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Reliability-Aware Energy Management for Periodic Real-Time Tasks
 

Summary: Reliability-Aware Energy Management
for Periodic Real-Time Tasks
Dakai Zhu, Member, IEEE, and Hakan Aydin, Member, IEEE
Abstract--Dynamic Voltage and Frequency Scaling (DVFS) has been widely used to manage energy in real-time embedded systems.
However, it was recently shown that DVFS has direct and adverse effects on system reliability. In this work, we investigate static and
dynamic reliability-aware energy management schemes to minimize energy consumption for periodic real-time systems while
preserving system reliability. Focusing on earliest deadline first (EDF) scheduling, we first show that the static version of the problem is
NP-hard and propose two task-level utilization-based heuristics. Then, we develop a job-level online scheme by building on the idea of
wrapper-tasks, to monitor and manage dynamic slack efficiently in reliability-aware settings. The feasibility of the dynamic scheme is
formally proved. Finally, we present two integrated approaches to reclaim both static and dynamic slack at runtime. To preserve
system reliability, the proposed schemes incorporate recovery tasks/jobs into the schedule as needed, while still using the remaining
slack for energy savings. The proposed schemes are evaluated through extensive simulations. The results confirm that all the
proposed schemes can preserve the system reliability, while the ordinary (but reliability-ignorant) energy management schemes result
in drastically decreased system reliability. For the static heuristics, the energy savings are close to what can be achieved by an optimal
solution by a margin of 5 percent. By effectively exploiting the runtime slack, the dynamic schemes can achieve additional energy
savings while preserving system reliability.
Index Terms--Real-time systems, periodic tasks, earliest deadline first (EDF) scheduling, dynamic voltage and frequency scaling
(DVFS), reliability, transient faults, backward recovery.

1 INTRODUCTION

  

Source: Aydin, Hakan - Department of Computer Science, George Mason University

 

Collections: Computer Technologies and Information Sciences; Engineering