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Sensors 2017, 17(12), 2763; https://doi.org/10.3390/s17122763

Symbiotic Sensing for Energy-Intensive Tasks in Large-Scale Mobile Sensing Applications

1
Pervasive Systems Group, Department of Computer Science, University of Twente, Drienerlolaan 5, 7522 NB Enschede, The Netherlands
2
The Australian e-Health Research Centre, CSIRO, Herston, Queensland 4029, Australia
Current address: Zilverling 5007, University of Twente, Drienerlolaan 5, 7522 NB Enschede, The Netherlands.
*
Author to whom correspondence should be addressed.
Received: 4 October 2017 / Revised: 24 November 2017 / Accepted: 26 November 2017 / Published: 29 November 2017
(This article belongs to the Special Issue Ubiquitous Massive Sensing Using Smartphones)
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Abstract

Energy consumption is a critical performance and user experience metric when developing mobile sensing applications, especially with the significantly growing number of sensing applications in recent years. As proposed a decade ago when mobile applications were still not popular and most mobile operating systems were single-tasking, conventional sensing paradigms such as opportunistic sensing and participatory sensing do not explore the relationship among concurrent applications for energy-intensive tasks. In this paper, inspired by social relationships among living creatures in nature, we propose a symbiotic sensing paradigm that can conserve energy, while maintaining equivalent performance to existing paradigms. The key idea is that sensing applications should cooperatively perform common tasks to avoid acquiring the same resources multiple times. By doing so, this sensing paradigm executes sensing tasks with very little extra resource consumption and, consequently, extends battery life. To evaluate and compare the symbiotic sensing paradigm with the existing ones, we develop mathematical models in terms of the completion probability and estimated energy consumption. The quantitative evaluation results using various parameters obtained from real datasets indicate that symbiotic sensing performs better than opportunistic sensing and participatory sensing in large-scale sensing applications, such as road condition monitoring, air pollution monitoring, and city noise monitoring. View Full-Text
Keywords: participatory sensing; opportunistic sensing; success probability; energy consumption; mobile sensing; massive sensing participatory sensing; opportunistic sensing; success probability; energy consumption; mobile sensing; massive sensing
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Le, D.V.; Nguyen, T.; Scholten, H.; Havinga, P.J.M. Symbiotic Sensing for Energy-Intensive Tasks in Large-Scale Mobile Sensing Applications. Sensors 2017, 17, 2763.

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