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/lp/inderscience-publishers/scheduling-policy-design-for-autonomic-systems-UXPYP0odjS
- Publisher
- Inderscience Publishers
- Copyright
- Copyright © Inderscience Enterprises Ltd. All rights reserved
- ISSN
- 1754-8632
- eISSN
- 1754-8640
- DOI
- 10.1504/IJAACS.2009.026786
- Publisher site
- See Article on Publisher Site
Abstract
Scheduling the execution of multiple concurrent tasks on shared resources such as CPUs and network links is essential to ensuring the reliable operation of many autonomic systems. Well-known techniques such as rate-monotonic scheduling can offer rigorous timing and preemption guarantees, but only under assumptions (i.e. a fixed set of tasks with well-known execution times and invocation rates) that do not hold in many autonomic systems. New hierarchical scheduling techniques are better suited to enforce the more flexible execution constraints and enforcement mechanisms that are required for autonomic systems, but a rigorous and efficient foundation for verifying and enforcing concurrency and timing guarantees is still needed for these approaches. This paper summarises our previous work on addressing these challenges, on Markov decision process-based scheduling policy design and on wrapping repeated structure of the scheduling state spaces involved into a more efficient model, and presents a new algorithm called expanding state policy iteration (ESPI), that allows us to compute the optimal policy for a wrapped state model.
Journal
International Journal of Autonomous and Adaptive Communications Systems – Inderscience Publishers
Published: Jan 1, 2009