A taxonomy and survey of grid resource management systems for distributed computing
Software—Practice & Experience
Models and Scheduling Mechanisms for Global Computing Applications
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
GridFlow: Workflow Management for Grid Computing
CCGRID '03 Proceedings of the 3st International Symposium on Cluster Computing and the Grid
Hybrid Task Scheduling: Integrating Static and Dynamic Heuristics
SBAC-PAD '03 Proceedings of the 15th Symposium on Computer Architecture and High Performance Computing
Scheduling in Bag-of-Task Grids: The PAUÁ Case
SBAC-PAD '04 Proceedings of the 16th Symposium on Computer Architecture and High Performance Computing
Self adaptivity in Grid computing: Research Articles
Concurrency and Computation: Practice & Experience - Grid Performance
Concurrency and Computation: Practice & Experience - Middleware for Grid Computing
Managing the Execution of Large Scale MPI Applications on Computational Grids
SBAC-PAD '05 Proceedings of the 17th International Symposium on Computer Architecture on High Performance Computing
Concurrency and Computation: Practice & Experience - Middleware for Grid Computing
New grid scheduling and rescheduling methods in the GrADS project
International Journal of Parallel Programming - Special issue: The next generation software program
Autonomic application management for large scale MPI programs
International Journal of High Performance Computing and Networking
Three-layer control policy for grid resource management
Journal of Network and Computer Applications
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The execution of distributed applications on the grid is already a reality. As both the number of applications grow and grids scale, efficient utilization of the available but shared heterogeneous resources will be essential. The EasyGrid middleware is a hierarchically distributed Application Management System embedded into MPI applications to facilitate their efficient execution in computational grids. The overhead of employing a distinct AMS to make each application system aware does however bring at least two benefits. First, the (scheduling) policies adopted can be tailored to the specific needs of each application leading to improved performance. Second, distributing the management effort amongst the applications themselves makes grid management more scalable. This paper describes a low intrusion implementation of a hybrid scheduling strategy designed to cope with the dynamic behaviour of grid environments. Using application-specific scheduling policies, near-optimal runtimes highlight the advantages of self-scheduling when executing one or more system aware applications on a grid.