Skip to main content

Advertisement

SpringerLink
Log in

Energy efficiency on location based applications in mobile cloud computing: a survey

  • Published:
Computing Aims and scope Submit manuscript

Abstract

The constrained battery power of mobile devices poses a serious impact on user experience. As an increasingly prevalent type of applications in mobile cloud environments, location-based applications (LBAs) present some inherent limitations concerning energy. For example, the Global Positioning System based positioning mechanism is well-known for its extremely power-hungry attribute. Due to the severity of the issue, considerable researches have focused on energy-efficient locating sensing mechanism in the last a few years. In this paper, we provide a comprehensive survey of recent work on low-power design of LBAs. An overview of LBAs and different locating sensing technologies used today are introduced. Methods for energy saving with existing locating technologies are investigated. Reductions of location updating queries and simplifications of trajectory data are also mentioned. Moreover, we discuss cloud-based schemes in detail which try to develop new energy-efficient locating technologies by leveraging the cloud capabilities of storage, computation and sharing. Finally, we conclude the survey and discuss the future research directions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Google maps api. http://code.google.com/apis/maps/. Accessed Nov 2011

  2. Skyhook wireless. http://www.skyhookwireless.com/. Accessed Oct 2012

  3. Armbrust M, Fox A, Griffith R, Joseph A, Katz R, Konwinski A, Lee G, Patterson D, Rabkin A, Stoica I et al (2010) A view of cloud computing. Commun ACM 53(4):50–58

    Article  Google Scholar 

  4. Azizyan M, Constandache I, Roy Choudhury R (2009) Surroundsense: mobile phone localization via ambience fingerprinting. In: Proceedings of the 15th annual international conference on mobile computing and networking. ACM, New York, pp 261–272

  5. Bahl P, Padmanabhan V (2000) Radar: an in-building rf-based user location and tracking system. In: INFOCOM 2000. Proceedings of nineteenth annual joint conference of the IEEE computer and communications societies, vol. 2. IEEE, New York, pp 775–784

  6. Ben Abdesslem F, Phillips A, Henderson T (2009) Less is more: energy-efficient mobile sensing with senseless. In: Proceedings of the 1st ACM workshop on networking, systems, and applications for mobile handhelds. ACM, New York, pp 61–62

  7. Chang Y, Lin C, Chen L (2012) A two-layer approach for energy efficiency in mobile location sensing applications. NETWORKING 2012, pp 304–315

  8. Cheng Y, Chawathe Y, LaMarca A, Krumm J (2005) Accuracy characterization for metropolitan-scale wi-fi localization. In: Proceedings of the 3rd international conference on mobile systems, applications, and services. ACM, New York, pp 233–245

  9. Constandache I, Choudhury R, Rhee I (2010) Towards mobile phone localization without war-driving. In: INFOCOM, 2010 Proceedings. IEEE, New York, pp 1–9

  10. Constandache I, Gaonkar S, Sayler M, Choudhury R, Cox L (2009) Enloc: energy-efficient localization for mobile phones. In: INFOCOM 2009. IEEE, New York, pp 2716–2720

  11. Cui Y, Ma X, Wang H, Stojmenovic I, Liu J (2013) A survey of energy efficient wireless transmission and modeling in mobile cloud computing. Mobile Netw Appl 18(1):148–155

    Google Scholar 

  12. Cui Y, Wang H, Cheng X, Li D, Ylä-Jääski A (2013) Dynamic scheduling for wireless data center networks. IEEE Trans Parallel Distrib Syst. doi:10.1109/TPDS.2013.52012.12

  13. Dhondge K, Park H, Choi B, Song S (2012) Energy-efficient cooperative opportunistic positioning for heterogeneous mobile devices. In: 2012 21st international conference on computer communications and networks (ICCCN). IEEE, New York, pp 1–6

  14. Djuknic G, Richton R (2001) Geolocation and assisted GPS. Computer 34(2):123–125

    Article  Google Scholar 

  15. Farrell T, Cheng R, Rothermel K (2007) Energy-efficient monitoring of mobile objects with uncertainty-aware tolerances. In: 11th international database engineering and applications symposium, 2007. IDEAS 2007. IEEE, New York, pp 129–140

  16. Froehlich J, Chen M, Consolvo S, Harrison B, Landay J (2007) Myexperience: a system for in situ tracing and capturing of user feedback on mobile phones. In: Proceedings of the 5th international conference on mobile systems, applications and services. ACM, New York, pp 57–70

  17. Kaplan E, Hegarty C (2006) Understanding GPS: principles and applications. Artech House Publishers, London

    Google Scholar 

  18. Kim D, Kim Y, Estrin D, Srivastava M (2010) Sensloc: sensing everyday places and paths using less energy. In: Proceedings of the 8th ACM conference on embedded networked sensor systems. ACM, New York, pp 43–56

  19. Kjærgaard M, Bhattacharya S, Blunck H, Nurmi P (2011) Energy-efficient trajectory tracking for mobile devices. In: Proceedings of the 9th international conference on mobile systems, applications, and services. ACM, New York, pp 307–320

  20. Kjærgaard M, Langdal J, Godsk T, Toftkjær T (2009) Entracked: energy-efficient robust position tracking for mobile devices. In: Proceedings of the 7th international conference on mobile systems, applications, and services. ACM, New York, pp 221–234

  21. Krumm J, Letchner J, Horvitz E (2007) Map matching with travel time constraints. In: SAE World Congress

  22. LaMarca A, Chawathe Y, Consolvo S, Hightower J, Smith I, Scott J, Sohn T, Howard J, Hughes J, Potter F et al (2005) Place lab: device positioning using radio beacons in the wild. Pervasive Comput, 301–306

  23. Lane N, Miluzzo E, Lu H, Peebles D, Choudhury T, Campbell A (2010) A survey of mobile phone sensing. In: Communications magazine, vol 48, no 9. IEEE, New York, pp 140–150

  24. Leonhardi A, Rothermel K (2001) A comparison of protocols for updating location information. Cluster Comput 4(4):355–367

    Article  Google Scholar 

  25. Lin K, Kansal A, Lymberopoulos D, Zhao F (2010) Energy-accuracy trade-off for continuous mobile device location. In: Proceedings of the 8th international conference on mobile systems, applications, and services. ACM, New York, pp 285–298

  26. Liu J, Priyantha B, Hart T, Ramos H, Loureiro A, Wang Q (2012) Energy efficient GPS sensing with cloud offloading. In: Proceedings of the 10th ACM conference on embedded networked sensor systems. ACM, New York

  27. Lou Y, Zhang C, Zheng Y, Xie X, Wang W, Huang Y (2009) Map-matching for low-sampling-rate gps trajectories. In: Proceedings of the 17th ACM SIGSPATIAL international conference on advances in geographic information systems. ACM, New York, pp 352–361

  28. Ma X, Cui Y, Stojmenovic I (2012) Energy efficiency on location based applications in mobile cloud computing: a survey. Procedia Comput Sci 10:577–584

    Article  Google Scholar 

  29. Ma X, Cui Y, Wang L, Stojmenovic I (2012) Energy optimizations for mobile terminals via computation offloading. In: 2012 2nd IEEE international conference on parallel distributed and grid computing (PDGC). IEEE, New York, pp 236–241

  30. Marinelli E (2009) Hyrax: cloud computing on mobile devices using mapreduce. Tech. rep, DTIC Document

  31. Murray D, Yoneki E, Crowcroft J, Hand, S (2010) The case for crowd computing. In: Proceedings of the second ACM SIGCOMM workshop on networking, systems, and applications on mobile handhelds. ACM, New York, pp 39–44

  32. Nelson G, Lombardi M, Okayama D (2005) Nist time and frequency radio stations: Wwv, wwvh, and wwvb. NIST Spec Publ 250(67):161

    Google Scholar 

  33. Paek J, Kim J, Govindan R (2010) Energy-efficient rate-adaptive gps-based positioning for smartphones. In: Proceedings of the 8th international conference on mobile systems, applications, and services. ACM, New York, pp 299–314

  34. Paek J, Kim K, Singh J, Govindan R (2011) Energy-efficient positioning for smartphones using cell-id sequence matching. In: Proceedings of the 9th international conference on mobile systems, applications, and services. ACM, New York, pp 293–306

  35. Ramos H, Zhang T, Liu J, Priyantha N, Kansal A (2011) Leap: a low energy assisted GPS for trajectory-based services. ACM Ubicomp 2011, pp 335–344

  36. Robinson S (2009) Cellphone energy gap: desperately seeking solutions. Strategy analytics tech, rep

  37. Ryder J, Longstaff B, Reddy S, Estrin D (2009) Ambulation: a tool for monitoring mobility patterns over time using mobile phones. In: International conference on computational science and engineering, 2009. CSE’09, vol 4. IEEE, New York, pp 927–931

  38. Thiagarajan A, Ravindranath L, Balakrishnan H, Madden S, Girod L, et al. (2011) Accurate, low-energy trajectory mapping for mobile devices. In: Proceedings of 8th USENIX symosium on networked systems design and implementation (NSDI 2011). ACM Press, New York

  39. Thiagarajan A, Ravindranath L, LaCurts K, Madden S, Balakrishnan H, Toledo S, Eriksson J (2009) Vtrack: accurate, energy-aware road traffic delay estimation using mobile phones. In: Proceedings of the 7th ACM conference on embedded networked sensor systems. ACM, New York, pp 85–98

  40. Van Diggelen F (2009) A-GPS: assisted GPS, GNSS, and SBAS. Artech House Publishers, London

    Google Scholar 

  41. Wang Y, Lin J, Annavaram M, Jacobson Q, Hong J, Krishnamachari B, Sadeh N (2009) A framework of energy efficient mobile sensing for automatic user state recognition. In: Proceedings of the 7th international conference on mobile systems, applications, and services. ACM, New York, pp 179–192

  42. Xiao Y, Cui Y, Savolainen P, Siekkinen M, Wang A, Yang L, Ylä-Jääski A, Tarkoma S (2013) Modeling energy consumption of data transmission over wi-fi. IEEE Trans Mobile Comput. doi:10.1109/TMC.2013.51

  43. You C, Huang P, Chu H, Chen Y, Chiang J, Lau S (2008) Impact of sensor-enhanced mobility prediction on the design of energy-efficient localization. Ad Hoc Netw 6(8):1221–1237

    Article  Google Scholar 

  44. Zhuang Z, Kim K, Singh J (2010) Improving energy efficiency of location sensing on smartphones. In: Proceedings of the 8th international conference on mobile systems, applications, and services. ACM, New York, pp 315–330

Download references

Acknowledgments

This work is supported by NSFC (no. 61120106008, 60911130511), National Major Basic Research Program of China (no. 2009CB320501, 2009CB320503). The work of Ivan Stojmenovic was also supported by the Government of China for the Tsinghua 1000 Plan Distinguished Professor (2012–2015) position and by NSERC Discovery grant.

Author information

Authors and Affiliations

  1. Department of Computer Science, Tsinghua University, Beijing, People’s Republic of China

    Lian Wang, Yong Cui, Xiao Ma & Jian Song

  2. School of Information Technology and Engineering, University of Ottawa, Ottawa, Canada

    Ivan Stojmenovic

  3. School of Software, Tsinghua University, Beijing, People’s Republic of China

    Ivan Stojmenovic

Authors
  1. Lian Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yong Cui
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ivan Stojmenovic
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xiao Ma
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jian Song
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yong Cui.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Wang, L., Cui, Y., Stojmenovic, I. et al. Energy efficiency on location based applications in mobile cloud computing: a survey. Computing 96, 569–585 (2014). https://doi.org/10.1007/s00607-013-0334-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00607-013-0334-0

Keywords

Mathematics Subject Classification

Search

Navigation