Effects of Response and Stability on Scheduling in Distributed Computing Systems
IEEE Transactions on Software Engineering
Adaptive Optimal Load Balancing in a Nonhomogeneous Multiserver System with a Central Job Scheduler
IEEE Transactions on Computers
Parallel machines scheduling with nonsimultaneous machine available time
Discrete Applied Mathematics
Improved Utilization and Responsiveness with Gang Scheduling
IPPS '97 Proceedings of the Job Scheduling Strategies for Parallel Processing
Scheduling Distributed Applications: the SimGrid Simulation Framework
CCGRID '03 Proceedings of the 3st International Symposium on Cluster Computing and the Grid
Job-Length Estimation and Performance in Backfilling Schedulers
HPDC '99 Proceedings of the 8th 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
A Study of Deadline Scheduling for Client-Server Systems on the Computational Grid
HPDC '01 Proceedings of the 10th IEEE International Symposium on High Performance Distributed Computing
PAPER: influence of deterministic customers in time sharing scheduler
ACM SIGOPS Operating Systems Review
Models for Dynamic Load Balancing in a Heterogeneous Multiple Processor System
IEEE Transactions on Computers
Telecommunication network modeling and planning tool on ASP clusters
ICCS'03 Proceedings of the 2003 international conference on Computational science: PartIII
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Clusters and computational grids are opened environments on which a great number of different users can submit computational requests. Some privileged users may have strong Quality of Service requirements whereas others may be less demanding. Common mapping algorithms are not well suited to guarantee a defined quality of service, they propose at best priority systems in order to favour some applications without any guaranty. We propose a new mapping algorithm, dealing with the notion of quality of service for scheduling applications over clusters and grids over different classes of service. This algorithm uses information on the application to map, all the unfinished applications previously mapped, the state of the execution support, and the processor access model (round robin model) to suggest a mapping which guarantees all the expressed constraints. The mapping decision is taken on-line based on the release date of all applications and the memory space used. To finish, the validation of the algorithm is performed with real log files entries simulated with Simgrid.