Abstract

Grid computing, one of the latest buzzwords in the ICT industry, is emerging as a new paradigm for Internet-based parallel and distributing computing. It enables the sharing, selection, and aggregation of geographically distributed autonomous resources, such as computers (PCs, servers, clusters, supercomputers), databases, and scientific instruments, for solving large-scale problems in science, engineering, and commerce. It leverages existing IT infrastructure to optimize compute resources and manage data and computing workloads. The developers of Grids and Grid applications need to address numerous challenges: security, heterogeneity, dynamicity, scalability, reliability, service creation and pricing, resource discovery, resource management, application dAbsecomposition and service composition, and qualify of services. A number of projects around the world are developing technologies that help address one or more of these challenges. To address some of these challenges, the Gridbus Project at the University of Melbourne has developed grid middleware technologies that (1) enable the creation of Utility Grids, which provide economic incentive for Grid service providers for sharing resources; and (2) support rapid development and optimal deployment of eScience and eBusiness applications on enterprise and global Grids. The components of Gridbus middleware are: Grid application development environment for rapid creation of distributed applications, Grid service broker and application scheduler, Grid workflow management engine, SLA (service-level agreements) based Scheduler for clusters, Web-services based Grid market directory (GMD), Grid accounting services, Gridscape for creation of dynamic and interactive resource monitoring portals, Portlets for creation of Grid portals that support web-based management of Grid applications execution, and GridSim toolkit for performance evaluation. In addition, Gridbus also includes a widely used .NET-based enterprise Grid technology and Grid web services framework to support the integration of both Windows and Unix-class resources for Grid computing.

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