Autonomic Computing, International Conference on (2005)
June 13, 2005 to June 16, 2005
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICAC.2005.41
Piyush Shivam , Durham NC
Adriana Iamnitchi , Durham NC
Aydan R. Yumerefendi , Durham NC
Jeffrey S. Chase , Durham NC
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.
A. R. Yumerefendi, A. Iamnitchi, P. Shivam and J. S. Chase, "Model-Driven Placement of Compute Tasks and Data in a Networked Utility," Autonomic Computing, International Conference on(ICAC), Seattle, Washington, 2005, pp. 344-345.