Anthony Edward Mayer

ICENI: An Open Grid Service Architecture Implemented with Jini

The move towards Service Grids, where services are composed to meet the requirements of a user community within constraints specified by the resource provider, present many challenges to service provision and description. To support our research activities in the autonomous composition of services to form a Semantic Service Grid we describe the adoption within ICENI of web services to enable interoperability with the recently proposed Open Grid Services Architecture.

ICENI: optimisation of component applications within a Grid environment

Effective exploitation of Computational Grids can only be achieved when applications are fully integrated with the Grid middleware and the underlying computational resources. Fundamental to this exploitation is information. Information about the structure and behaviour of the application, the capability of the computational and networking resources, and the availability and access to these resources by an individual, a group or an organisation.In this paper we describe Imperial College e-Science Networked Infrastructure (ICENI), a Grid middleware framework developed within the London e-Science Centre. ICENI is a platform-independent framework that uses open and extensible XML derived protocols, within a framework built using Java and Jini, to explore effective application execution upon distributed federated resources. We match a high-level application specification, defined as a network of components, to an optimal combination of the currently available component implementations within our Grid environment, by using composite performance models. We demonstrate the effectiveness of this architecture through the high-level specification and solution of a set of linear equations by automatic and selection of optimal resources and implementations.

Making the Grid Predictable through Reservations and Performance Modelling

Unpredictable job execution environments pose a significant barrier to the widespread adoption of the Grid paradigm, because of the innate risk of jobs failing to execute at the time specified by the user. We demonstrate that predictability can be enhanced with a supporting infrastructure consisting of three parts: Performance modelling and monitoring, scheduling which exploits application structure and an advanced reservation resource management service. We prove theoretically that execution times using advanced reservations display less variance than those without. We also show that the costs of advanced reservations can be reduced by providing the system with more accurate performance models. Following the theoretical discussion, we describe the implementation of a fully functional workflow enactment framework that supports advanced reservations and performance modelling thereby providing predictable execution behavior. We further provide experimental results confirming our theoretical models.

Meaning and Behaviour in Grid Oriented Components

The ICENI middleware utilises information captured within a component based application in order to facilitate Grid-based scheduling. We describe a system of application related meta-data that features a separation of concerns between meaning, behaviour and implementation, which allows for both communication and implementation selection at run-time, while providing the user with a flow-based programming model. It is shown that this separation enables a flexible approach to scheduling, and eases the integration of components with disparate control flow patterns or data types, by means of converters and tees for collective communication. By explicitly recording application information and supporting multiple scheduling approaches, communication protocols and component applications, while retaining OGSA compatibility, the ICENI component model is ideally suited to Grid computing.

Optimisation of component-based applications within a grid environment

Effective exploitation of computational grids can only be achieved when applications are fully integrated with the grid middleware and the underlying computational resources. Fundamental to this exploitation is information. Information about the structure and behaviour of the application, the capability of the computational and networking resources, and the availability and access to these resources by an individual, a group or an organisation.This paper describes an integrated grid environment that is open, extensible and platform independent. We match a high-level application specification, defined as a network of components, to an optimal combination of the currently available component implementations within our grid environment. We demonstrate the effectiveness of this architecture through high-level specification and solution of a set of linear equations by automatic and optimal resource and implementation selection.

ICENI: An Integrated Grid Middleware to Support E-Science

Scientists now have a greater desire to undertake work within global collaborations. This increases their dependence on distributed computation, storage and data resources. For this new paradigm of e-research to be easily adopted by the applied science community, it needs to be enabled by a new software infrastructure — Grid middleware. In this chapter, we describe ICENI, an integrated Grid middleware that explores the services and meta-data necessary to support e-research within a variety of application domains. We focus on the services that we feel are necessary to facilitate Grid use, ranging from running a simple self contained application through to building a simulation from scientific software components distributed across a Grid, selecting the optimal combination of services to enact the simulation and paying for them on demand.

RealityGrid : an integrated approach to middleware through ICENI

The advancement of modelling and simulation within complex scientific applications is currently constrained by the rate at which knowledge can be extracted from the data produced. As Grid computing evolves, new means of increasing the efficiency of data analysis are being explored. RealityGrid aims to enable more efficient use of scientific computing resources within the condensed matter, materials and biological science communities. The Imperial College e-Science Networked Infrastructure (ICENI) Grid middleware provides an end-to-end pipeline that simplifies the stages of computation, simulation and collaboration. The intention of this work is to allow all scientists to have access to these features without the need for heroic efforts that have been associated with this sort of work in the past. Scientists can utilise advanced scheduling mechanisms to ensure efficient planning of computations, visualize and interactively steer simulations and securely collaborate with colleagues via the Access Grid through a single integrated middleware application.

An Integrated Grid Environment for Component Applications

Computational grids present many obstacles to their effective exploitation by non-trivial applications. We present a grid middleware, implemented using Java and Jini, that eliminates these obstacles through the intelligent use of meta-data relating to the structure, behaviour and performance of an application. We demonstrate how different problem sizes and selection criteria (minimum execution time or minimum cost) utilise different implementations for the optimal solution of a set of linear equations.

A Component Framework for HPC Applications

We describe a general component software framework designed for demanding grid environments that provides optimal performance for the assembled component application. This is achieved by separating the high level abstract description of the composition from the low level implementations. These implementations are chosen at run time by performance analysis of the composed application on the currently available resources. We show through the solution of a simple linear algebra problem that the framework introduces minimal overheads while always selecting the most effective implementation.

A Software Architecture for HPC Grid Applications

We introduce a component software architecture designed for demanding grid computing environments that allows the optimal performance of the assembled component applications to be achieved. Performance over the assembled component application is maintained through inter-component static and dynamic optimisation techniques. Having defined an application through both its component task and data flow graphs we are able to use the associated performance models to support application level scheduling. By building grid aware applications through reusable interchangeable software components with integrated performance models we enable the automatic and optimal partitioning of an application across distributed computational resources.