Energy-optimal Batching periods for asynchronous multistage data processing on sensor nodes: Foundations and an mPlatform case study

Dong Wang, Tarek Abdelzaher, Bodhi Priyantha, Jie Liu, Feng Zhao

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Pages (from-to)135-165
Number of pages31
JournalReal-Time Systems
Volume48
Issue number2
DOIs
StatePublished - Mar 1 2012

Keywords

  • Energy optimization
  • Heterogeneous platform
  • Real-time systems
  • Sensor network

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Computer Science Applications
  • Computer Networks and Communications
  • Control and Optimization
  • Electrical and Electronic Engineering

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