Grid Service Orchestration Using the Business Process Execution Language (BPEL)

Modern scientific applications often need to be distributed across Grids. Increasingly applications rely on services, such as job submission, data transfer or data portal services. We refer to such services as Grid services. While the invocation of Grid services could be hard coded in theory, scientific users want to orchestrate service invocations more flexibly. In enterprise applications, the orchestration of web services is achieved using emerging orchestration standards, most notably the Business Process Execution Language (BPEL). We describe our experience in orchestrating scientific workflows using BPEL. We have gained this experience during an extensive case study that orchestrates Grid services for the automation of a polymorph prediction application. Using this example, we explain the extent with which the BPEL language supports the definition of scientific workflows. We then describe the reliability, performance and scalability that can be achieved by executing a complex scientific workflow with ActiveBPEL, an industrial strength but freely available BPEL engine. *The work has been funded by the UK EPSRC through grants GR/R97207/01 (e-Materials) and GR/S90843/01 (OMII Managed Programme).     

Performance metrics and ontologies for Grid workflows

Many Grid workflow middleware services require knowledge about the performance behavior of Grid applications/services in order to effectively select, compose, and execute workflows in dynamic and complex Grid systems. To provide performance information for building such knowledge, Grid workflow performance tools have to select, measure, and analyze various performance metrics of workflows. However, there is a lack of a comprehensive study of performance metrics which can be used to evaluate the performance of a workflow executed in the Grid. Moreover, given the complexity of both Grid systems and workflows, semantics of essential performance-related concepts and relationships, and associated performance data in Grid workflows should be well described. In this paper, we analyze performance metrics that performance monitoring and analysis tools should provide during the evaluation of the performance of Grid workflows. Performance metrics are associated with multiple levels of abstraction. We introduce an ontology for describing performance data of Grid workflows and illustrate how the ontology can be utilized for monitoring and analyzing the performance of Grid workflows.     

Campus Grids Meet Applications: Modeling, Metascheduling and Integration

Air Quality Forecasting (AQF) is a new discipline that attempts to reliably predict atmospheric pollution. An AQF application has complex workflows and in order to produce timely and reliable forecast results, each execution requires access to diverse and distributed computational and storage resources. Deploying AQF on Grids is one option to satisfy such needs, but requires the related Grid middleware to support automated workflow scheduling and execution on Grid resources. In this paper, we analyze the challenges in deploying an AQF application in a campus Grid environment and present our current efforts to develop a general solution for Grid-enabling scientific workflow applications in the GRACCE project. In GRACCE, an application’s workflow is described using GAMDL, a powerful dataflow language for describing application logic. The GRACCE metascheduling architecture provides the functionalities required for co-allocating Grid resources for workflow tasks, scheduling the workflows and monitoring their execution. By providing an integrated framework for modeling and metascheduling scientific workflow applications on Grid resources, we make it easy to build a customized environment with end-to-end support for application Grid deployment, from the management of an application and its dataset, to the automatic execution and analysis of its results.The work has been performed as part of the University of Houston’s Sun Microsystems Center of Excellence in Geosciences [38].     

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.     

The Charité Grid Portal: User-friendly and Secure Access to Grid-based Resources and Services

The Charité Grid Portal combines portal components from different groups and projects to provide domain researchers a gateway to Grid-based biomedical applications. Trusted users can securely access and employ Grid resources and services. In this paper, five portal components are presented: (1) The credential management administrates the user-credentials and authenticates them to the Grid. (2) The brain imaging data analysis (FSL) submits workflows to the Grid as part of Medical Image processing. (3) The integrated web services of Generic Workflow Execution Service (GWES) manage workflows executed by users in the Grid. (4) The data management component provides secure and efficient data management in a Grid environment, and enables high-speed data transports between user and Grid. (5) The lung sound analysis application provides twofold-pseudonymization before data-transferred to the Grid. The implementation as standardized portlets allows easy integration of specific components into different Grid portals such as the VO specific MediGRID and PneumoGrid portals.     

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.     

DynaGrid: A dynamic service deployment and resource migration framework for WSRF-compliant applications

Large-scale Grid is a computing environment composed of Internet-wide distributed resources shared by a number of applications. Although WSRF and Java-based hosting environment can successfully deal with the heterogeneity of resources and the diversity of applications, the current Grid systems have several limitations to support the dynamic nature of large-scale Grid.This paper proposes DynaGrid, a new framework for building large-scale Grid for WSRF-compliant applications. Compared to the existing Grid systems, DynaGrid provides three new mechanisms: dynamic service deployment, resource migration, and transparent request dispatching. Two core components, ServiceDoor and dynamic service launcher (DSL), have been implemented as WSRF-compliant Web services to realize DynaGrid, which are applicable to any Java-based WSRF hosting environment. We construct a real testbed with DynaGrid on the Globus Toolkit 4 and evaluate the effectiveness of our framework using two practical applications. The evaluation results show that dynamic service deployment and resource migration in DynaGrid bring many advantages to large-scale Grid in terms of performance and reliability with minimal overhead.     

Using Grid services to parallelize IBM's Generic Log Adapter

Since their definition in the Open Grid Services Architecture, Grid services has been used in many Grid-enabled applications to leverage the computational power offered by Grid Systems. An important research issue addressed in this regard is how to increase the efficiency of the Grid services for a massive processing and scientific computing computations arising in data intensive computations, for example the processing of large log data files arising in “problem determination” in today's IT computing environments.In this paper we present an approach that uses Grid services to efficiently parallelize the IBM's Generic Log Adapter (GLA). GLA is a generic parsing engine shipped with the IBM's Autonomic Computing Toolkit that has been conceived to convert proprietary log data into a standard log data event-based format in real time. However, in order to provide generic support for parsing the majority of today's unstructured log data formats the GLA makes heavy use of regular expressions that incur in performance limitations. Until now all the approaches that have been proposed to increase GLA's performance have revolved around fine-tuning the set of regular expressions used to configure the GLA for a particular log data format or writing specific parsing code. In this work we propose a new approach consisting in transparently parallelizing the GLA by taking advantage of its internal architecture and the fact that structuring log data is a task that lends itself very well to parallelization. We present a Master-Worker strategy that uses Grid services to parallelize GLA efficiently and in a completely transparent way for the user.     

基于领域本体的制造网格服务自动组合技术研究

为实现制造网格应用的自动化，提出了一个基于领域本体（ontology）的服务自动组合体系结构及其相应的算法。领域本体基于TOVE、STEP、PSL三个成熟的制造本体和网格服务概念模型构建。体系结构以语义结构良好的用户目标作为输入，输出预约的可执行工作流；通过基于领域本体推理的反向递归组合算法，能够实现本地仓库中工作流的重用和网格范围内服务的新工作流组合；支持抽象、具体两个层面的松耦合工作流组合（对应于编排（Choreography）和编制（Orchestration））；支持面向服务质量的工作流优化选择和工作流预约。实现了一个原型系统，实例的实验结果证明了该体系结构和算法的有效性。     

Trustworthy remote compiling services for grid-based scientific applications

Grid computing, which is characterized by large-scale sharing and collaboration of dynamic resources, is becoming an emerging computing platform on a global scale for data-intensive and computation-intensive scientific application. However, the complications of large-scale scientific computations and simulations harnessing massive computing resources are compounded by extensive heterogeneity in environments arising from “the Grid.” Scientists and engineers lack an intuitive grid-based compilation tool, which has contributed to the difficulty of exploiting these diverse resources and developing their applications on the grid. While manual configuration of various toolkits simplifying the end-to-end completion of a job is adequate for a computational grid with a limited number of nodes, the compilation procedure becomes inefficient for a computational grid with an increasing number of heterogeneous computational service providers. On the other hand, a global-scale computational grid is a potentially untrustworthy computing environment. How to take advantage of the potentially untrustworthy grid resources to provide trustworthy computational services for large-scale scientific applications is another critical issue. In this article, a remote compiling service for a heterogeneous computational grid is developed. In addition to running compilation tasks, the remote compiling service provides security enforcement and validation facilities, including intermediate value checking, secure source program submission, restricted compilation, and binary inspection, to support trustworthy compilation and execution of grid-based scientific applications. Overall, it is expected that our remote compiling services on the grid can tackle the heterogeneity problem of the grid and provide a secure, trustworthy, reliable, and state-of-the-art mechanism to develop grid-aware scientific applications.

Flexible Grid service management through resource partitioning

In this paper, a distributed and scalable Grid service management architecture is presented. The proposed architecture is capable of monitoring task submission behaviour and deriving Grid service class characteristics, for use in performing automated computational, storage and network resource-to-service partitioning. This partitioning of Grid resources amongst service classes (each service class is assigned exclusive usage of a distinct subset of the available Grid resources), along with the dynamic deployment of Grid management components dedicated and tuned to the requirements of a particular service class introduces the concept of Virtual Private Grids. We present two distinct algorithmic approaches for the resource partitioning problem, the first based on Divisible Load Theory (DLT) and the second built on Genetic Algorithms (GA). The advantages and drawbacks of each approach are discussed and their performance is evaluated on a sample Grid topology using NSGrid, an ns-2 based Grid simulator. Results show that the use of this Service Management Architecture in combination with the proposed algorithms improves computational and network resource efficiency, simplifies schedule making decisions, reduces the overall complexity of managing the Grid system, and at the same time improves Grid QoS support (with regard to job response times) by automatically assigning Grid resources to the different service classes prior to scheduling.     

A Taxonomy of Workflow Management Systems for Grid Computing

With the advent of Grid and application technologies, scientists and engineers are building more and more complex applications to manage and process large data sets, and execute scientific experiments on distributed resources. Such application scenarios require means for composing and executing complex workflows. Therefore, many efforts have been made towards the development of workflow management systems for Grid computing. In this paper, we propose a taxonomy that characterizes and classifies various approaches for building and executing workflows on Grids. We also survey several representative Grid workflow systems developed by various projects world-wide to demonstrate the comprehensiveness of the taxonomy. The taxonomy not only highlights the design and engineering similarities and differences of state-of-the-art in Grid workflow systems, but also identifies the areas that need further research.     

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.     

Validating and Scaling the MicroGrid: A Scientific Instrument for Grid Dynamics

Large-scale Grids that aggregate and share resources over wide-area networks present major challenges in understanding dynamic application and resource behavior for performance, stability, and reliability. Accurate study of the dynamic behavior of applications, middleware, resources, and networks depends on coordinated and accurate modeling of all four of these elements simultaneously. We have designed and implemented a tool called the MicroGrid which enables accurate and comprehensive study of the dynamic interaction of applications, middleware, resource, and networks. The MicroGrid creates a virtual Grid environment – accurately modeling networks, resources, the information services (resource and network metadata) transparently. Thus, the MicroGrid enables users, Grid researchers, or Grid operators to study arbitrary collections of resources and networks. The MicroGrid includes the MaSSF online network simulator which provides packet-level accurate, but scalable network modeling. We present experimental results with applications which validate the implementation of the MicroGrid, showing that it not only runs real Grid applications and middleware, but that it accurately models both their and underlying resource and network behavior. We also study a range of techniques for scaling a critical part of the online network simulator to the simulation of large networks. These techniques employ a sophisticated graph partitioner, and a range of edge and node weighting schemes exploiting a range of static network and dynamic application information. The best of these, profile-driven placement, scales well to online simulation of large networks of 6,000 nodes using 24 simulation engine nodes.     

On the Simulation of Grid Market Coordination Approaches

Grid computing has recently become an important paradigm for managing computationally demanding applications, composed of a collection of services. The dynamic discovery of services, and the selection of a particular service instance providing the best value out of the discovered alternatives, poses a complex multi-attribute n:m allocation decision problem, which is often solved using a central resource broker. However, decentralized approaches to this service allocation problem represent a much more flexible alternative, thus promising improvements in the efficiency of the resulting negotiations and service allocations. This paper compares centralized and decentralized service allocation mechanisms in Grid market scenarios according to a defined set of metrics.     

An overview of S-OGSA: A Reference Semantic Grid Architecture

The Grid's vision, of sharing diverse resources in a flexible, coordinated and secure manner through dynamic formation and disbanding of virtual communities, strongly depends on metadata. Currently, Grid metadata is generated and used in an ad hoc fashion, much of it buried in the Grid middleware's code libraries and database schemas. This ad hoc expression and use of metadata causes chronic dependency on human intervention during the operation of Grid machinery, leading to systems which are brittle when faced with frequent syntactic changes in resource coordination and sharing protocols.The Semantic Grid is an extension of the Grid in which rich resource metadata is exposed and handled explicitly, and shared and managed via Grid protocols. The layering of an explicit semantic infrastructure over the Grid Infrastructure potentially leads to increased interoperability and greater flexibility.In recent years, several projects have embraced the Semantic Grid vision. However, the Semantic Grid lacks a Reference Architecture or any kind of systematic framework for designing Semantic Grid components or applications. The Open Grid Service Architecture (OGSA) aims to define a core set of capabilities and behaviours for Grid systems. We propose a Reference Architecture that extends OGSA to support the explicit handling of semantics, and defines the associated knowledge services to support a spectrum of service capabilities. Guided by a set of design principles, Semantic-OGSA (S-OGSA) defines a model, the capabilities and the mechanisms for the Semantic Grid.We conclude by highlighting the commonalities and differences that the proposed architecture has with respect to other Grid frameworks.     

GEMLCA: Running Legacy Code Applications as Grid Services

There are many legacy code applications that cannot be run in a Grid environment without significant modification. To avoid re-engineering of legacy code, we developed the Grid Execution Management for Legacy Code Architecture (GEMLCA) that enables deployment of legacy code applications as Grid services. GEMLCA implements a general architecture for deploying legacy applications as Grid services without the need for code re-engineering, or even access to the source files. With GEMLCA, only a user-level understanding is required to run a legacy application from a standard Grid service client. The legacy code runs in its native environment using the GEMLCA resource layer to communicate with the Grid client, thus hiding the legacy nature of the application and presenting it as a Grid service. GEMLCA as a Grid service layer supports submitting jobs, getting their results and status back. The paper introduces the GEMLCA concept, its life cycle, design and implementation. It also presents as an example a legacy simulation code that has been successfully transformed into a Grid service using GEMLCA.     

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.