Introduction to algorithms
An Algorithm for Finding a Minimal Equivalent Graph of a Digraph
Journal of the ACM (JACM)
SETI@HOME—massively distributed computing for SETI
Computing in Science and Engineering
Models and Scheduling Mechanisms for Global Computing Applications
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
The Computational Co-op: Gathering Clusters into a Metacomputer
IPPS '99/SPDP '99 Proceedings of the 13th International Symposium on Parallel Processing and the 10th Symposium on Parallel and Distributed Processing
Applying Chimera virtual data concepts to cluster finding in the Sloan Sky Survey
Proceedings of the 2002 ACM/IEEE conference on Supercomputing
Grid Harvest Service: A System for Long-Term, Application-Level Task Scheduling
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
A Case for Economy Grid Architecture for Service Oriented Grid Computing
IPDPS '01 Proceedings of the 10th Heterogeneous Computing Workshop â"" HCW 2001 (Workshop 1) - Volume 2
On Scheduling Mesh-Structured Computations for Internet-Based Computing
IEEE Transactions on Computers
Guidelines for Scheduling Some Common Computation-Dags for Internet-Based Computing
IEEE Transactions on Computers
On Scheduling Complex Dags for Internet-Based Computing
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers - Volume 01
Distributed computing in practice: the Condor experience: Research Articles
Concurrency and Computation: Practice & Experience - Grid Performance
Parallel scheduling of complex dags under uncertainty
Proceedings of the seventeenth annual ACM symposium on Parallelism in algorithms and architectures
The Anatomy of the Grid: Enabling Scalable Virtual Organizations
International Journal of High Performance Computing Applications
IEEE Transactions on Parallel and Distributed Systems
Evaluation of Eligible Jobs Maximization Algorithm for DAG Scheduling in Grids
ICCS '08 Proceedings of the 8th international conference on Computational Science, Part I
Investigation of the DAG eligible jobs maximization algorithm in a grid
GRID '08 Proceedings of the 2008 9th IEEE/ACM International Conference on Grid Computing
Extending IC-scheduling via the Sweep Algorithm
Journal of Parallel and Distributed Computing
An open computing resource management framework for real-time computing
HiPC'08 Proceedings of the 15th international conference on High performance computing
Area-maximizing schedules for series-parallel DAGs
Euro-Par'10 Proceedings of the 16th international Euro-Par conference on Parallel processing: Part II
Assessing the computational benefits of AREA-oriented DAG-scheduling
Euro-Par'11 Proceedings of the 17th international conference on Parallel processing - Volume Part I
Performing dynamically injected tasks on processes prone to crashes and restarts
DISC'11 Proceedings of the 25th international conference on Distributed computing
On scheduling dag s for volatile computing platforms: Area-maximizing schedules
Journal of Parallel and Distributed Computing
Using relative costs in workflow scheduling to cope with input data uncertainty
Proceedings of the 10th International Workshop on Middleware for Grids, Clouds and e-Science
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Conceptual and algorithmic tools are developed as a foundation for a theory of scheduling complex computation-dags for Internet-based computing. The goal of the schedules produced is to render tasks eligible for allocation to remote clients (hence, for execution) at the maximum possible rate. This allows one to utilize remote clients well, as well as to lessen the likelihood of the "gridlock” that ensues when a computation stalls for lack of eligible tasks. Earlier work has introduced a formalism for studying this optimization problem and has identified optimal schedules for several significant families of structurally uniform dags. The current paper extends this work via a methodology for devising optimal schedules for a much broader class of complex dags, which are obtained via composition from a prespecified collection of simple building-block dags. The paper provides a suite of algorithms that decompose a given dag {\cal G} to expose its building blocks and an execution-priority relation \triangleright on building blocks. When the building blocks are appropriately interrelated under \triangleright, the algorithms specify an optimal schedule for {\cal G}.