Scheduling Strategies for Master-Slave Tasking on Heterogeneous Processor Platforms
IEEE Transactions on Parallel and Distributed Systems
BOINC: A System for Public-Resource Computing and Storage
GRID '04 Proceedings of the 5th IEEE/ACM International Workshop on Grid Computing
SBAC-PAD '05 Proceedings of the 17th International Symposium on Computer Architecture on High Performance Computing
Practical Scheduling of Bag-of-Tasks Applications on Grids with Dynamic Resilience
IEEE Transactions on Computers
The performance of bags-of-tasks in large-scale distributed systems
HPDC '08 Proceedings of the 17th international symposium on High performance distributed computing
SimGrid: A Generic Framework for Large-Scale Distributed Experiments
UKSIM '08 Proceedings of the Tenth International Conference on Computer Modeling and Simulation
Centralized versus Distributed Schedulers for Bag-of-Tasks Applications
IEEE Transactions on Parallel and Distributed Systems
Toward a fully decentralized algorithm for multiple bag-of-tasks application scheduling on grids
GRID '08 Proceedings of the 2008 9th IEEE/ACM International Conference on Grid Computing
Scheduling Concurrent Bag-of-Tasks Applications on Heterogeneous Platforms
IEEE Transactions on Computers
Self-Healing of Operational Workflow Incidents on Distributed Computing Infrastructures
CCGRID '12 Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)
Self-healing of workflow activity incidents on distributed computing infrastructures
Future Generation Computer Systems
Fair scheduling of bag-of-tasks applications using distributed Lagrangian optimization
Journal of Parallel and Distributed Computing
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The bag-of-tasks application model, albeit simple, arises in many application domains and has received a lot of attention in the scheduling literature. Previous works propose either theoretically sound solutions that rely on unrealistic assumptions, or ad-hoc heuristics with no guarantees on performance. This work attempts to bridge this gap through the design of non-clairvoyant heuristics based on solid theoretical foundations. The performance achieved by these heuristics is studied via simulations in a view to comparing them both to previously proposed solutions and to theoretical upper bounds on achievable performance. Also, an interesting theoretical result in this work is that a straightforward on-demand heuristic delivers asymptotically optimal performance when the communications or the computations can be neglected.