Skip to main content
SpringerLink
Log in

Participant selection for data collection through device-to-device communications in mobile sensing

  • Original Article
  • Published:
Personal and Ubiquitous Computing Aims and scope Submit manuscript

Abstract

The appearance of smart mobile devices with communication, computation and sensing capability and increasing popularity of various mobile applications have caused the explosion of mobile data recently. In the same time, mobile sensing has been emerging as a new sensing paradigm where vast numbers of mobile devices are used for sensing and collecting huge amounts of mobile data in cities. One of the challenges faced by mobile sensing is how to efficiently collect the huge amount of mobile data beyond the existing capacity of 4G networks. In this paper, we investigate the feasibility of collecting data packets from mobile devices through device-to-device communications by carefully selecting the subset of relaying (or/and sensing) devices. We formulate these problems as optimization problems and propose a set of solutions to solve them. Our experiments over a real-life mobile trace confirm the effectiveness of the proposed idea.

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
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  1. Cisco visual networking index: global mobile data traffic forecast update, 2015–2020 (February 3, 2016). http://www.cisco.com/c/en/us/solutions/collateral/service-provider/visual-networking-index-vni/mobile-white-paper-c11-520862.html

  2. Guo B, Wang Z, Yu Z, Wang Y, Yen N, Huang R, Zhou X (2015) Mobile crowd sensing and computing: the review of an emerging human-powered sensing paradigm. ACM Comput Surv 48(1):7

    Article  Google Scholar 

  3. Bengtsson L, Xin Lu, Thorson A, Garfield R, Schreeb JV (2011) Improved response to disasters and outbreaks by tracking population movements with mobile phone network data: A post-earthquake geospatial study in Haiti. PLoS Med 8(8):e1001083

    Article  Google Scholar 

  4. Bo C, Jian X, Jung TJ, Han X-Y, Li Mao X, Wang Y (2016) Detecting driver’s smartphone usage via non-intrusively sensing driving dynamics. IEEE Internet Things J (99):1. doi:10.1109/JIOT.2016.2552399

  5. Zhou P, Zheng Y, Li M (2012) How long to wait? Predicting bus arrival time with mobile phone based participatory sensing. In: Proceedings of ACM MobiSys

  6. Nawaz S, Efstratiou C, Mascolo C (2013) Parksense: a smartphone based sensing system for on-street parking. In: Proceedings of ACM Mobicom

  7. Gao R, Zhao M, Ye T, Ye F, Wang Y, Bian K, Wang T, Li X (2014) Jigsaw: indoor floor plan reconstruction via mobile crowdsensing. In: Proceedings of ACM MobiCom

  8. Bo C, Jung T, Mao X, Li X-Y, Wang Y (2016) SmartLoc: sensing landmarks silently for smartphone based metropolitan localization. EURASIP J Wirel Commun Netw 2016:e111

    Article  Google Scholar 

  9. Rana RK, Chou CT, Kanhere SS, Bulusu N, Hu W (2010) Ear-phone: an end-to-end participatory urban noise mapping system. In: Proceedings of ACM/IEEE IPSN

  10. Mun M, Reddy S, Shilton K, Yau N, Burke J, Estrin D, Hansen M, Howard E, West R, Boda P (2009) PEIR, the personal environmental impact report, as a platform for participatory sensing systems research. In: Proceedings of ACM MobiSys

  11. Lathia N, Pejovic V, Rachuri KK, Mascolo C, Musolesi M, Rentfrow PJ (2013) Smartphones for large-scale behavior change interventions. IEEE Pervasive Comput 12(3):66–73

    Article  Google Scholar 

  12. Noulas A, Scellato S, Lambiotte R, Pontil M, Mascolo C (2012) A tale of many cities: universal patterns in human urban mobility. PLoS ONE 7(5):e37027

    Article  Google Scholar 

  13. Balasubramanian A, Mahajan R, Venkataramani A (2010) Augmenting mobile 3G using WiFi. In: ACM MobiSys 2010

  14. Dimatteo S, Hui P, Han B, Li VOK (2011) Cellular traffic offloading through WiFi networks. In: Proceedings of IEEE MASS

  15. Chandrasekhar V, Andrews JG, Gatherer A (2008) Femtocell networks: a survey. IEEE Commun Mag 46(9):59–67

    Article  Google Scholar 

  16. Han B, Hui P, Kumar VSA, Marathe MV, Shao J, Srinivasan A (2012) Mobile data offloading through opportunistic communications and social participation. IEEE Trans Mobile Comput 11(5):821–834

    Article  Google Scholar 

  17. Li Y, Qian M, Jin D, Hui P, Wang Z, Chen S (2014) Multiple mobile data offloading through disruption tolerant networks. IEEE Trans Mobile Comput 13(7):1579–1596

    Article  Google Scholar 

  18. Zhu Y, Zhang C, Wang Y (2013) Mobile data delivery through opportunistic communications among cellular users: a case study for the D4D challenge. In: Proceedings of NetMob

  19. Xiong H, Zhang D, Wang L, Chaouchi H (2015) EMC\(^3\): energy-efficient data transfer in mobile crowdsensing under full coverage constraint. IEEE Trans Mobile Comput 14(7):1355–1368

    Article  Google Scholar 

  20. Xiong H, Zhang D, Chen G, Wang L, Gauthier V (2015) Crowdtasker: maximizing coverage quality in piggyback crowdsensing under budget constraint. In: Proceedings of IEEE Percom

  21. Zhang D, Xiong H, Wang L, Chen G (2014) Crowdrecruiter: selecting participants for piggyback crowdsensing under probabilistic coverage constraint. In: Proceedings of ACM UbiComp

  22. Li H, Li T, Wang Y (2015) Dynamic participant recruitment of mobile crowd sensing for heterogeneous sensing tasks. In: Proceedings of IEEE MASS

  23. Li H, Li T, Li F, Wang W, Wang Y (2016) Enhancing participant selection through caching in mobile crowd sensing. In: Proceedings of ACM/IEEE IWQoS

  24. Wang L, Zhang D, Xiong H (2013) Effsense: energy-efficient and cost-effective data uploading in mobile crowdsensing . In: Proceedings of ACM UbiComp

  25. Karaliopoulos M, Telelis O, Koutsopoulos I (2015) User recruitment for mobile crowdsensing over opportunistic networks. In: Proceedings of IEEE INFOCOM

  26. Li H, Li T, Shi X, Wang Y (2016) Data collection through device-to-device communications for mobile big data sensing. In: Proceedings of 1st workshop of mission-critical big data analytics (MCBDA 2016)

  27. Vahdat A, Becker D (2000) Epidemic routing for partially connected ad hoc networks. Technical Report CS-200006, Duke University, Technical Report

  28. Merugu S, Ammar M, Zegura E (2004) Routing in space and time in networks with predictable mobility. Technical Report GIT-CC-04-07

  29. Huang M, Chen S, Zhu Y, Wang Y (2013) Topology control for time-evolving and predictable delay-tolerant networks. IEEE Trans Comput 62(11):2308–2321

    Article  MathSciNet  Google Scholar 

  30. Li F, Chen S, Huang M, Yin Z, Zhang C, Wang Y (2015) Reliable topology design in time-evolving delay-tolerant networks with unreliable links. IEEE Trans Mobile Comput 14(6):1301–1314

    Article  Google Scholar 

  31. Agrawal A, Barlow RE (1984) A survey of network reliability and domination theory. Oper Res 32:478–492

    Article  MathSciNet  MATH  Google Scholar 

  32. Blondel VD, Esch M, Chan C, Clerot F, Deville P, Huens E, Morlot F, Smoreda Z, Ziemlicki C (2013) Data for development: the D4D challenge on mobile phone data. arXiv.1210.0137v2

  33. Pournajaf L, Xiong L, Sunderam VS (2014) Dynamic data driven crowd sensing task assignment. In: Proceedings of ICCS

  34. Zhao D, Ma H, Liu L (2014) Energy-efficient opportunistic coverage for people-centric urban sensing. Wirel Netw 20(6):461–1476

    Google Scholar 

  35. Li F, Tian C, Li T, Wang Y (2016) Energy efficient social routing framework for mobile social sensing networks. Tsinghua Sci Technol 21(4):363–373

    Article  Google Scholar 

  36. Jin H, Su L, Ding B, Nahrstedt K, Borisov N (2016) Enabling privacy-preserving incentives for mobile crowd sensing systems. In: Proceedings of IEEE ICDCS

  37. Yang D, Xue G, Fang X, Tang J (2012) Crowdsourcing to smartphones: incentive mechanism design for mobile phone sensing. In: Proceedings of ACM Mobicom

  38. Liu Y, Li F, Wang Y (2016) Incentives for delay-constrained data query and feedback in mobile opportunistic crowdsensing. Sensors 16(7):1138. doi:10.3390/s16071138

    Article  Google Scholar 

  39. Feng Z, Zhu Y, Zhang Q, Ni LM (2014) Vasilakos AV TRAC: truthful auction for location-aware collaborative sensing in mobile crowdsourcing In: Proceedings of INFOCOM

  40. Zhu Y, Xu B, Shi X, Wang Y (2013) A survey of social-based routing in delay tolerant networks: positive and negative social effects. IEEE Commun Surv Tutor 15(1):387–401

    Article  Google Scholar 

  41. Zhu Y, Zhang C, Li F, Wang Y (2015) Geo-social: routing with location and social metrics in mobile opportunistic networks. In: IEEE ICC

  42. Liu Y, Bashar AMAE, Li F, Wang Y, Liu K (2016) Multi-copy data dissemination with probabilistic delay constraint in mobile opportunistic device-to-device networks. In: Proceedings of 17th IEEE international symposium on a world of wireless, mobile and multimedia networks (WOWMOM 2016)

  43. Li Y, Wu H, Xia Y, Wang Y, Li F, Yang P (2016) Optimal online data dissemination for resource constrained mobile opportunistic networks. IEEE Trans Veh Tech (99):1. doi:10.1109/TVT.2016.2616034

Download references

Acknowledgements

The work is partially supported by the US National Science Foundation under Grant Nos. CNS-1319915 and CNS-1343355, and the National Natural Science Foundation of China under Grant Nos. 61428203 and 61572347. The authors would like to thank Orange and the D4D challenge organizers for providing them the D4D datasets and allowing them to continue working on the datasets after the D4D challenge.

Author information

Authors and Affiliations

  1. College of Information Engineering, Taiyuan University of Technology, Taiyuan, 030024, China

    Yu Wang

  2. Department of Computer Science, University of North Carolina at Charlotte, Charlotte, NC, 28223, USA

    Yu Wang, Hanshang Li & Ting Li

Authors
  1. Yu Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hanshang Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ting Li
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yu Wang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, Y., Li, H. & Li, T. Participant selection for data collection through device-to-device communications in mobile sensing. Pers Ubiquit Comput 21, 31–41 (2017). https://doi.org/10.1007/s00779-016-0974-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00779-016-0974-0

Keywords

Search

Navigation