Power-aware task motion for enhancing dynamic range of embedded systems with renewable energy sources

Authors:
Jinfeng Liu;Pai H. Chou;Nader Bagherzadeh
Affiliations:
Department of Electrical and Computer Engineering, University of California, Irvine, CA;Department of Electrical and Computer Engineering, University of California, Irvine, CA;Department of Electrical and Computer Engineering, University of California, Irvine, CA
Venue:
PACS'02 Proceedings of the 2nd international conference on Power-aware computer systems
Year:
2002

Citing 15
Cited 1

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Abstract

In this paper we propose a novel scheduling framework for a dynamic real-time environment that experiences power consumption constraints. This framework is capable of dynamically adjusting the voltage/ speed of the system, such that no task in the system misses its deadline and the total energy savings of the system are maximized. Each task in the system consumes a certain amount of energy, which depends on a speed chosen for execution. The process of selecting speeds for execution while maximizing the energy savings of the system requires the exploration of a large number of combinations, which is too time consuming to be computed on-line. Thus, we propose an integrated heuristic methodology which executes an optimization procedure and an approximate greedy algorithm in a low computation time. This scheme allows the scheduler to handle power-aware real-time tasks with low cost while maximizing the use of the available resources and without jeopardizing the temporal constraints of the system. Simulation results show that our heuristic methodology achieves a performance with near-optimal results.