TY - GEN
T1 - Energy-optimal batching periods for asynchronous multistage data processing on sensor nodes
T2 - 16th IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS 2010
AU - Cao, Qing
AU - Wang, Dong
AU - Abdelzaher, Tarek
AU - Priyantha, Bodhi
AU - Liu, Jie
AU - Zhao, Feng
PY - 2010
Y1 - 2010
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=77953853934&partnerID=8YFLogxK
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U2 - 10.1109/RTAS.2010.16
DO - 10.1109/RTAS.2010.16
M3 - Conference contribution
AN - SCOPUS:77953853934
SN - 9780769540016
T3 - Real-Time Technology and Applications - Proceedings
SP - 101
EP - 110
BT - Proceedings of the 16th IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS 2010
Y2 - 12 April 2010 through 15 April 2010
ER -