Using Grid Technology for Maximizing Collaborative Emergency Response Decision Making

Much work is under way within the Grid technology community on issues associated with the development of services to foster collaboration via the integration and exploitation of multiple autonomous, distributed data sources through a seamless and flexible virtualized interface. However, several obstacles arise in the design and implementation of such services. A notable obstacle, namely how clients within a data Grid environment can be kept automatically informed of the latest and relevant changes about data entered/committed in single or multiple autonomous distributed datasets is identified. The view is that keeping interested users informed of relevant changes occurring across their domain of interest will enlarge their decision-making space which in turn will increase the opportunities for a more informed decision to be encountered. With this in mind, the chapter goes on to describe in detail the model architecture and its implementation to keep interested users informed automatically about relevant up-to-date data.

Model Architecture for a User Tailored Data Push Service in Data Grids

This chapter describes a framework to support runtime service discovery for Grid applications based on service discovery queries in both push and pull modes of query execution. The framework supports six different types of trigger conditions that may prompt service replacement during run-time of grid business application, and evaluates the relevance of a set of candidate services against service discovery queries. The chapter also describes the language used to express service discovery queries and the three types of fitness measurement used to evaluate the candidate services against these queries. Both synchronous (pull) and asynchronous (push) mechanisms for service discovery are presented and shown to be complimentary in dealing with all six service discovery trigger conditions. The chapter is illustrated through examples.

Runtime Service Discovery for Grid Applications

A Virtual Organisation in large-scale distributed systems is a set of individuals and/or institutions with some common purposes or interests that need to share their resources to further their objectives, which is similar to a human community in social networks that consists of people have common interests or goals. Due to the similarity between social networks and Grids, the concepts in social science (e.g. small world phenomenon) can be adopted for the design of new generation Grid systems. This chapter presents a Small World Architecture for Effective Virtual Organisations (SWEVO) for Grid resource discovery in Virtual Organisations, which enables Virtual Organisations working in a more collaborative manner to support decision makers. In SWEVO, Virtual Organisations are connected by a small number of interorganisational links. Not every local network node needs to be connected to remote Virtual Organisations, but every network node can efficiently find connections to specific Virtual Organisations.

Semantics-Based Process Support for Grid Applications

The infrastructure of Grid is approaching maturity and can be used to enable the utilisation and sharing of large scale, remote data storages through distributed computational capabilities and support collaborations and co-operations between different organisations. Grid can therefore be suitably used to support the creation and running of a virtual organisation (VO). However, to assist the smooth operation of VOs, robust computational and storage facilities alone are not sufficient. There must also exist appropriate rich business infrastructure. In this chapter, the authors consider business process frameworks that utilise semantics-based business process modelling (BPM) technologies, and they illustrate the multidisciplinary nature of our approach by applying them to three different fields: Supply Chain Management, Business Intelligence and Knowledge Management, and Intelligent Video Analysis. They aim to show that these three application areas that incorporate semantics-based BPM methods could be used to support developing Grid applications, and to subsequently support VOs.

Small World Architecture for Building Effective Virtual Organisations

The aim of this chapter is to appreciate the need for and propose some thoughts on modelling trust–control dynamics for communities that use grid technology. It takes the viewpoint that members within a grid-based community require a trust framework that brings together and takes into account both social and technological approaches to trust. It also emphasises the importance of the simultaneous analysis of trust and control in their co-development. In line with the duality perspective that considers trust and control as independent yet interrelated dimensions, trust is explored in its relation to control. Control is examined as a multi-dimensional phenomenon that includes personal, formal, and social scopes. The analysis of trust appeals to its cognitive and affective dimensions. The model introduced also takes into account the mediating role of psychological ownership in the trust–control dynamics. Specifically, shared psychological ownership is singled out as a new explanatory variable of this dynamic.

Modelling Trust–Control Dynamics for Grid-based Communities

A Virtual Organisation (VO) or Virtual Enterprise is a loosely-coupled group of collaborating organisations, acting to some extent as though they were part of a single organisation. This implies that they exhibit some properties of a conventional organisation without actually being one. In practice, this involves overcoming organisational boundaries, which tend to make collaborative working difficult. The authors of this chapter propose that this is a socio-technical problem, requiring both a technical (software) infrastructure and a sociological approach to building, deploying and operating the VOs supported by it. This joint approach can help to overcome some of the problems associated with collaborative working, ranging from poorly coordinated activity, to ineffective problem solving and decision- making. The authors describe a socio-technical approach to building and operating VOs in highly dynamic environments and present two factual scenarios from the chemical and health industries. They describe a platform supporting such VOs, which was developed as part of the EPSRC E-Science Pilot Project GOLD.

The Socio-Technical Virtual Organisation

Flexible and remote working is becoming more and more widespread. In particular, virtual team working is growing rapidly. Although virtual teams have attracted the attention of many researchers, until recently little investigation had been carried out specifically on what impact trust – a key element in favouring cooperation among team members – has on the performance of such teams. In the authors’ opinion Grid computing, through the collaborative nature of the technologies employed, provides an opportunity to build trust through the sharing of common resources and the enabling of rich communications.

Sustainable and Interoperable e-Infrastructures for Research and Business

Grid computing allows for the creation of e-infrastructures providing computational power and information storage capabilities needed both by present and future research centres around the world. Although the value of Grids is recognised by its early users, many companies, which would benefit from the adoption of this new paradigm, are still waiting claiming that Grid technologies are still not wellestablished and continuously evolving. A company usually takes a risk when it adopts a technology before its standardisation because if the technology subsequently demonstrates to diverge from (de-facto) standards then the investments can be partially lost and, additionally, switching to the new standard technology will probably be more expensive. In this chapter we present a couple of approaches which allow existing Grid infrastructures to evolve, by including newer Grid middleware, and consequently preserve the investment made on the infrastructure. The capability to evolve reduces current problems of Grid implementation (especially the lack of standards), so it makes Grid adoption by business companies and research centres painless.

Unified Data Access/Query over Integrated Data-views for Decision Making in Geographic Information Systems

Geographic information is critical for building disaster planning, crisis management, and early-warning systems. Decision making in geographic information systems (GIS) increasingly relies on analyses of spatial data in map-based formats. Maps are complex structures composed of layers created from distributed heterogeneous data belonging to the separate organizations. This chapter presents a distributed service architecture for managing the production of knowledge from distributed collections of observations and simulation data through integrated data-views. Integrated views are defined by a federation service (“federator”) located on top of the standard service components. Common GIS standards enable the construction of this system. However, compliance requirements for interoperability, such as XML-encoded data and domain specific data characteristics, have costs and performance overhead. The authors investigate issues of combining standard compliance with performance. Although their framework is designed for GIS, they extend the principles and requirements to general science domains and discuss how these may be applied.

Leveraging Simulation Practice in Industry through use of Desktop Grid Middleware

The computational grid offers services for efficiently scheduling jobs on the grid, but for grid-enabled applications where data handling is a most relevant part, the data grid kicks in. It typically builds on the concept of files, sites and file transfers between sites. These use a data transfer service, plus a replica manager to keep track of where replicas are located. The authors consider a multi-site, grid-aware data warehouse, which is a large distributed repository sharing a schema and data concerning scientific or business domains. Differently from typical grid scenarios, the data warehouse is not simply a set of files and accesses to individual files. It is a single distributed schema and both localized and distributed computations must be managed over that schema. Given this difference, it is important to study approaches for placement and computation over the grid data warehouse and this is our contribution in this book chapter.