Improving energy efficiency of personal sensing applications with heterogeneous multi-processors

  • Authors:

  • Moo-Ryong Ra;Bodhi Priyantha;Aman Kansal;Jie Liu

  • Affiliations:

  • University of Southern California;Microsoft Research Redmond;Microsoft Research Redmond;Microsoft Research Redmond

  • Venue:
  • Proceedings of the 2012 ACM Conference on Ubiquitous Computing
  • Year:
  • 2012

Quantified Score

Hi-index 0.00

Visualization

Abstract

The availability of multiple sensors on mobile devices offers a significant new capability to enable rich user and context aware applications. Many of these applications run in the background to continuously sense user context. However, running these applications on mobile devices can impose a significant stress on the battery life, and the use of supplementary low-power processors has been proposed on mobile devices for continuous background activities. In this paper, we experimentally and analytically investigate the design considerations that arise in the efficient use of the low power processor and provide a thorough understanding of the problem space. We answer fundamental questions such as which segments of the application are most efficient to be hosted on the low power processor, and how to select an appropriate low power processor. We discuss our measurements, analysis, and results using multiple low power processors and existing phone platforms.