Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment
Journal of the ACM (JACM)
Real-time dynamic voltage scaling for low-power embedded operating systems
SOSP '01 Proceedings of the eighteenth ACM symposium on Operating systems principles
An Adaptive, Distributed Airborne Tracking System ("process the Right Tracks at the Right Time")
Proceedings of the 11 IPPS/SPDP'99 Workshops Held in Conjunction with the 13th International Parallel Processing Symposium and 10th Symposium on Parallel and Distributed Processing
Power aware computing
A Power-Aware, Best-Effort Real-Time Task Scheduling Algorithm
WSTFES '03 Proceedings of the IEEE Workshop on Software Technologies for Future Embedded Systems
Dynamic and Aggressive Scheduling Techniques for Power-Aware Real-Time Systems
RTSS '01 Proceedings of the 22nd IEEE Real-Time Systems Symposium
Best-effort decision-making for real-time scheduling
Best-effort decision-making for real-time scheduling
Scheduling dependent real-time activities
Scheduling dependent real-time activities
Balancing batteries, power, and performance: system issues in cpu speed-setting for mobile computing
Balancing batteries, power, and performance: system issues in cpu speed-setting for mobile computing
Energy-efficient soft real-time CPU scheduling for mobile multimedia systems
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
Energy-Efficient, Utility Accrual Real-Time Scheduling Under the Unimodal Arbitrary Arrival Model
Proceedings of the conference on Design, Automation and Test in Europe - Volume 1
Utility Accrual Real-Time Scheduling Under the Unimodal Arbitrary Arrival Model with Energy Bounds
IEEE Transactions on Computers
An experimental evaluation of real-time DVFS scheduling algorithms
Proceedings of the 5th Annual International Systems and Storage Conference
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We present a CPU scheduling algorithm, called Energy-efficient Utility Accrual Algorithm (or EUA), for battery-powered, embedded real-time systems. We consider an embedded software application model where repeatedly occurring application activities are subject to deadline constraints specified using step time/utility functions. For battery-powered embedded systems, system-level energy consumption is also a primary concern. We consider CPU scheduling that (1) provides assurances on individual and collective application timeliness behaviors and (2) maximizes system-level timeliness and energy efficiency. Since the scheduling problem is intractable, EUA heuristically computes CPU schedules with a polynomial-time cost. Several properties of EUA are analytically established, including timeliness optimality during under-load situations and statistical assurances on timeliness behavior. Further, our simulation results confirm EUA's superior performance.