid with the specific needs and constraints of the major bioinformatics approaches. We also present a tool that implements this process and allows researchers to assess the computational needs for a specific task and optimize the allocation of available resources for its efficient completion.     

Studying protein folding on the Grid: experiences using CHARMM on NPACI resources under Legion

One benefit of a computational Grid is the ability to run high‐performance applications over distributed resources simply and securely. We demonstrated this benefit with an experiment in which we studied the protein‐folding process with the CHARMM molecular simulation package over a Grid managed by Legion, a Grid operating system. High‐performance applications can take advantage of Grid resources if the Grid operating system provides both low‐level functionality as well as high‐level services. We describe the nature of services provided by Legion for high‐performance applications. Our experiences indicate that human factors continue to play a crucial role in the configuration of Grid resources, underlying resources can be problematic, Grid services must tolerate underlying problems or inform the user, and high‐level services must continue to evolve to meet user requirements. Our experiment not only helped a scientist perform an important study, but also showed the viability of an integrated approach such as Legion's for managing a Grid. Copyright © 2004 John Wiley & Sons, Ltd.     

REMUS: A Rerouting and Multiplexing System for Grid Connectivity Across Firewalls

The Grid provides unique opportunities for high-performance computing through distributed applications that execute over multiple remote resources. Participating institutions can form a virtual organization to maximize the utilization of collective resources as well as to facilitate collaborative projects. However, there are two design aspects in distributed environments like the Grid that can easily clash: security and resource sharing. It may be that resources are secure but are not entirely conducive to resource sharing, or networks are wide open for resource sharing but sacrifice security as a result. We developed REMUS, a rerouting and multiplexing system that provides a compromise through connection rerouting and wrappers. REMUS reroutes connections using proxies, ports and protocols that are already authorized across firewalls, avoiding the need to make new openings through the firewalls. We also encapsulate applications within wrappers, transparently rerouting the connections among Grid applications without modifying their programs. In this paper, we describe REMUS and the tests we conducted across firewalls using two Grid middleware case studies: Globus Toolkit 2.4 and Nimrod/G 3.0.