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Optimistic Reliability Aware Energy Management for Real-Time Tasks with Probabilistic Execution Times
 

Summary: Optimistic Reliability Aware Energy Management for Real-Time Tasks with
Probabilistic Execution Times
Dakai Zhu Hakan Aydin Jian-Jia Chen
Univ. of Texas at San Antonio George Mason Univ. Swiss Federal Inst. of Technology
San Antonio, TX, 78249 Fairfax, VA 22030 Zurich, Switzerland
dzhu@cs.utsa.edu aydin@cs.gmu.edu chen@tik.ee.ethz.ch
Abstract
Reliability-aware power management (RAPM)
schemes have been recently studied to save energy
while preserving system reliability. The existing RAPM
schemes, however, provision for worst-case execution
scenarios and are rather conservative. In this paper, by
exploiting the probabilistic execution time information of
real-time tasks, we develop an optimistic RAPM scheme.
Instead of scheduling a full recovery for tasks whose
executions are scaled down, the new scheme puts aside
just enough slack to guarantee the required reliability
leave while leaving more slack for energy management to
achieve better energy savings. The problem is shown to
be NP-hard and a novel heuristic algorithm is proposed

  

Source: Aydin, Hakan - Department of Computer Science, George Mason University
Zhu, Dakai - Department of Computer Science, University of Texas at San Antonio

 

Collections: Computer Technologies and Information Sciences; Engineering