This paper derives energy-optimal batching periods

for asynchronous multistage data processing on sensor

nodes in the sense of minimizing energy consumption

while meeting end-to-end deadlines. Batching the processing

of (sensor) data maximizes processor sleep periods,

hence minimizing the wakeup frequency and the

corresponding overhead. The algorithm is evaluated on

mPlatform, a next-generation heterogeneous sensor node

platform equipped with both a low-end microcontroller

(MSP430) and a higher-end embedded systems processor

(ARM). Experimental results show that the total energy

consumption of mPlatform, when processing data flows

at their optimal batching periods, is up to 35% lower than

that for uniform period assignment. Moreover, processing

data at the appropriate processor can use as much as

80% less energy than running the same task set on the

ARM alone and 25% less energy than running the task

set on the MSP430 alone.

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In  Proc. of IEEE Real Time Technology and Applications Symposium (RTAS2010)

Publisher  IEEE Computer Society

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