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Richard McClatchey

Publications and source records attributed to Richard McClatchey.

At least 37 records · Page 2Linked to original sources

Model Driven Engineering for Science Gateways

From n-Tier client/server applications, to more complex academic Grids, or even the most recent and promising industrial Clouds, the last decade has witnessed significant developments in distributed computing. In spite of this conceptual heterogeneity, Service-Oriented Architectures (SOA) seem to have emerged as the common underlying abstraction paradigm. Suitable access to data and applications resident in SOAs via so-called Science Gateways has thus become a pressing need in various fields of science, in order to realize the benefits of Grid and Cloud infrastructures. In this context, authors have consolidated work from three complementary experiences in European projects, which have developed and deployed large-scale production quality infrastructures as Science Gateways to support research in breast cancer, paediatric diseases and neurodegenerative pathologies respectively. In analysing the requirements from these biomedical applications the authors were able to elaborate on commonly faced Grid development issues, while proposing an adaptable and extensible engineering framework for Science Gateways. This paper thus proposes the application of an architecture-centric Model-Driven Engineering (MDE) approach to service-oriented developments, making it possible to define Science Gateways that satisfy quality of service requirements, execution platform and distribution criteria at design time. An novel investigation is presented on the applicability of the resulting grid MDE (gMDE) to specific examples, and conclusions are drawn on the benefits of this approach and its possible application to other areas, in particular that of Distributed Computing Infrastructures (DCI) interoperability.

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The Case for Cloud Service Trustmarks and Assurance-as-a-Service

Cloud computing represents a significant economic opportunity for Europe. However, this growth is threatened by adoption barriers largely related to trust. This position paper examines trust and confidence issues in cloud computing and advances a case for addressing them through the implementation of a novel trustmark scheme for cloud service providers. The proposed trustmark would be both active and dynamic featuring multi-modal information about the performance of the underlying cloud service. The trustmarks would be informed by live performance data from the cloud service provider, or ideally an independent third-party accountability and assurance service that would communicate up-to-date information relating to service performance and dependability. By combining assurance measures with a remediation scheme, cloud service providers could both signal dependability to customers and the wider marketplace and provide customers, auditors and regulators with a mechanism for determining accountability in the event of failure or non-compliance. As a result, the trustmarks would convey to consumers of cloud services and other stakeholders that strong assurance and accountability measures are in place for the service in question and thereby address trust and confidence issues in cloud computing.

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Data Management Challenges in Paediatric Information Systems

There is a compelling demand for the data integration and exploitation of heterogeneous biomedical information for improved clinical practice, medical research, and personalised healthcare across the EU. The area of paediatric information integration is particularly challenging since the patients physiology changes with growth and different aspects of health being regularly monitored over extended periods of time. Paediatricians require access to heterogeneous data sets, often collected in different locations with different apparatus and over extended timescales. Using a Grid platform originally developed for physics at CERN and a novel integrated semantic data model the Health-e-Child project has developed an integrated healthcare platform for European paediatrics, providing seamless integration of traditional and emerging sources of biomedical data. The long-term goal of the project was to provide uninhibited access to universal biomedical knowledge repositories for personalised and preventive healthcare, large-scale information-based biomedical research and training, and informed policy making. The project built a Grid-enabled european network of leading clinical centres that can share and annotate paediatric data, can validate systems clinically, and diffuse clinical excellence across Europe by setting up new technologies, clinical workflows, and standards. The Health-e-Child project highlights data management challenges for the future of European paediatric healthcare and is the subject of this chapter.

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A Description Driven Approach for Flexible Metadata Tracking

Evolving user requirements presents a considerable software engineering challenge, all the more so in an environment where data will be stored for a very long time, and must remain usable as the system specification evolves around it. Capturing the description of the system addresses this issue since a description-driven approach enables new versions of data structures and processes to be created alongside the old, thereby providing a history of changes to the underlying data models and enabling the capture of provenance data. This description-driven approach is advocated in this paper in which a system called CRISTAL is presented. CRISTAL is based on description-driven principles; it can use previous versions of stored descriptions to define various versions of data which can be stored in various forms. To demonstrate the efficacy of this approach the history of the project at CERN is presented where CRISTAL was used to track data and process definitions and their associated provenance data in the construction of the CMS ECAL detector, how it was applied to handle analysis tracking and data index provenance in the neuGRID and N4U projects, and how it will be matured further in the CRISTAL-ISE project. We believe that the CRISTAL approach could be invaluable in handling the evolution, indexing and tracking of large datasets, and are keen to apply it further in this direction.

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CRISTAL : A Practical Study in Designing Systems to Cope with Change

Software engineers frequently face the challenge of developing systems whose requirements are likely to change in order to adapt to organizational reconfigurations or other external pressures. Evolving requirements present difficulties, especially in environments in which business agility demands shorter development times and responsive prototyping. This paper uses a study from CERN in Geneva to address these research questions by employing a description-driven approach that is responsive to changes in user requirements and that facilitates dynamic system reconfiguration. The study describes how handling descriptions of objects in practice alongside their instances (making the objects self-describing) can mediate the effects of evolving user requirements on system development. This paper reports on and draws lessons from the practical use of a description-driven system over time. It also identifies lessons that can be learned from adopting such a self-describing description-driven approach in future software development.

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An Integrated e-science Analysis Base for Computation Neuroscience Experiments and Analysis

Recent developments in data management and imaging technologies have significantly affected diagnostic and extrapolative research in the understanding of neurodegenerative diseases. However, the impact of these new technologies is largely dependent on the speed and reliability with which the medical data can be visualised, analysed and interpreted. The EUs neuGRID for Users (N4U) is a follow-on project to neuGRID, which aims to provide an integrated environment to carry out computational neuroscience experiments. This paper reports on the design and development of the N4U Analysis Base and related Information Services, which addresses existing research and practical challenges by offering an integrated medical data analysis environment with the necessary building blocks for neuroscientists to optimally exploit neuroscience workflows, large image datasets and algorithms in order to conduct analyses. The N4U Analysis Base enables such analyses by indexing and interlinking the neuroimaging and clinical study datasets stored on the N4U Grid infrastructure, algorithms and scientific workflow definitions along with their associated provenance information.

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Towards Provenance and Traceability in CRISTAL for HEP

This paper discusses the CRISTAL object lifecycle management system and its use in provenance data management and the traceability of system events. This software was initially used to capture the construction and calibration of the CMS ECAL detector at CERN for later use by physicists in their data analysis. Some further uses of CRISTAL in different projects (CMS, neuGRID and N4U) are presented as examples of its flexible data model. From these examples, applications are drawn for the High Energy Physics domain and some initial ideas for its use in data preservation HEP are outlined in detail in this paper. Currently investigations are underway to gauge the feasibility of using the N4U Analysis Service or a derivative of it to address the requirements of data and analysis logging and provenance capture within the HEP long term data analysis environment.

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Risk-Driven Compliant Access Controls for Clouds

There is widespread agreement that cloud computing have proven cost cutting and agility benefits. However, security and regulatory compliance issues are continuing to challenge the wide acceptance of such technology both from social and commercial stakeholders. An important facture behind this is the fact that clouds and in particular public clouds are usually deployed and used within broad geographical or even international domains. This implies that the exchange of private and other protected data within the cloud environment would be governed by multiple jurisdictions. These jurisdictions have a great degree of harmonisation; however, they present possible conflicts that are hard to negotiate at run time. So far, important efforts were played in order to deal with regulatory compliance management for large distributed systems. However, measurable solutions are required for the context of cloud. In this position paper, we are suggesting an approach that starts with a conceptual model of explicit regulatory requirements for exchanging private data on a multijurisdictional environment and build on it in order to define metrics for non-compliance or, in other terms, risks to compliance. These metrics will be integrated within usual data access-control policies and will be checked at policy analysis time before a decision to allow/deny the data access is made.

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An Architecture for Integrated Intelligence in Urban Management using Cloud Computing

With the emergence of new methodologies and technologies it has now become possible to manage large amounts of environmental sensing data and apply new integrated computing models to acquire information intelligence. This paper advocates the application of cloud capacity to support the information, communication and decision making needs of a wide variety of stakeholders in the complex business of the management of urban and regional development. The complexity lies in the interactions and impacts embodied in the concept of the urban-ecosystem at various governance levels. This highlights the need for more effective integrated environmental management systems. This paper offers a user-orientated approach based on requirements for an effective management of the urban-ecosystem and the potential contributions that can be supported by the cloud computing community. Furthermore, the commonality of the influence of the drivers of change at the urban level offers the opportunity for the cloud computing community to develop generic solutions that can serve the needs of hundreds of cities from Europe and indeed globally.

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A Fault Tolerant, Dynamic and Low Latency BDII Architecture for Grids

The current BDII model relies on information gathering from agents that run on each core node of a Grid. This information is then published into a Grid wide information resource known as Top BDII. The Top level BDIIs are updated typically in cycles of a few minutes each. A new BDDI architecture is proposed and described in this paper based on the hypothesis that only a few attribute values change in each BDDI information cycle and consequently it may not be necessary to update each parameter in a cycle. It has been demonstrated that significant performance gains can be achieved by exchanging only the information about records that changed during a cycle. Our investigations have led us to implement a low latency and fault tolerant BDII system that involves only minimal data transfer and facilitates secure transactions in a Grid environment.

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Reusable Services from the neuGRID Project for Grid-Based Health Applications

By abstracting Grid middleware specific considerations from clinical research applications, re-usable services should be developed that will provide generic functionality aimed specifically at medical applications. In the scope of the neuGRID project, generic services are being designed and developed which will be applied to satisfy the requirements of neuroscientists. These services will bring together sources of data and computing elements into a single view as far as applications are concerned, making it possible to cope with centralised, distributed or hybrid data and provide native support for common medical file formats. Services will include querying, provenance, portal, anonymization and pipeline services together with a 'glueing' service for connection to Grid services. Thus lower-level services will hide the peculiarities of any specific Grid technology from upper layers, provide application independence and will enable the selection of 'fit-for-purpose' infrastructures. This paper outlines the design strategy being followed in neuGRID using the glueing and pipeline services as examples.

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Research Traceability using Provenance Services for Biomedical Analysis

We outline the approach being developed in the neuGRID project to use provenance management techniques for the purposes of capturing and preserving the provenance data that emerges in the specification and execution of workflows in biomedical analyses. In the neuGRID project a provenance service has been designed and implemented that is intended to capture, store, retrieve and reconstruct the workflow information needed to facilitate users in conducting user analyses. We describe the architecture of the neuGRID provenance service and discuss how the CRISTAL system from CERN is being adapted to address the requirements of the project and then consider how a generalised approach for provenance management could emerge for more generic application to the (Health)Grid community.

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Context-Aware Service Utilisation in the Clouds and Energy Conservation

Ubiquitous computing environments are characterised by smart, interconnected artefacts embedded in our physical world that are projected to provide useful services to human inhabitants unobtrusively. Mobile devices are becoming the primary tools of human interaction with these embedded artefacts and utilisation of services available in smart computing environments such as clouds. Advancements in capabilities of mobile devices allow a number of user and environment related context consumers to be hosted on these devices. Without a coordinating component, these context consumers and providers are a potential burden on device resources; specifically the effect of uncoordinated computation and communication with cloud-enabled services can negatively impact the battery life. Therefore energy conservation is a major concern in realising the collaboration and utilisation of mobile device based context-aware applications and cloud based services. This paper presents the concept of a context-brokering component to aid in coordination and communication of context information between mobile devices and services deployed in a cloud infrastructure. A prototype context broker is experimentally analysed for effects on energy conservation when accessing and coordinating with cloud services on a smart device, with results signifying reduction in energy consumption.

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CMS Workflow Execution using Intelligent Job Scheduling and Data Access Strategies

Complex scientific workflows can process large amounts of data using thousands of tasks. The turnaround times of these workflows are often affected by various latencies such as the resource discovery, scheduling and data access latencies for the individual workflow processes or actors. Minimizing these latencies will improve the overall execution time of a workflow and thus lead to a more efficient and robust processing environment. In this paper, we propose a pilot job based infrastructure that has intelligent data reuse and job execution strategies to minimize the scheduling, queuing, execution and data access latencies. The results have shown that significant improvements in the overall turnaround time of a workflow can be achieved with this approach. The proposed approach has been evaluated, first using the CMS Tier0 data processing workflow, and then simulating the workflows to evaluate its effectiveness in a controlled environment.

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A Data Model for Integrating Heterogeneous Medical Data in the Health-e-Child Project

There has been much research activity in recent times about providing the data infrastructures needed for the provision of personalised healthcare. In particular the requirement of integrating multiple, potentially distributed, heterogeneous data sources in the medical domain for the use of clinicians has set challenging goals for the healthgrid community. The approach advocated in this paper surrounds the provision of an Integrated Data Model plus links to/from ontologies to homogenize biomedical (from genomic, through cellular, disease, patient and population-related) data in the context of the EC Framework 6 Health-e-Child project. Clinical requirements are identified, the design approach in constructing the model is detailed and the integrated model described in the context of examples taken from that project. Pointers are given to future work relating the model to medical ontologies and challenges to the use of fully integrated models and ontologies are identified.

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Ontology Assisted Query Reformulation Using Semantic and Assertion Capabilities of OWL-DL Ontologies

End users of recent biomedical information systems are often unaware of the storage structure and access mechanisms of the underlying data sources and can require simplified mechanisms for writing domain specific complex queries. This research aims to assist users and their applications in formulating queries without requiring complete knowledge of the information structure of underlying data sources. To achieve this, query reformulation techniques and algorithms have been developed that can interpret ontology-based search criteria and associated domain knowledge in order to reformulate a relational query. These query reformulation algorithms exploit the semantic relationships and assertion capabilities of OWL-DL based domain ontologies for query reformulation. In this paper, this approach is applied to the integrated database schema of the EU funded Health-e-Child (HeC) project with the aim of providing ontology assisted query reformulation techniques to simplify the global access that is needed to millions of medical records across the UK and Europe.

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Managing Separation of Concerns in Grid Applications Through Architectural Model Transformations

Grids enable the aggregation, virtualization and sharing of massive heterogeneous and geographically dispersed resources, using files, applications and storage devices, to solve computation and data intensive problems, across institutions and countries via temporary collaborations called virtual organizations (VO). Most implementations result in complex superposition of software layers, often delivering low quality of service and quality of applications. As a consequence, Grid-based applications design and development is increasingly complex, and the use of most classical engineering practices is unsuccessful. Not only is the development of such applications a time-consuming, error prone and expensive task, but also the resulting applications are often hard-coded for specific Grid configurations, platforms and infra-structures. Having neither guidelines nor rules in the design of a Grid-based application is a paradox since there are many existing architectural approaches for distributed computing, which could ease and promote rigorous engineering methods based on the re-use of software components. It is our belief that ad-hoc and semi-formal engineer-ing approaches, in current use, are insufficient to tackle tomorrows Grid develop-ments requirements. Because Grid-based applications address multi-disciplinary and complex domains (health, military, scientific computation), their engineering requires rigor and control. This paper therefore advocates a formal model-driven engineering process and corresponding design framework and tools for building the next generation of Grids.

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PhantomOS: A Next Generation Grid Operating System

Grid Computing has made substantial advances in the past decade; these are primarily due to the adoption of standardized Grid middleware. However Grid computing has not yet become pervasive because of some barriers that we believe have been caused by the adoption of middleware centric approaches. These barriers include: scant support for major types of applications such as interactive applications; lack of flexible, autonomic and scalable Grid architectures; lack of plug-and-play Grid computing and, most importantly, no straightforward way to setup and administer Grids. PhantomOS is a project which aims to address many of these barriers. Its goal is the creation of a user friendly pervasive Grid computing platform that facilitates the rapid deployment and easy maintenance of Grids whilst providing support for major types of applications on Grids of almost any topology. In this paper we present the detailed system architecture and an overview of its implementation.

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