Keywords and Phrases
Approximation Ratio; DVFS; Mixed-Criticality; Precise; Speedup; Sustainability
"In this thesis, the imprecise mixed-criticality model (IMC) is extended to precise scheduling of tasks, and integrated with the dynamic voltage and frequency scaling (DVFS) technique to enable energy minimization. The challenge in precise scheduling of MC systems is to simultaneously guarantee the timing correctness for all tasks, hi and lo, under both pessimistic and optimistic (less pessimistic) assumptions. To the best of knowledge this is the first work to address the integration of DVFS energy conserving techniques with precise scheduling of lo-tasks of the MC model.
In this thesis, the utilization based schedulability tests and sufficient conditions for such systems under Earliest Deadline First EDF-VD scheduling policy are presented. Quantitative study in the forms of speedup bound and approximation ratio are also proved for the unified model. Extensive experimental studies are conducted to verify the theoretical results as well as the effectiveness of the proposed algorithm.
In safety- critical systems, it is essential to perform schedulability analysis prior to run-time. Parameters characterizing the run-time workload are generated by pessimistic techniques; hence, adopting conservative estimates may result in systems performing much better than anticipated during run-time. This thesis also addresses the following questions associated to the better performance of the task system: (i) How does parameter change affect the schedulability of a task set (system)? (ii) In the event that a mixed-criticality system design is deemed schedulable and specific part/parts of the system are reassigned to be of low-criticality, is the system still safe to run? (iii) If a system is presumed to be non-schedulable, does it invariably benefit to reduce the criticality of some task?
To answer these questions, in this thesis, we not only study the property of sustainability with regards to criticality levels, but also revisit sustainability of several uniprocessor and multiprocessor scheduling policies with respect to other parameters"--Abstract, page iii.
Madria, Sanjay Kumar
M.S. in Computer Science
Missouri University of Science and Technology
xi, 62 pages
© 2018 Sai Sruti, All rights reserved.
Thesis - Open Access
Electronic OCLC #
Sruti, Sai, "Precise energy efficient scheduling of mixed-criticality tasks & sustainable mixed-criticality scheduling" (2018). Masters Theses. 7809.