The Legion support for advanced parameter-space studies on a grid

Parameter-space (p-space) studies involve running a single application several times with different parameter sets. Since the jobs are mutually independent, many computing resources can be recruited to conduct an entire study in a distributed manner. The p-space studies are attractive applications for grids, which are networked collections of computing and other resources. Legion is a grid infrastructure that facilitates the secure and easy use of heterogeneous, geographically distributed resources by providing the illusion of a single virtual machine from those resources. Legion provides tools and services that support advanced p-space studies, i.e., studies that make complex demands such as transparent access to distributed files, fault-tolerance and security. We demonstrate these benefits with a protein-folding experiment in which a molecular simulation package was run over a grid managed by Legion.     

Service selection and workflow mapping for Grids: an approach exploiting quality‐of‐service information

The advent of heterogeneous and distributed environments, such as Grid environments, made feasible the solution to computational‐intensive problems in a reliable and cost‐effective manner. In parallel, workflows with increased complexity that require specialized systems to deal with them are emerging, so as to carry out more composite and mission‐critical applications. In that rationale, quality‐of‐service (QoS) issues need to be tackled in order to ensure that each application satisfies the corresponding user requirements. Therefore, considering the quality provision aspect as fundamental for enabling Grid applications to become QoS compliant, we present an approach for service selection using QoS criteria. The latter is achieved with a suite of components that allow the different mappings of application workflow processes to Grid services that not only meet the user goals and requirements but also maximize his/her benefit in terms of the offered QoS level. We also demonstrate the operation of the aforementioned suite of components and evaluate its performance and effectiveness using a Grid scenario, based on a 3D image rendering application. Copyright © 2008 John Wiley & Sons, Ltd.     

Enhancing grid security by fine-grained behavioral control and negotiation-based authorization

Nowadays, Grid has become a leading technology in distributed computing. Grid poses a seamless sharing of heterogeneous computational resources belonging to different domains and conducts efficient collaborations between Grid users. The core Grid functionality defines computational services which allocate computational resources and execute applications submitted by Grid users. The vast models of collaborations and openness of Grid system require a secure, scalable, flexible and expressive authorization model to protect these computational services and Grid resources. Most of the existing authorization models for Grid have granularity to manage access to service invocations while behavioral monitoring of applications executed by these services remains a responsibility of a resource provider. The resource provider executes an application under a local account, and acknowledges all permissions granted to this account to the application. Such approach poses serious security threats to breach system functionality since applications submitted by users could be malicious. We propose a flexible and expressive policy-driven credential-based authorization system to protect Grid computational services against a malicious behavior of applications submitted for the execution. We split an authorization process into two levels: a coarse-grained level that manages access to a computational service; and a fine-grained level that monitors the behavior of applications executed by the computational service. Our framework guarantees that users authorized on a coarse-grained level behave as expected on the fine-grained level. Credentials obtained on the coarse-grained level reflect on fine-grained access decisions. The framework defines trust negotiations on coarse-grained level to overcome scalability problem, and preserves privacy of credentials and security policies of, both, Grid users and providers. Our authorization system was implemented to control access to the Globus Computational GRAM service. A comprehensive performance evaluation shows the practical scope of the proposed system.

A national-scale authentication infrastructure

Participants in virtual organizations commonly need to share resources such as data archives, computer cycles, and networks, resources usually available only with restrictions based on the requested resource's nature and the user's identity. Thus, any sharing mechanism must have the ability to authenticate the user's identity and determine whether the user is authorized to request the resource. Virtual organizations tend to be fluid, however, so authentication mechanisms must be flexible and lightweight, allowing administrators to quickly establish and change resource-sharing arrangements. Nevertheless, because virtual organizations complement rather than replace existing institutions, sharing mechanisms cannot change local policies and must allow individual institutions to maintain control over their own resources. Our group has created and deployed an authentication and authorization infrastructure that meets these requirements: the Grid Security Infrastructure (I. Foster et al., 1998). GSI offers secure single sign-ons and preserves site control over access policies and local security. It provides its own versions of common applications, such as FTP and remote login, and a programming interface for creating secure applications. Dozens of supercomputers and storage systems already use GSI, a level of acceptance reached by few other security infrastructures.     

使用GPDK实现网格门户的开发

开放网格服务体系结构(OGA)是基于网格和Web服务领域的概念和技术。门户是访问高性能计算机系统上的服务的用户界面。使用GPDK(Grid Portal Development Kit)可以方便地构造Web界面。本文给出了一个模拟复杂流体运动的实验网格系统。在该系统中，门户是在GPDK平台上设计的。     

Workflow Concepts of the Java CoG Kit

Many scientific simulations and experiments require the coordination of numerous tasks posed by interdisciplinary research teams. Grids can provide access to the necessary high-end resources to conduct such tasks. The complex tasks and their interactions must be supported through convenient tools. To address this issue, we introduce a number of Grid abstractions that make the development of Grid middleware-independent tools possible and allow for the integration of a number of commodity tools. Our vision is implemented through an integrated approach based on a layered architecture that bridges the gap between Grid middleware and scientific applications. Our abstractions include specialized services, a Grid workflow engine and language, and Gridfaces – graphical abstractions that can be employed in science portals and standalone applications.     

Searching for Software on the EGEE Infrastructure

Several large-scale Grid infrastructures are currently in operation around the world, federating an impressive collection of computational resources, a wide variety of application software, and hundreds of user communities. To better serve the current and prospective users of Grid infrastructures, it is important to develop advanced software retrieval services that could help users locate software components suitable to their needs. In this paper, we present the design and implementation of Minersoft, a distributed, multi-threaded harvester for application software located in large-scale Grid infrastructures. Minersoft crawls the sites of a Grid infrastructure, discovers installed software resources, annotates them with keyword-rich metadata, and creates inverted indexes that can be used to support full-text software retrieval. We present insights derived from the implementation and deployment of Minersoft on EGEE, one of the largest Grid production services currently in operation. Experimental results show that Minersoft achieves a high performance in crawling EGEE sites and discovering software-related files, and a high efficiency in supporting software retrieval.     

Enhancing Availability of Grid Computational Services to Ubiquitous Computing Applications

The Grid is an integrated infrastructure that can play the dual roles of a coordinated resource consumer as well as a donator in distributed computing environments. The enormous growth in the use of mobile and embedded devices in ubiquitous computing environment and their interaction with human beings produces a huge amount of data that need to be processed efficiently anytime anywhere. However, such devices often have limited resources in terms of CPU, storage, battery power, and communication bandwidth. Thus, there is a need to transfer ubiquitous computing application services to more powerful computational resources. In this paper, we investigate the use of the Grid as a candidate for provisioning computational services to applications in ubiquitous computing environments. In particular, we present a competitive model that describes the possible interaction between the competing resources in the Grid Infrastructure as service providers and ubiquitous applications as subscribers. The competition takes place in terms of quality of service (QoS) and cost offered by different Grid Service Providers (GSPs). We also investigate the job allocation of different GSPs by exploiting the noncooperativeness among the strategies. We present the equilibrium behavior of our model facing global competition under stochastic demand and estimate guaranteed QoS assurance level by efficiently satisfying the requirement of ubiquitous application. We have also performed extensive experiments over Distributed Parallel Computing Cluster (DPCC) and studied overall job execution performance of different GSPs under a wide range of QoS parameters using different strategies. Our model and performance evaluation results can serve as a valuable reference for designing appropriate strategies in a practical grid environment.     

Survey on Grid Resource Allocation Mechanisms

Grid is a distributed high performance computing paradigm that offers various types of resources (like computing, storage, communication) to resource-intensive user tasks. These tasks are scheduled to allocate available Grid resources efficiently to achieve high system throughput and to satisfy user requirements. The task scheduling problem has become more complex with the ever increasing size of Grid systems. Even though selecting an efficient resource allocation strategy for a particular task helps in obtaining a desired level of service, researchers still face difficulties in choosing a suitable technique from a plethora of existing methods in literature. In this paper, we explore and discuss existing resource allocation mechanisms for resource allocation problems employed in Grid systems. The work comprehensively surveys Gird resource allocation mechanisms for different architectures (centralized, distributed, static or dynamic). The paper also compares these resource allocation mechanisms based on their common features such as time complexity, searching mechanism, allocation strategy, optimality, operational environment and objective function they adopt for solving computing- and data-intensive applications. The comprehensive analysis of cutting-edge research in the Grid domain presented in this work provides readers with an understanding of essential concepts of resource allocation mechanisms in Grid systems and helps them identify important and outstanding issues for further investigation. It also helps readers to choose the most appropriate mechanism for a given system/application.     

Neural network‐based multi‐agent approach for scheduling in distributed systems

A distributed system consists of a collection of autonomous heterogeneous resources that provide resource sharing and a common platform for running parallel compute‐intensive applications. The different application characteristics combined with the heterogeneity and performance variations of the distributed system make it difficult to find the optimal set of needed resources. When deployed, user applications are usually handled by application domain experts or system administrators who depending on the infrastructure provide a scheduling strategy for selecting the best candidate resource over a set of available resources. However, the provided strategy is usually generic, aimed at handling a wide array of applications and does not take into consideration specific application resource requirements. As such, an intelligent method for selecting the best resources based on expert knowledge is needed. In this paper, we propose a neural network‐based multi‐agent resource selection technique capable of mimicking the services of an expert user. In addition, to cope with the geographical distribution of the underlying system, we employ a multi‐agent coordination mechanism. The proposed neural network‐based scheduling framework combined with the multi‐agent intelligence is a unique approach to efficiently deal with the resource selection problem. Results run on a simulated environment show the efficiency of our proposed method. Several scheduling simulations were conducted to compare the performance of some conventional resource selection methods against the proposed agent‐based neural network technique. The results obtained indicate that the agent‐based approach outperformed the classical algorithms by reducing the amount of time required to search for suitable resources irrespective of the resource size. Copyright © 2016 John Wiley & Sons, Ltd.     

Distributed computing with Triana on the Grid

In this paper, we describe Triana, a distributed problem‐solving environment that makes use of the Grid to enable a user to compose applications from a set of components, select resources on which the composed application can be distributed and then execute the application on those resources. We describe Triana's current pluggable architecture that can support many different modes of operation by the use of flexible writers for many popular Web service choreography languages. We further show, that the Triana architecture is middleware‐independent through the use of the Grid Application Toolkit (GAT) API and demonstrate this through the use of a GAT binding to JXTA. We describe how other bindings being developed to Grid infrastructures, such as OGSA, can seamlessly be integrated within the current prototype by using the switching capability of the GAT. Finally, we outline an experiment we conducted using this prototype and discuss its current status. Copyright © 2005 John Wiley & Sons, Ltd.     

Autonomic oil reservoir optimization on the Grid

The emerging Grid infrastructure and its support for seamless and secure interactions is enabling a new generation of autonomic applications where the application components, Grid services, resources, and data interact as peers to manage, adapt and optimize themselves and the overall application. In this paper we describe the design, development and operation of a prototype of such an application that uses peer‐to‐peer interactions between distributed services and data on the Grid to enable the autonomic optimization of an oil reservoir. Copyright © 2005 John Wiley & Sons, Ltd.     

网格环境下基于服务的分布式查询处理机制研究

OGSA-DQP是一种用于网格环境、基于服务的分布式查询处理系统,实现了运行在不同平台的分布式数据密集型应用的高级数据访问与集成服务方法,为用户提供一致的虚拟关系数据视图和分布式数据查询支持。文章描述了其体系结构、分析了其查询和优化机制,并在不同条件下测试了查询性能,为寻找系统查询性能瓶颈、提高系统查询响应时间提供依据。     

Designing a resource broker for heterogeneous grids

Grids provide uniform access to aggregations of heterogeneous resources and services such as computers, networks and storage owned by multiple organizations. However, such a dynamic environment poses many challenges for application composition and deployment. In this paper, we present the design of the Gridbus Grid resource broker that allows users to create applications and specify different objectives through different interfaces without having to deal with the complexity of Grid infrastructure. We present the unique requirements that motivated our design and discuss how these provide flexibility in extending the functionality of the broker to support different low‐level middlewares and user interfaces. We evaluate the broker with different job profiles and Grid middleware and conclude with the lessons learnt from our development experience. Copyright © 2007 John Wiley & Sons, Ltd.     

一个基于QoS的网格编程方法

网格环境下的程序设计方法是当前研究的难点之一。网格服务的概念很好地屏蔽了网格资源的异构性,其提供统一的接口便于构建网格上的虚拟组织。基于QoS（Quality of Service）的服务使得为网格计算构建经济模型成为可能。考虑到BSP（Bulk—Synchronous Parallelism）并行计算模型具有程序性能可预测的优点和多Agent技术在开放环境中的灵活性,提出了网格环境下的Service BSP程序设计方法。该方法有助于网格服务相互协同,为开发可预测时间和经济开销的网格应用提供了可能．     

Management of a parameter sweep for scientific applications on cluster environments

The GEOsciences Network (GEON, www.geongrid.org ) is a large‐scale collaborative cyberinfrastructure project involving information technology and geoscience researchers from multiple institutions. The GEON infrastructure provides portal, middleware, and data resources to facilitate scientific discovery for domain scientists using applications, tools, and services. It consists of both a service‐oriented Web/Grid framework and application toolkits, using the Web service and portlet programming model to represent applications. Based on those grid environments, we have developed the SYNSEIS (SYNthetic SEISmogram) tool within the GEON infrastructure to support personalized experiments in seismology. In this paper, we present an overview of SYNSEIS from a user point of view, and demonstrate how one can use a simple management scheme to perform a parameter sweep and distribute the work in computational resources, using a scientific application that was not specifically designed to perform parameter sweeps. The performance advantages to be gained by using this scheme with scientific codes for dealing with a large number of jobs on computational grids are very substantial. In particular, we identify the earthquake simulations in the SYNSEIS tool as an example application that can benefit from running jobs on computational resources and subsequently promote the sharing of computational resources among partner sites involved in the GEON project. Finally, we also discuss the parallel scaling behavior of our primary earthquake simulation application. Copyright © 2010 John Wiley & Sons, Ltd.     

Earth Observation application development based on the Grid oriented ESIP satellite image processing platform

Satellite images supply important information on earth surface, weather, clime, geographic areas, vegetation, and natural phenomena. Processing of satellite data requires high computation resources and flexible tools in order to search, discover, and reveal the main information, to experiment new algorithms, and to include them into new Earth Observation applications. This paper describes the features and the architectures of the ESIP and gProcess platforms, supporting the Grid based satellite imagery processing. The development methodology of Earth Observation applications is highlighted as well in order to hide the Grid complexity to the user.     

Earth Observation application development based on the Grid oriented ESIP satellite image processing platform

Satellite images supply important information on earth surface, weather, clime, geographic areas, vegetation, and natural phenomena. Processing of satellite data requires high computation resources and flexible tools in order to search, discover, and reveal the main information, to experiment new algorithms, and to include them into new Earth Observation applications. This paper describes the features and the architectures of the ESIP and gProcess platforms, supporting the Grid based satellite imagery processing. The development methodology of Earth Observation applications is highlighted as well in order to hide the Grid complexity to the user.     

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.