Condor: a distributed job scheduler
Beowulf cluster computing with Linux
GridFlow: Workflow Management for Grid Computing
CCGRID '03 Proceedings of the 3st International Symposium on Cluster Computing and the Grid
Grid Computing: Making the Global Infrastructure a Reality
Grid Computing: Making the Global Infrastructure a Reality
Resource management for the Triana peer-to-peer services
Grid resource management
A Novel Architecture for Realizing Grid Workflow using Tuple Spaces
GRID '04 Proceedings of the 5th IEEE/ACM International Workshop on Grid Computing
ASKALON: a tool set for cluster and Grid computing: Research Articles
Concurrency and Computation: Practice & Experience - Grid Performance
Agreement-Based Workload and Resource Management
E-SCIENCE '05 Proceedings of the First International Conference on e-Science and Grid Computing
GRIDCC: real-time workflow system
Proceedings of the 2nd workshop on Workflows in support of large-scale science
GRIDCC: A Real-time Grid workflow system with QoS
Scientific Programming - Dynamic Computational Workflows: Discovery, Optimization and Scheduling
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Many Grid architectures have been developed in recent years. These range from the large community Grids such as LHG and EGEE to single site deployments such as Condor. However, these Grid architectures have tended to focus on the single or batch submission of executable jobs. Application scientists are now seeking to manage and use physical instrumentation on the Grid, integrating these with the computational tasks they already perform. This will require the functionality of current Grid systems to be extended to allow the submission of entire workflows. Thus allowing the scientists to perform increasingly larger parts of their experiments within the Grid environment. We propose here a set of high level services which may be used on-top of these existing Grid architectures such that the benefits of these architectures may be exploited along with the new functionality of workflows.