Skip to main content
SpringerLink
Log in

Online task dispatching and pricing for quality-of-service-aware sensing data collection for mobile edge clouds

  • Regular Paper
  • Published:
CCF Transactions on Networking

Abstract

The proliferation of mobile devices equipped with rich sensing and computing resources has pushed the emergence of a new cloud paradigm, mobile edge clouds, where tasks are dispatched from the centralized cloud to the network edge. By taking the advantage of widely-distributed mobile devices, urban monitoring-oriented crowdsourcing services can be provided by a mobile edge cloud, where fine-grained monitoring data over time are crowdsourced by mobile devices and then useful information is extracted. However, as considerable costs are incurred on mobile devices, there exists a major problem that a high financial budget is required to guarantee the quality of service. Fortunately, we observe that real-world sensing data exhibit strong spatial and temporal correlations, and advanced inference methods can be employed to efficiently recover missing data. Motivated by the observation, we provide a near-optimal online task dispatching approach for crowdsourcing services provided by a mobile edge cloud, aiming to minimize the total cost incurred on devices while guarantee the quality of service in the meantime. Besides, considering strategic device users with private cost information, we also propose a truthful pricing policy. Extensive simulations based on real datasets show that our approach outperforms other competing schemes, producing a high quality of service with a much lower budget.

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
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17

Similar content being viewed by others

Notes

  1. Note that there should always exist \(\delta _1>\max \{\delta _2,\delta _3\}\), otherwise (4) can be satisfied directly when (5) or (6) is satisfied.

  2. Because VCG only works when the optimal selection is achieved. Obviously, random selection cannot achieve the minimum total cost.

  3. Note that these two baseline algorithms cannot guarantee the spatial coverage constraint and the temporal coverage constraint are satisfied.

References

  • 311 data. [Online]. http://nycopendata.socrata.com/Social-Services/311-Service-Requests-from-2010-to-Present/erm2-nwe9

  • Bonomi, F., Milito, R., Zhu, J., Addepalli, S.: Fog computing and its role in the internet of things, Edition of the Mcc Workshop on Mobile Cloud Computing, pp. 13–16 (2012)

  • Buyya, R., Yeo, C.S., Venugopal, S., Broberg, J., Brandic, I.: Cloud computing and emerging IT platforms: vision, hype, and reality for delivering computing as the 5th utility. Future Gen. Comput. Syst. 25(6), 599–616 (2009)

    Article  Google Scholar 

  • Cuervo, E., et al., MAUI:making smartphones last longer with code offload. In: International Conference on Mobile Systems, Applications, and Services, pp. 49–62 (2010)

  • Dhillon I. S., Sra, S.: Generalized nonnegative matrix approximations with bregman divergences, Neural Information Proc Systems, pp. 283–290 (2006)

  • Fernand, N., Loke, S.W., Rahayu, W.: Mobile cloud computing: a survey. Future Gen. Comput. Syst. 29(1), 84–106 (2013)

    Article  Google Scholar 

  • Greenberg, A., Hamilton, J., Maltz, D.A., Patel, P.: The cost of a cloud:research problems in data center networks. Acm Sigcomm Comput. Commun. Rev. 39(1), 68–73 (2008)

    Article  Google Scholar 

  • Liu, J., Mao, Y., Zhang, J., Letaief, K.B.: Delay-optimal computation task scheduling for mobile-edge computing systems. In: IEEE International Symposium on Information Theory, pp. 1451–1455 (2016)

  • Luan, T.H., Gao, L., Li, Z., Xiang, Y., Wei, G., Sun, L.: Fog computing: focusing on mobile users at the edge. Comput. Sci. (2016)

  • Mao, Y., Zhang, J., Letaief, K.B.: Dynamic computation offloading for mobile-edge computing with energy harvesting devices. IEEE J. Select. Areas Commun. 34(12), 3590–3605 (2016)

    Article  Google Scholar 

  • Mean absolute percentage error. [Online]. https://en.wikipedia.org/wiki/Mean_absolute_percentage_error

  • Mendez, D., Perez, A. J., Labrador, M. A., Marron, J. J.: P-sense: A participatory sensing system for air pollution monitoring and control. In: Proceedings of IEEE Percom Workshops’11, pp. 344–347 (2011)

  • Neely, M.J.: Stochastic network optimization with application to communication and queueing systems. Synth. Lect. Commun. Netw. 3(1), 1–211 (2010)

    Article  MATH  Google Scholar 

  • Nisan, N., Roughgarden, T., Tardos, E., Vazirani, V.V.: Algorithmic Game Theory, vol. 1. Cambridge University Press, Cambridge (2007)

    Book  MATH  Google Scholar 

  • Rana, R.K., Chou, C.T., Kanhere, S.S., Bulusu, N., Hu, W.: Ear-phone: an end-to-end participatory urban noise mapping system. In: Proceedings of IEEE IPSN’10, pp. 105–116 (2010)

  • Satyanarayanan, M., Bahl, P., Davies, N.: The case for VM-based cloudlets in mobile computing. IEEE Pervasive Comput. 8(4), 14–23 (2009)

    Article  Google Scholar 

  • Shi, W., Cao, J., Zhang, Q., Zhang, Q., Li, Y., Xu, L.: Edge computing: vision and challenges. IEEE Internet Things J. 3(5), 637–646 (2016)

    Article  Google Scholar 

  • Sun, Y., Zhou, S., Xu, J.: EMM: Energy-aware mobility management for mobile edge computing in ultra dense networks. IEEE J. Select. Areas Commun. PP(99), 1–1 (2017)

  • Tan, H., Han, Z., Li, X., Lau, F.C.M.: Online job dispatching and scheduling in edge-clouds. In: IEEE Conference on Computer Communications (INFOCOM), pp. 1–9, (2017)

  • Wang, L., Zhang, D., Pathak, A., Chen, C., Xiong, H., Yang, D., Wang, Y.: Ccs-ta: Quality-guaranteed online task allocation in compressive crowdsensing. In: Proceedings of ACM Ubicomp’15, pp. 683–694 (2015)

  • Waze app. https://www.waze.com/

  • World-wide smartphone users. https://www.statista.com/statistics/330695/number-of-smartphone-users-worldwide/

  • Xu, J., Chen, L., Ren, S.: Online learning for offloading and autoscaling in energy harvesting mobile edge computing. IEEE Trans. Cognit. Commun. Netw. PP(99) (2017)

  • Xu, L., Hao, X., Lane, N. D., Liu, X., Moscibroda, T.: Cost-aware compressive sensing for networked sensing systems. In: Proceedings of IEEE IPSN’15, pp. 130–141 (2015a)

  • Xu, L., Hao, X., Lane, N. D., Liu, X., Moscibroda, T.: More with less: lowering user burden in mobile crowdsourcing through compressive sensing. In: Proceedings of ACM Ubicomp’15, pp. 659–670 (2015b)

  • Zheng ,Y., Liu, F., Hsieh, H.-P.: U-air: when urban air quality inference meets big data. In: Proceedings of ACM KDD’13, pp. 1436–1444 (2013)

Download references

Acknowledgements

This research is supported in part by 973 Program (No. 2014CB340303), Shanghai Sailing Program 18YF1408200, and NSFC (Nos. 61772341, 61472254, 61572324, 61170238, and 61802245). This work is also supported by the Program for the Program for Changjiang Young Scholars in University of China, the Program for China Top Young Talents, and the Program for Shanghai Top Young Talents.

Author information

Authors and Affiliations

  1. School of Computer Engineering and Science, Shanghai University, 99 Shangda Road, Shanghai, 200444, China

    Tong Liu

  2. Department of Computer Science and Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China

    Yanmin Zhu & Jiadi Yu

  3. Department of Electrical and Computer Engineering, Stony Brook University, Stony Brook, NY, 11794, USA

    Yuanyuan Yang & Fan Ye

Authors
  1. Tong Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yanmin Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yuanyuan Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Fan Ye
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jiadi Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yanmin Zhu.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liu, T., Zhu, Y., Yang, Y. et al. Online task dispatching and pricing for quality-of-service-aware sensing data collection for mobile edge clouds. CCF Trans. Netw. 2, 28–42 (2019). https://doi.org/10.1007/s42045-018-0008-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s42045-018-0008-8

Keywords

Search

Navigation