Abstract
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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Wang, D., Abdelzaher, T., Priyantha, B. et al. Energy-optimal Batching periods for asynchronous multistage data processing on sensor nodes: foundations and an mPlatform case study. Real-Time Syst 48, 135–165 (2012). https://doi.org/10.1007/s11241-011-9138-5
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DOI: https://doi.org/10.1007/s11241-011-9138-5