Voltage scheduling problem for dynamically variable voltage processors
ISLPED '98 Proceedings of the 1998 international symposium on Low power electronics and design
On-line scheduling of hard real-time tasks on variable voltage processor
Proceedings of the 1998 IEEE/ACM international conference on Computer-aided design
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Proceedings of the 36th annual ACM/IEEE Design Automation Conference
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Proceedings of the 2001 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
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Proceedings of the 38th annual Design Automation Conference
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IEEE Design & Test
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FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
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RTSS '02 Proceedings of the 23rd IEEE Real-Time Systems Symposium
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ACM Transactions on Embedded Computing Systems (TECS)
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RTSS '01 Proceedings of the 22nd IEEE Real-Time Systems Symposium
Dynamic voltage scaling under EDF revisited
Real-Time Systems
A calculus approach to energy-efficient data transmission with quality-of-service constraints
IEEE/ACM Transactions on Networking (TON)
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IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
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We present an algorithm for scheduling a set of nonrecurrent tasks (or jobs) with FIFO real-time constraints so as to minimize the total energy consumed when the tasks are performed on a dynamically variable voltage processor. Our algorithm runs in linear time and thus, in this case, is an improvement over the classical algorithm of Yao et al. It was inspired by considering the problem as a shortest-path problem. We also propose an algorithm to deal with the case where the processor has only a limited number of clock frequencies. This algorithm gives the optimum schedule with the minimum number of speed changes, which is important when the speed switching overhead cannot be neglected. All our algorithms are linear in the number of tasks if the arrivals and deadlines are sorted and otherwise need O(N log N) time. These complexities are shown to be the best possible. Finally, we extend our results to fluid tasks and to nonconvex cost functions.