MARS—a framework for minimizing the job execution time in a metacomputing environment
Future Generation Computer Systems - Special issue: resource management in distributed systems
Application-level scheduling on distributed heterogeneous networks
Supercomputing '96 Proceedings of the 1996 ACM/IEEE conference on Supercomputing
An Empirical Investigation of Load Indices for Load Balancing Applications
Performance '87 Proceedings of the 12th IFIP WG 7.3 International Symposium on Computer Performance Modelling, Measurement and Evaluation
HPDC '02 Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing
Automated Learning of Workload Measures for Load Balancing on a Distributed System
ICPP '93 Proceedings of the 1993 International Conference on Parallel Processing - Volume 03
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A new architecture for scheduling an open-ended set of medical post processing applications in clusters is described in this work. The scheduler takes into consideration the characteristics of the set of currently executing applications as well as the incoming request to ensure optimal application performance. The approach uses a feedback mechanism to learn the resource requirements of an application and is non-intrusive. The scheduler is not tightly coupled with the applications and therefore can schedule an open-ended set of applications.