Theories and Models

This chapter is about conceptualizing the applicability of grid related technologies for supporting intelligence in decision-making. It aims to discuss how the open grid service architecture—data, access integration (OGSA-DAI) can facilitate the discovery of and controlled access to vast data-sets, to assist intelligence in decision making. Trust is also identified as one of the main challenges for intelligence in decision-making. On this basis, the implications and challenges of using grid technologies to serve this purpose are also discussed. To further the explanation of the concepts and practices associated with the process of intelligence in decision-making using grid technologies, a minicase is employed incorporating a scenario. That is to say, “Synergy Financial Solutions Ltd” is presented as the minicase, so as to provide the reader with a central and continuous point of reference.

Intelligent Job Service Scheduling Scheme in Campus Grids

Campus grid is to use grid technology, the existing campus network, distributed, heterogeneous computing resources and information resources to the virtual integrated together to form a pool of available computing resources and can provide information platform for users to query information. This paper presents job scheduling model based on open grid service architecture by analyzing the current status of campus network and grid technologies. The simulation results show that the models are feasibility and validity.

Resource Sharing Campus Grid Platform Based on Load Balancing and Open Grid Service Architecture

In order to share distributed resources in the campus network and save relevant cost, This paper presents an extended campus services, data integration middleware grid middleware, grid data integration gives the campus a key middleware technology and architecture, and discusses the integration of grid middleware architecture of the campus's role and how grid services and other interactive components to complete the application request

Architectures for Large Scale Distributed Systems

This chapter introduces the macroscopic views on distributed systems’ components and their inter-relations. The importance of the architecture for understanding, designing, implementing, and maintaining distributed systems is presented first. Then the currently used architectures and their derivatives are analyzed. The presentation refers to the client-server (with details about Multi-tiered, REST, Remote Evaluation, and Code-on-Demand architectures), hierarchical (with insights in the protocol oriented Grid architecture), service-oriented architectures including OGSA (Open Grid Service Architecture), cloud, cluster, and peer-to-peer (with its versions: hierarchical, decentralized, distributed, and event-based integration architectures). Due to the relation between architecture and application categories supported, the chapter’s structure is similar to that of Chapter 1. Nevertheless, the focus is different. In the current chapter, for each architecture the model, advantages, disadvantages and areas of applicability are presented. Also the chapter includes concrete cases of use (namely actual distributed systems and platforms), and clarifies the relation between the architecture and the enabling technology used in its instantiation. Finally, Chapter 2 frames the discussion in the other chapters, which refer to specific components and services for large scale distributed systems.

Using Grid for Data Sharing to Support Intelligence in Decision Making

This chapter is about conceptualizing the applicability of grid related technologies for supporting intelligence in decision-making. It aims to discuss how the open grid service architecture—data, access integration (OGSA-DAI) can facilitate the discovery of and controlled access to vast data-sets, to assist intelligence in decision making. Trust is also identified as one of the main challenges for intelligence in decision-making. On this basis, the implications and challenges of using grid technologies to serve this purpose are also discussed. To further the explanation of the concepts and practices associated with the process of intelligence in decision-making using grid technologies, a minicase is employed incorporating a scenario. That is to say, “Synergy Financial Solutions Ltd” is presented as the minicase, so as to provide the reader with a central and continuous point of reference.

Towards an Architecture for the Mobile Grid (Architektur für ein Mobiles Grid)

SummaryMobility is becoming a central aspect of everyday life and must not be ignored by the ongoing efforts in defining the Next Generation Grid architectures. Currently existing network agnostic Grid middleware solutions are duplicating functionality available from lower layers and cannot benefit from a richer set of additional information available such as the user or device context. In this article we will motivate why an integration of the infrastructure services built for supporting mobile users can be beneficial for the realization of a Next Generation Grid. Starting from a definition of the term Mobile Grid it is shown how new kind of adaptive applications can be realized and how the major obstacles for the wide take up of Grid solutions can be addressed. In particular how grid solutions can benefit from user authentication models, cross-organizational accounting, auditing and billing are covered. Beside the opportunities of this integration several new challenges in particular related to workflows and the management of Service Level Agreements will be outlined. This so called Cross-Layer Cooperation is seen as one of the major differences to other Next Generation Grids based on the Open Grid Service Architecture (OGSA) [10] approach. In the next section considerations related to deployment of Mobile Grids and why the approach outlined in the OGSA architecture to model grids as the composition of individual services is not adequate for this are presented.