Model-driven placement of compute tasks and data in a networked utility
Published
Journal Article
An important problem in resource management for networked resource-sharing systems is the simultaneous allocation of multiple resources to an application. Self-optimizing systems must co-allocate resources in a way that reconciles competing demands and maximizes global system objectives under dynamic conditions. We propose a simple model-driven approach to estimate the performance of a candidate assignment of resources, and select the best candidate to meet local or global goals. In this work, we address the placement of batch compute tasks and data in a network of compute and storage sites. We use the model to select placements for a set of synthetic benchmarks and a functional MRI processing application. Our experiments show that the model predicts the performance of candidate assignments within 10% of the empirical values.
Full Text
Duke Authors
Cited Authors
- Shivam, P; Iamnitchi, A; Yumerefendi, AR; Chase, JS
Published Date
- December 1, 2005
Published In
- Proceedings Second International Conference on Autonomic Computing, Icac 2005
Volume / Issue
- 2005 /
Start / End Page
- 344 - 345
Digital Object Identifier (DOI)
- 10.1109/ICAC.2005.41
Citation Source
- Scopus