Title
On Maximizing Reliability of Real-Time Embedded Applications Under Hard Energy Constraint
Abstract
The dynamic voltage and frequency scaling (DVFS) technique is the basis of numerous state-of-the-art energy management schemes proposed for real-time embedded systems. However, recent research has illustrated the alarmingly negative impact of DVFS on task and system reliability. In this paper, we consider the problem of assigning processing frequencies to a set of real-time tasks in order to maximize the overall reliability, under given time and energy constraints. First, under the frame-based task model, we formulate the problem as a nonlinear optimization problem and show how to obtain the static optimal solution. Then, we propose online (dynamic) algorithms that detect early completions and adjust the task frequencies at runtime, to improve overall reliability. Furthermore, we extend these solutions to the periodic task model, with both static and dynamic solutions. All our solutions ensure that all timing constraints are met while the cumulative energy consumption of tasks does not exceed the given energy budget. Our simulation results indicate that our algorithms perform comparably to a clairvoyant optimal scheduler that knows the exact workload in advance.
Year
DOI
Venue
2010
10.1109/TII.2010.2051970
IEEE Trans. Industrial Informatics
Keywords
Field
DocType
optimisation,power aware computing,frame-based task model,cumulative energy consumption,real-time embedded systems,dynamic voltage and frequency scaling technique,energy management systems,nonlinear optimization problem,reliability,system reliability,hard energy constraint,task reliability,dynamic voltage and frequency scaling,energy management schemes,embedded systems,clairvoyant optimal scheduler,maximizing reliability,energy budget,energy management,embedded system,nonlinear optimization,frequency,real time,cumulant,real time systems
Dynamic voltage scaling,Energy management,Computer science,Workload,Nonlinear optimization problem,Voltage,Real-time computing,Frequency scaling,Energy consumption,Periodic graph (geometry)
Journal
Volume
Issue
ISSN
6
3
1551-3203
Citations 
PageRank 
References 
29
0.93
35
Authors
3
Name
Order
Citations
PageRank
Baoxian Zhao12117.69
Hakan Aydin2121861.97
Da-Kai Zhu3140566.97