Tradeoff exploration between reliability, power consumption, and execution time for embedded systems.
Saved in:
| Title: | Tradeoff exploration between reliability, power consumption, and execution time for embedded systems. |
|---|---|
| Authors: | Assayad, Ismail1, Girault, Alain2 alain.girault@inria.fr, Kalla, Hamoudi3 |
| Source: | International Journal on Software Tools for Technology Transfer. Jun2013, Vol. 15 Issue 3, p229-245. 17p. |
| Subjects: | Conjoint analysis, Multidisciplinary design optimization, Reliability (Personality trait), Probability theory, Heuristic |
| Abstract: | For autonomous critical real-time embedded (e.g., satellite), guaranteeing a very high level of reliability is as important as keeping the power consumption as low as possible. We propose an off-line scheduling heuristic which, from a given software application graph and a given multiprocessor architecture (homogeneous and fully connected), produces a static multiprocessor schedule that optimizes three criteria: its length (crucial for real-time systems), its reliability (crucial for dependable systems), and its power consumption (crucial for autonomous systems). Our tricriteria scheduling heuristic, called TSH, uses the active replication of the operations and the data-dependencies to increase the reliability and uses dynamic voltage and frequency scaling to lower the power consumption. We demonstrate the soundness of TSH. We also provide extensive simulation results to show how TSH behaves in practice: first, we run TSH on a single instance to provide the whole Pareto front in 3D; second, we compare TSH versus the ECS heuristic (Energy-Conscious Scheduling) from the literature; and third, we compare TSH versus an optimal Mixed Linear Integer Program. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal on Software Tools for Technology Transfer is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
Be the first to leave a comment!
