Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
IPPS/SPDP '98 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
JSSPP '02 Revised Papers from the 8th International Workshop on Job Scheduling Strategies for Parallel Processing
GridWorkflow: A Flexible Failure Handling Framework for the Grid
HPDC '03 Proceedings of the 12th IEEE International Symposium on High Performance Distributed Computing
Scheduling with Advanced Reservations
IPDPS '00 Proceedings of the 14th International Symposium on Parallel and Distributed Processing
TransLight: a global-scale LambdaGrid for e-science
Communications of the ACM - Blueprint for the future of high-performance networking
Towards Ontology-Driven P2P Grid Resource Discovery
GRID '04 Proceedings of the 5th IEEE/ACM International Workshop on Grid Computing
Impact of Laxity on Scheduling with Advance Reservations in Grids
MASCOTS '05 Proceedings of the 13th IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems
The virtual resource manager: an architecture for SLA-aware resource management
CCGRID '04 Proceedings of the 2004 IEEE International Symposium on Cluster Computing and the Grid
ReGS: user-level reliability in a grid environment
CCGRID '05 Proceedings of the Fifth IEEE International Symposium on Cluster Computing and the Grid (CCGrid'05) - Volume 2 - Volume 02
A distributed load-based failure recovery mechanism for advance reservation environments
CCGRID '05 Proceedings of the Fifth IEEE International Symposium on Cluster Computing and the Grid (CCGrid'05) - Volume 2 - Volume 02
Hi-index | 0.00 |
For resource management in Grid environments, advance reservations turned out to be very useful and hence are supported by a variety of Grid toolkits. However, failure recovery for such systems has not yet received the attention it deserves. In this paper, we address the problem of remapping reservations to other resources, when the originally selected resource fails. Instead of dealing with jobs already running, which usually means checkpointing and migration, our focus is on jobs that are scheduled on the failed resource for a specific future period of time but not started yet. The most critical factor when solving this problem is the estimation of the downtime. We avoid the drawbacks of under- or over-estimating the downtime by a dynamic load-based approach that is evaluated by extensive simulations in a Grid environment and shows superior performance compared to estimation-based approaches.