EnTracked: energy-efficient robust position tracking for mobile devices

By Mikkel Baun Kjærgaard, J. L. Jensen, Torben Godsk, Thomas Toftkjær. ACM SIGMOBILE International Conference on Mobile Systems, Applications, and Services, 2009

306 citations recorded by the source corpus.

An important feature of a modern mobile device is that it can position itself. Not only for use on the device but also for remote applications that require tracking of the device. To be useful, such position tracking has to be energy-efficient to avoid having a major impact on the battery life of the mobile device. Furthermore, tracking has to robustly deliver position updates when faced with changing conditions such as delays due to positioning and communication, and changing positioning accuracy. This work proposes EnTracked - a system that, based on the estimation and prediction of system conditions and mobility, schedules position updates to both minimize energy consumption and optimize robustness. The realized system tracks pedestrian targets equipped with GPS-enabled devices. The system is configurable to realize different trade-offs between energy consumption and robustness. We provide extensive experimental results by profiling how devices consume power, by emulation on collected data and by validation in several real-world deployments. Results from this profiling show how a device consumes power while tracking its position. Results from the emulation indicate that the system can estimate and predict system conditions and mobility. Furthermore they provide evidence for that the system can lower the energy consumption considerably and remain robust when faced with changing system conditions. By validation in several real-world deployments we provide evidence that the real system works as predicted by the emulation.

Subfields: Computer Networks and Communications, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/92b6630705cac7759add0eb28790e4661ef11ade

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Citations in the corpus

Energy-efficient rate-adaptive GPS-based positioning for smartphones (2010, methodology): “There is a significant literature on the effectiveness of using an accelerometer to detect whether the user is moving or not [12, 27, 3].”
SurroundSense: mobile phone localization via ambience fingerprinting (2009, background): “Independent research is in progress on energyefficient localization and sensing [6,15,29] – we believe SurroundSense will benefit from these works.”
Energy-accuracy trade-off for continuous mobile device location (2010, methodology): “A-Loc uses time granularity of 1 minute, which is the same order of magnitude as in [12].”
ParkUs: A Novel Vehicle Parking Detection System (2017, background): “Although it’s been nearly a decade since its Yang and Cho 2014; Kjærgaard et al. 2009; Perrucci, Fitzek, and Widmer 2011) have evaluated and veriﬁed its sensor’s power consumption.”
SensLoc: sensing everyday places and paths using less energy (2010, methodology): “We collect GPS fixes periodically for path tracking but other positioning systems or energy saving mechanisms may be used [20, 25, 6, 15].”
A Survey of Green Mobile Networks: Opportunities and Challenges (2011, background): “For instance, the work in [60] and [70] reduce power consumption based on mobility prediction, but the prediction fails in worst cases, which may lead to seriously degraded performance.”