skip to main content
10.1145/2676727.2676729acmotherconferencesArticle/Chapter ViewAbstractPublication PagesmiddlewareConference Proceedingsconference-collections
research-article

Virtual GPS: a middleware for power efficient localization of smartphones using cross layer approach

Published: 08 December 2014 Publication History

Abstract

Location based smartphone services such as maps and context-aware advertisements are increasingly becoming popular. However, a major limitation of these services is that they tend to consume significant power due to the usage of power-hungry GPS receivers. This paper proposes Virtual GPS, a middleware layer that provides current location to the applications in a power efficient manner using our novel cross layer approach. A number of mechanisms such as GPS, WiFi signatures[14], crowd sourcing, mobility tracking, etc. can be used to determine the current smartphone location. All these mechanisms differ from one another in terms of their power consumption and location accuracy. Virtual GPS requires higher level applications to indicate the desired location accuracy, e.g. low, medium or high, and then chooses the mechanism that satisfies the desired location accuracy with minimum power consumption. A prototype of Virtual GPS has been implemented. The paper describes the design and implementation of this prototype, and provides an extensive evaluation that includes lab-controlled settings as well as real world settings.
Primary contributions of this work is in energy-efficient location estimation by considering application's accuracy requirements and dynamically switching sensors based on estimation algorithm in Virtual GPS layer. Another contribution of our V-GPS layer is to provide location to multiple applications simultaneously from stored location data instead of sampling sensors when the location errors accumulated satisfies application's accuracy requirements. We evaluate our approach using multiple experiments in moderate mobile and highly mobile environments. Results and evaluations show that Virtual-GPS layer can save over 28% compared to direct sensor usage with least overhead.

References

[1]
Martin Azizyan, Ionut Constandache, Romit Roy, Choudhury, Duke University, Duke University, and Duke University. Surroundsense: Mobile phone localization via ambience fingerprinting. 2009.
[2]
I. Constandache, S. Gaonkar, M. Sayler, R. R. Choudhury, and L. Cox. Enloc: Energy-efficient localization for mobile phones. In INFOCOM 2009, IEEE, pages 2716--2720, April 2009.
[3]
Tobias Farrell, Reynold Cheng, and Kurt Rothermel. Energy-efficient monitoring of mobile objects with uncertainty-aware tolerances. In Proceedings of the 11th International Database Engineering and Applications Symposium, IDEAS '07, pages 129--140, Washington, DC, USA, 2007. IEEE Computer Society.
[4]
Jon Froehlich, Mike Y. Chen, Ian E. Smith, and Fred Potter. Voting with your feet: An investigative study of the relationship between place visit behavior and preference. In Proceedings of the 8th International Conference on Ubiquitous Computing, UbiComp'06, pages 333--350, Berlin, Heidelberg, 2006. Springer-Verlag.
[5]
Ganesh, Maya Haridasan, Iqbal Mohomed, Ananthanarayanan Microsoft, Research Microsoft, and Research. Startrack: A framework for enabling track-based applications. 2009.
[6]
Shravan Gaonkar, Jack Li, Romit Roy Choudhury, Landon Cox, and Al Schmidt. Micro-blog: Sharing and querying content through mobile phones and social participation. In Proceedings of the 6th International Conference on Mobile Systems, Applications, and Services, MobiSys '08, pages 174--186, New York, NY, USA, 2008. ACM.
[7]
Christopher Jekeli. Inertial Navigation Systems with Geodetic Applications. Walter de Gruyter, 2001.
[8]
Donnie H. Kim, Younghun Kim, Deborah Estrin, Mani B. Srivastava, UCLA CSD CENS, and UCLA EED NESL. Sensloc: Sensing everyday places and paths using less energy. 2010.
[9]
Mikkel Baun Kjærgaard, Jakob Langdal, Torben Godsk, and Thomas Toftkjær. Entracked: Energy-efficient robust position tracking for mobile devices. In Proceedings of the 7th International Conference on Mobile Systems, Applications, and Services, MobiSys '09, pages 221--234, New York, NY, USA, 2009. ACM.
[10]
Axel Küpper and Georg Treu. Efficient proximity and separation detection among mobile targets for supporting location-based community services. SIGMOBILE Mob. Comput. Commun. Rev., 10(3):1--12, July 2006.
[11]
Anthony LaMarca, Yatin Chawathe, Sunny Consolvo, Jeffrey Hightower, Ian Smith, James Scott, Timothy Sohn, James Howard, Jeff Hughes, Fred Potter, Jason Tabert, Pauline Powledge, Gaetano Borriello, and Bill Schilit. Place lab: Device positioning using radio beacons in the wild. In Proceedings of the Third International Conference on Pervasive Computing, PERVASIVE'05, pages 116--133, Berlin, Heidelberg, 2005. Springer-Verlag.
[12]
Loukas Lazos, Radha Poovendran, Network Security Lab, and Dept. of EE. Serloc: Secure range-independent localization for wireless sensor networks. 2004.
[13]
Xinrong Li. Rss-based location and estimation with and unknown pathloss and model. In Digital Object Identifier 10.1109/TWC.2006.05084 transmitted from reference nodes to target node. IEEE, 2006.
[14]
Neal Patwari and Sneha K. Kasera. Temporal link signature measurements for location distinction. TRANSACTIONS ON MOBILE COMPUTING, VOL. 10, NO. 3,:449--462, 2011.
[15]
CELL PHONES, TECHNOLOGY EXPOSURES, and HEALTH EFFECTS. *The cellphone problem.
[16]
Grant Schindler, Matthew Brown, and Richard Szeliski. City-scale location recognition. 2006.
[17]
Guolin Sun, Jie Chen, and Wei Guo. Signal processing techniques in network-aided positioning: A survey of state-ofthe-art positioning designs. In IEEE Signal Processing Magazine, pages 12--23, 2005.
[18]
Arsalan Tavakoli, Aman Kansal, and Suman Nath. On-line sensing task optimization for shared sensors. In Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN '10, pages 47--57, New York, NY, USA, 2010. ACM.
[19]
Arvind Thiagarajan, Lenin Ravindranath, Katrina LaCurts, Samuel Madden, Hari Balakrishnan, Sivan Toledo, and Jakob Eriksson. Vtrack. Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems - SenSys ???09, 2009.
[20]
Moustafa Youssef and Ashok Agrawala. The horus wlan location determination system. In Proceedings of the 3rd International Conference on Mobile Systems, Applications, and Services, MobiSys '05, pages 205--218, New York, NY, USA, 2005. ACM.
[21]
Paul A Zandbergen. Accuracy of iphone locations: A comparison of assisted GPS, WiFi and cellular positioning. Transactions in GIS, 13:5--25, Jun 2009.
[22]
Radim Zemek, Daisuke Anzai, Shinsuke Hara, Kentaro Yanagihara, and Ken-ichi Kitayama. RSsi-based localization without a prior knowledge of channel model parameters. International Journal of Wireless Information Networks, 15(3-4):128--136, Dec 2008.

Cited By

View all
  • (2019)Modeling of energy consumption in GPS receivers for power aware localization systemsProceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems10.1145/3302509.3311043(217-226)Online publication date: 16-Apr-2019

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences
Industry papers: Proceedings of the Middleware Industry Track
December 2014
37 pages
ISBN:9781450332194
DOI:10.1145/2676727
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 December 2014

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. GPS abstraction
  2. location based services
  3. power efficient localization
  4. virtual GPS

Qualifiers

  • Research-article

Funding Sources

Conference

Middleware '14

Acceptance Rates

Industry papers Paper Acceptance Rate 5 of 23 submissions, 22%;
Overall Acceptance Rate 5 of 23 submissions, 22%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)2
  • Downloads (Last 6 weeks)0
Reflects downloads up to 08 Mar 2025

Other Metrics

Citations

Cited By

View all
  • (2019)Modeling of energy consumption in GPS receivers for power aware localization systemsProceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems10.1145/3302509.3311043(217-226)Online publication date: 16-Apr-2019

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media