The Community for Technology Leaders
Autonomic Computing, International Conference on (2005)
Seattle, Washington
June 13, 2005 to June 16, 2005
ISBN: 0-7965-2276-9
pp: 344-345
Adriana Iamnitchi , Durham NC
Piyush Shivam , 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.
Aydan R. Yumerefendi, Adriana Iamnitchi, Piyush Shivam, Jeffrey S. Chase, "Model-Driven Placement of Compute Tasks and Data in a Networked Utility", Autonomic Computing, International Conference on, vol. 00, no. , pp. 344-345, 2005, doi:10.1109/ICAC.2005.41
92 ms
(Ver 3.3 (11022016))