Abstract
A dynamic voltage scaling (DVS) technique for embedded systems expressed as conditional task graphs (CTGs) is described. The idea is to identify and exploit the available worst case slack time, taking into account the conditional behaviour of CTGs. Also the effect of combining a genetic algorithm based mapping with the DVS technique is examined and it is shown that further energy reduction can be achieved. The techniques are tested on a number of CTGs including a real-life example. The results show that the DVS technique can be applied to CTGs with an energy saving of up to 24%. Furthermore, it is shown that savings of up to 51% are achieved by considering DVS during the mapping optimisation. Finally, the impact of communications and communication link selection on the scheduling and mapping technique is investigated and results are reported.
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