CO-GPS: Energy Efficient GPS Sensing with Cloud Offloading

Location is a fundamental service for mobile computing. Typical GPS receivers, although widely available for navigation purposes, may consume too much energy to be useful for many applications. Observing that in many sensing scenarios, the location information can be post-processed when the data is...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on mobile computing 2016-06, Vol.15 (6), p.1348-1361
Main Authors: Jie Liu, Priyantha, Bodhi, Hart, Ted, Yuzhe Jin, Woosuk Lee, Raghunathan, Vijay, Ramos, Heitor S., Qiang Wang
Format: Magazinearticle
Language:English
Subjects:
Assisted GPS
Cloud-offloading
Coarse-time Navigation
Detection
Earth
Energy consumption
Global Positioning System
Location
Mathematical models
Mobile computing
Raw
Receivers
Satellite navigation systems
Satellites
Sensing devices
Sensors
Synchronization
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Location is a fundamental service for mobile computing. Typical GPS receivers, although widely available for navigation purposes, may consume too much energy to be useful for many applications. Observing that in many sensing scenarios, the location information can be post-processed when the data is uploaded to a server, we design a cloud-offloaded GPS (CO-GPS) solution that allows a sensing device to aggressively duty-cycle its GPS receiver and log just enough raw GPS signal for post-processing. Leveraging publicly available information such as GNSS satellite ephemeris and an Earth elevation database, a cloud service can derive good quality GPS locations from a few milliseconds of raw data. Using our design of a portable sensing device platform called CLEON, we evaluate the accuracy and efficiency of the solution. Compared to more than 30 seconds of heavy signal processing on standalone GPS receivers, we can achieve three orders of magnitude lower energy consumption per location tagging.
ISSN:1536-1233
1558-0660
DOI:10.1109/TMC.2015.2446461