Skip to main content
SpringerLink
Log in

EMUNE: Architecture for Mobile Data Transfer Scheduling with Network Availability Predictions

  • Published:
Mobile Networks and Applications Aims and scope Submit manuscript

Abstract

With the mobile communication market increasingly moving towards value-added services, the network cost will need to be included in the service offering itself. This will lead service providers to optimize network usage based on real cost rather than simplified network plans sold to consumers traditionally. Meanwhile, today’s mobile devices are increasingly containing multiple radios, enabling users on the move to take advantage of the heterogeneous wireless network environment. In addition, we observe that many bandwidth intensive services such as video on demand and software updates are essentially non real-time and buffers in mobile devices are effectively unlimited. We therefore propose EMUNE, a new transfer service which leverages these aspects. It supports opportunistic bulk transfers in high bandwidth networks while adapting to device power concerns, application requirements and user preferences of cost and quality. Our proposed architecture consists of an API, a transport service and two main functional units. The well defined API hides all internal complexities from a programmer and provides easy access to the functionalities. The prediction engine infers future network and bandwidth availability. The scheduling engine takes the output of the prediction engine as well as the power and monetary costs, application requirements and user preferences into account and determines which interface to use, when and for how long for all outstanding data transfer requests. The transport service accordingly executes the inferred data transfer schedule. The results from the implementation of EMUNE’s and of the prediction and scheduling engines evaluated against real user data show the effectiveness of the proposed architecture for better utilization of multiple network interfaces in mobile devices.

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
Fig. 18
Fig. 19
Fig. 20

Similar content being viewed by others

Notes

  1. This applies for small downloads, which can be finished during the prediction window. For larger downloads, a minimum download rate is necessary to adhere to the transfer deadlines (Section 7.2.2).

  2. We include the Auto-Regressive HMM to show the explosion of the parameter space with this model.

References

  1. Analysis of Multihoming in Mobile IPv6 (2011) http://www.nautilus6.org/ietf/monami6/ietf63/monami6-ietf63-bof.html. Accessed 23 June 2011

  2. Bahl P, Adya A, Padhye J, Wolman A (2004) Reconsidering wireless systems with multiple radios. In: ACM SigComm CCR, vol 34

  3. Baig A, Libman L, Hassan M (2006) Performance enhancement of on-board communication networks using outage prediction. IEEE J Sel Areas Commun 24(9):1692–1701

    Article  Google Scholar 

  4. Bayati M, Squillante M, Sharma M (2006) Optimal scheduling in multi-server queuing network. ACM SIGMETRICS/Performance

  5. Bonnin J, Hamouda ZB, Lassoued I, Belghith A (2008) Middleware for multi-interfaces management through profiles handling. In: Proc. of Mobileware 2008, Innsbruck, Austria

  6. Doss CR, Jennings A, Shenoy N (2004) A review of current work on mobility prediction in wireless networks. ACM AMOC, Thailand

    Google Scholar 

  7. Erbas F, Steuer J, Eggeiseker D, Kyamakya K, Jobmann K (2001) A regular path recognition method and prediction of user movements in wireless networks. In: Proceedings of vehicular technology conference, VTC

  8. Exposito E, Malaney R, Wei X, Nghia D (2005) Using the XQoS Platform for designing and developing the QoS-Seeker system. In: The proceeding of the 3rd International IEEE Conference on Industrial Informatics (INDIN), Perth, Australia

  9. Goff T, Moronski J, Phatak DS, Gupta V (2000) Freeze-tcp: a true end-to-end tcp enhancement mechanism for mobile environments. In: IEEE INFOCOM

  10. Herborn S, Petander H, Ott M (2008) Predictive context aware mobility handling. In: International conference on telecommunications

  11. Henderson T, Crowcroft J, Bhatti S (2001) Congestion Pricing: Paying Your Way in Communication Networks, In IEEE Internet Computing Journal, vol 5, pp 85–89

  12. Higle JL (2005) Stochastic programming: optimization when uncertainty matters. Tutorials in Operational Research—INFORMS

  13. Hsieh HY, Kim KH, Zhu Y, Sivakumar R (2003) A receiver-centric transport protocol for mobile hosts with heterogeneous wireless interfaces. In: Proc. of ACM MOBICOM’03

  14. Jay Sethuraman and Mark Squillante, “Optimal stochastic scheduling in multiclass parallel queues”, SIGMETRICS 1999

  15. Jordan M, Bishop C (2002) An introduction to graphical models. MIT Press, in press

  16. Kim M, Kotz D, Kim S (2006) Extracting a mobility model from real user traces. In: Proceedings of the 25th annual conference of INFOCOM, Barcelona, Spain

  17. Koutsordoi AA, Adamopoulou EF, Demestichas KP, Theologou ME (2006) Terminal management and intelligent access selection in heterogeneous environments. MONET 11(6):861–871

    Google Scholar 

  18. Chou L-D, Chen J-M, Chen J-W, Yang J-S (2008) Method and system for selecting an access network in a heterogeneous network environment. US Patent 7315750. http://www.patentstorm.us/patents/7315750/fulltext.html. Accessed 23 June 2011

  19. Ormond O, Murphy J, Muntean G (2006) Utility-based intelligent network selection in beyond 3G systems. In: Proc. of IEEE ICC

  20. Pering T, Agarwal Y, Gupta R, Want R (2006) CoolSpots: reducing the power consumption of wireless mobile devices with multiple radio interfaces. In: Proc. of MobiSys, Sweden

  21. Rahmati A, Zhong L (2007) Context-for-wireless: context-sensitive energy-efficient wireless data transfer. In: Proc. ACM/USENIX MobiSys

  22. Rathnayake U, Ott M (2008) Predicting network availability using user context. In: Proceedings of ACM MobiQuitous ’08, Dublin, Ireland

  23. Rathnayake U, Ott M, Seneviratne A (2009) A DBN approach for network availability prediction. In: Proceedings of MSWiM’09, Canary Islands, Spain

  24. Rathnayake U, Iftikhar M, Ott M, Seneviratne A (2009) Realistic data transfer scheduling with uncertainty. NICTA Technical Report

  25. Samaan N, Karmouch A (2005) A mobility prediction architecture based on contextual knowledge and spatial conceptual maps. IEEE Trans Mob Comput 4(6):537–551

    Article  Google Scholar 

  26. Schorr A, Kassler A, Petrovic G (2004) Adaptive media streaming in heterogeneous wireless networks. In: Proc. of IEEE workshop on multimedia signal processing

  27. Shapiro A, Philpott A (2011) A tutorial on stochastic programming. http://stoprog.org/. Accessed 23 June 2011

  28. Shih E, Bahl P, Sinclair M (2006) Wake on wireless: an event driven energy saving strategy for battery operated devices. In: Proc. of ACM MobiCom

  29. Song L, Kotz D, Jain R, He X (2004) Evaluating location predictors with extensive Wi-Fi mobility data. In: Proceedings of the 23rd annual conference INFOCOM, pp 1414–1424

  30. Sowmia Devia MK, Agarwal P (2007) Dynamic interface selection in portable multi-interface terminals. In: Proc. of IEEE Portable, Orlando, FL, 25–29 March 2007

  31. Stenm M, Katz RH (1998) Vertical handoffs in wireless overlay networks. ACM Mob Netw Appl 3(4):335–350

    Article  Google Scholar 

  32. Sun J, Riekki J, Sauvola J, Jurmu M (2004) Towards connectivity management adaptability: context awareness in policy representation and end-to-end evaluation algorithm. In: Proc. of 3rd MUM, College park, MD, pp 85–92

  33. Thompson N, He G, Luo H (2006) Flow scheduling for end-host multihoming. In: Proceedings IEEE INFOCOM

  34. Toyama K, Murty RN, Thekkath CA, Chandra R (2007) Cost-aware networking over heterogeneous data channels. US patent 20070171915. http://www.freepatentsonline.com/y2007/0171915.html

  35. Vanrompay Y, Rigole P, Berbers Y (2007) Predicting network connectivity for context-aware pervasive systems with localized network availability. In: WoSSIoT’07, a workshop of EuroSys

  36. Wang H, Katz R, Giese J (2004) Policy-enabled handoffs across heterogeneous wireless networks. In: Mobile computing systems and applications

  37. Xian C, Lu Y, Li Z (2007) Energy aware scheduling for realtime multiprocessor systems with uncertain task execution time. In: Proceedings of DAC, Califf, USA

  38. Yuan W, Nahrstedt K (2003) Energy-efficient soft real-time CPU scheduling for mobile multimedia systems. In: Proc. of 19th ACM Symposium on Operating Systems Principles (SOSP’03). Bolton Landing, NY

  39. Zaharia M, Keshav S (2007) Fast and optimal scheduling over multiple network interfaces. Technical Report CS-2007-36, University of Waterloo

  40. Zaidi ZR, Mark BL (2004) Mobility estimation for wireless networks based on an autoregressive model. In: Proc. IEEE Globecom 2004, Dallas, Texas

  41. Zhu F, McNair J (2004) Optimizations for vertical handoff decision algorithms. In: Proc. WCNC

Download references

Acknowledgements

This work has been performed in the context of NICTA’s CAMP project, which is funded by Ericsson. We would like to thank NICTA staff and other volunteers who participated in our experiments.

Author information

Authors and Affiliations

  1. NICTA, Sydney, Australia

    Upendra Rathnayake, Henrik Petander, Maximilian Ott & Aruna Seneviratne

  2. EET school of UNSW, Sydney, Australia

    Upendra Rathnayake & Aruna Seneviratne

Authors
  1. Upendra Rathnayake
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Henrik Petander
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Maximilian Ott
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Aruna Seneviratne
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Upendra Rathnayake.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Rathnayake, U., Petander, H., Ott, M. et al. EMUNE: Architecture for Mobile Data Transfer Scheduling with Network Availability Predictions. Mobile Netw Appl 17, 216–233 (2012). https://doi.org/10.1007/s11036-011-0332-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11036-011-0332-4

Keywords

Search

Navigation