2008Unpublished venueRequires access

Market-Oriented Grid Computing and the Gridbus Middleware

Rajkumar Buyya

Open publisher page 3 citations

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. Despite a number of advances in grid computing, resource management and application scheduling in such environments continues to be a challenging and complex undertaking. This is due to geographic distribution of grid resources owned by different organizations with different usage policies, cost models and varying load and availability patterns with time. This tutorial introduces fundamental principles of grid computing and computational economy and discusses how they impact on emerging computational and data grid technologies. It identifies resource management challenges and introduces new challenges and requirements introduced by the grid economy on grid service providers (GSPs) and grid service consumers. The tutorial presents a service-oriented grid architecture inspired by computational economies and demonstrates how it can be realized by leveraging the existing grid technologies and building new economic-oriented capabilities and components. We present solutions to these challenges based on our experience in designing and developing market-oriented Gridbus technologies such as Grid Market Directory, Grid Bank, Grid Service Broker, Workflow Engine, and SLA-based enterprise Grid Resource Allocation system. Case studies on the use of Gridbus middleware in the creation of various e-science and e-business applications and their deployment on national/international utility-oriented grids along with its impact on emerging cloud computing paradigm will also be highlighted.

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What this paper is about

Grid computing, one of the latest buzzwords in the ICT industry, is emerging as a new paradigm for Internet-based parallel and distributing computing. Despite a number of advances in grid computing, resource management and application scheduling in such environments continues to be a challenging and complex undertaking. This is due to geographic distribution of grid resources owned by different organizations with different usage policies, cost models and varying load and availability patterns with time. This tutorial introduces fundamental principles of grid computing and computational economy and discusses how they impact on emerging computational and data grid technologies. It identifies resource management challenges and introduces new challenges and requirements introduced by the grid economy on grid service providers (GSPs) and grid service consumers. The tutorial presents a service-oriented grid architecture inspired by computational economies and demonstrates how it can be realized by leveraging the existing grid technologies and building new economic-oriented capabilities and components. We present solutions to these challenges based on our experience in designing and developing market-oriented Gridbus technologies such as Grid Market Directory, Grid Bank, Grid Service Broker, Workflow Engine, and SLA-based enterprise Grid Resource Allocation system. Case studies on the use of Gridbus middleware in the creation of various e-science and e-business applications and their deployment on national/international utility-oriented grids along with its impact on emerging cloud computing paradigm will also be highlighted.

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Available 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. Despite a number of advances in grid computing, resource management and application scheduling in such environments continues to be a challenging and complex undertaking. This is due to geographic distribution of grid resources owned by different organizations with different usage policies, cost models and varying load and availability patterns with time. This tutorial introduces fundamental principles of grid computing and computational economy and discusses how they impact on emerging computational and data grid technologies. It identifies resource management challenges and introduces new challenges and requirements introduced by the grid economy on grid service providers (GSPs) and grid service consumers. The tutorial presents a service-oriented grid architecture inspired by computational economies and demonstrates how it can be realized by leveraging the existing grid technologies and building new economic-oriented capabilities and components. We present solutions to these challenges based on our experience in designing and developing market-oriented Gridbus technologies such as Grid Market Directory, Grid Bank, Grid Service Broker, Workflow Engine, and SLA-based enterprise Grid Resource Allocation system. Case studies on the use of Gridbus middleware in the creation of various e-science and e-business applications and their deployment on national/international utility-oriented grids along with its impact on emerging cloud computing paradigm will also be highlighted.

Key concepts: Grid computing, DRMAA, Semantic grid, Computer science, Grid, Cloud computing, Distributed computing, Data grid

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