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Deviceless Communications: Cloud-Based Communications for Heterogeneous Networks

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Abstract

Mobile networks today see increasingly large numbers of connected user equipments (UE), allowing users to go beyond voice calling and tap into rich on-line services. Parallel to this evolution, other devices, such as TV’s, home automation or even Internet of Things controllers, have become integrated with connectivity capabilities, allowing them to not only be locally connected, but also be reachable from the Internet. In this paper we propose a deviceless communication approach, where data and media flows reaching a user can be individually shifted into nearby devices. To support this, we present a framework that explores and enhances Software Defined Network and Network Function Virtualisation concepts, allowing the opportunistic utilization of nearby devices as the user moves, while still being perceived as a single end-point towards external entities. An experimental validation scenario is presented, showcasing a video stream being delivered to a nearby large TV screen, allowing the user to watch the video while a voice call is routed to a nearby phone. Results showcase the feasibility of the proposed framework and how virtualisation of both the UE and the points of attachment contribute to reduce the impact of flow management in the physical devices.

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Notes

  1. In the past years mobile data traffic has been increasingly growing along with the number of connected devices. Despite composing 45% of the total network attached devices in 2016, smartphones accounted for 81% of the total mobile traffic, with mobile video representing 60% of the traffic [1].

  2. Youtube: https://www.youtube.com/.

  3. Netflix: https://www.netflix.com/.

  4. Bluetooth beacon device: ByteReal TagBeacon 2.0.

  5. Android Beacon Library: https://altbeacon.github.io/android-beacon-library/.

  6. POX: https://github.com/noxrepo/pox.

  7. Hostapd: https://w1.fi/hostapd/.

  8. Capsulator: http://archive.openflow.org/wk/index.php/Capsulator.

  9. Media format standards for Android: https://developer.android.com/guide/topics/media/media-formats.html.

  10. Raspberry Pi 3: https://www.raspberrypi.org/products/raspberry-pi-3-model-b/.

  11. iperf: https://iperf.fr/.

  12. Video Caminandes 3: http://www.caminandes.com/.

References

  1. Cisco. (2017). Cisco visual networking index: Global mobile data traffic forecast update, 2016–2021 white paper. http://www.cisco.com/c/en/us/solutions/collateral/service-provider/visual-networking-index-vni/mobile-white-paper-c11-520862.html. Accessed Sept 2017.

  2. European Telecommunications Standards Institute. Network functions virtualisation: Network operator perspectives on nfv priorities for 5g (2017). https://portal.etsi.org/nfv/nfv_white_paper.pdf. Accessed Sept 2017.

  3. Ericsson. (2017). 5G Systems White Paper. https://www.ericsson.com/res/docs/whitepapers/wp-5g-systems.pdf. Accessed Sept 2017.

  4. Onishi, H., & Asaka, T. (2016). Performance evaluation of participatory sensing scheme using delay tolerant networking. In 2016 Fourth International Symposium on Computing and Networking (CANDAR) (pp. 291–296). IEEE.

  5. Meneses, F., Corujo, D., Guimaraes, C., & Aguiar, R. L. (2017). An abstraction framework for flow mobility in multi-technology 5G environments using virtualization and SDN. In 2017 IEEE Conference on Network Softwarization (NetSoft) (pp. 1–5). IEEE.

  6. Saito, H., Sugo, K., Aida, H., Thepvilojanapong, N., & Tobe, Y. (2012). SBike: Acquisition of person’s state riding a bicycle with mobile sensing for participatory sensing. IPSJ Journal, 53(2), 770–782.

    Google Scholar 

  7. Rana, R. K., Chou, C. T., Kanhere, S. S., Bulusu, N., & Hu, W. (2010). Ear-phone: An end-to-end participatory urban noise mapping system. In Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks (pp. 105–116). ACM.

  8. Ferguson, A. D., Guha, A., Liang, C., Fonseca, R., & Krishnamurthi, S. (2013). Participatory networking: An API for application control of SDNs. In ACM SIGCOMM computer communication review (Vol. 43, No. 4, pp. 327–338). ACM.

  9. McKeown, N., Anderson, T., Balakrishnan, H., Parulkar, G., Peterson, L., Rexford, J., et al. (2008). OpenFlow: Enabling innovation in campus networks. ACM SIGCOMM Computer Communication Review, 38(2), 69–74.

    Article  Google Scholar 

  10. Open Networking Foundation. Special report: Openflow and sdn state of the union (2016). https://www.opennetworking.org/images/stories/downloads/sdn-resources/special-reports/Special-Report-OpenFlow-and-SDN-State-of-the-Union-B.pdf. Accessed Sept 2017.

  11. Yiakoumis, Y., Schulz-Zander, J., & Zhu, J. (2011). Pantou: OpenFlow 1.0 for OpenWRT. http://www.openflow.org/wk/index.php/OpenFlow_1.0_for_OpenWRT. Accessed Sept 2017.

  12. Yap, K. K., Kobayashi, M., Sherwood, R., Huang, T. Y., Chan, M., Handigol, N., et al. (2010). OpenRoads: Empowering research in mobile networks. ACM SIGCOMM Computer Communication Review, 40(1), 125–126.

    Article  Google Scholar 

  13. Guimarães, C., Corujo, D., & Aguiar, R. L. (2014). Enhancing openflow with media independent management capabilities. In 2014 IEEE International Conference on Communications (ICC) (pp. 2995–3000). IEEE.

  14. Chen, C., Lin, Y. T., Yen, L. H., Chan, M. C., & Tseng, C. C. (2016). Mobility management for low-latency handover in SDN-based enterprise networks. In 2016 IEEE Wireless Communications and Networking Conference (WCNC) (pp. 1–6). IEEE.

  15. Giust, F., Cominardi, L., & Bernardos, C. J. (2015). Distributed mobility management for future 5G networks: Overview and analysis of existing approaches. IEEE Communications Magazine, 53(1), 142–149.

    Article  Google Scholar 

  16. Nguyen, T. T., Bonnet, C., & Harri, J. (2016). SDN-based distributed mobility management for 5G networks. In 2016 IEEE Wireless Communications and Networking Conference (WCNC) (pp. 1–7). IEEE.

  17. Bernardos, C. J., De La Oliva, A., Serrano, P., Banchs, A., Contreras, L. M., Jin, H., et al. (2014). An architecture for software defined wireless networking. IEEE wireless communications, 21(3), 52–61.

    Article  Google Scholar 

  18. Dely, P., Kassler, A., Chow, L., Bambos, N., Bayer, N., Einsiedler, H., et al. (2014). Best-ap: Non-intrusive estimation of available bandwidth and its application for dynamic access point selection. Computer Communications, 39, 78–91.

    Article  Google Scholar 

  19. Lee, J., Uddin, M., Tourrilhes, J., Sen, S., Banerjee, S., Arndt, M., et al. (2014). mesdn: Mobile extension of sdn. In Proceedings of the Fifth International Workshop on Mobile Cloud Computing & Services (pp. 7–14). ACM.

  20. Meneses, F., Corujo, D., Guimaraes, C., & Aguiar, R. L. (2015). Extending sdn to end nodes towards heterogeneous wireless mobility. In 2015 IEEE Globecom Workshops (GC Wkshps) (pp. 1–6). IEEE.

  21. Meneses, F., Corujo, D., Guimaraes, C., & Aguiar, R. L. (2015). Multiple flow in extended sdn wireless mobility. In 2015 Fourth European Workshop on Software Defined Networks (EWSDN) (pp. 1–6). IEEE.

  22. Makris, N., Choumas, K., Zarafetas, C., Korakis, T., & Tassiulas, L. (2016). Forging Client Mobility with OpenFlow: An experimental study. In 2016 IEEE Wireless Communications and Networking Conference (WCNC) (pp. 1–7). IEEE.

  23. Andreev, S., Pyattaev, A., Johnsson, K., Galinina, O., & Koucheryavy, Y. (2014). Cellular traffic offloading onto network-assisted device-to-device connections. IEEE Communications Magazine, 52(4), 20–31.

    Article  Google Scholar 

  24. Ericsson. (2015). Cloud RAN: the benefits of virtualization, centralization and coordination—White Paper. https://www.ericsson.com/res/docs/whitepapers/wp-cloud-ran.pdf. Accessed Sept 2017.

  25. Li, L. E., Mao, Z. M., & Rexford, J. (2012). Toward software-defined cellular networks. In 2012 European Workshop on Software Defined Networking (EWSDN) (pp. 7–12). IEEE.

  26. Gudipati, A., Perry, D., Li, L. E., & Katti, S. (2013). SoftRAN: Software defined radio access network. In Proceedings of the Second ACM SIGCOMM Workshop on Hot Topics in Software Defined Networking (pp. 25–30). ACM.

  27. Cai, Y., Yu, F. R., & Bu, S. (2014). Cloud radio access networks (C-RAN) in mobile cloud computing systems. In 2014 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) (pp. 369–374). IEEE.

  28. Akyildiz, I. F., Wang, P., & Lin, S. C. (2015). SoftAir: A software defined networking architecture for 5G wireless systems. Computer Networks, 85, 1–18.

    Article  Google Scholar 

  29. Suresh, L., Schulz-Zander, J., Merz, R., Feldmann, A., & Vazao, T. (2012). Towards programmable enterprise WLANS with Odin. In Proceedings of the First Workshop on Hot Topics in Software Defined Networks (pp. 115–120). ACM.

  30. Dely, P., Vestin, J., Kassler, A., Bayer, N., Einsiedler, H., & Peylo, C. (2012). CloudMAC—An OpenFlow based architecture for 802.11 MAC layer processing in the cloud. In 2012 IEEE Globecom Workshops (GC Wkshps) (pp. 186–191). IEEE.

  31. Barraca, J. P., Gomes, D., & Aguiar, R. L. (2010). AMazING–Advanced Mobile wIreless playGrouNd. In International Conference on Testbeds and Research Infrastructures (pp. 219–230). Berlin: Springer.

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Acknowledgements

This work is funded by FCT/MEC through national funds and when applicable co-funded by FEDER PT2020 partnership agreement under the Project UID/EEA/50008/2013, and by the Integrated Programme of SR&TD SOCA (Ref. CENTRO-01-0145-FEDER-000010), co-funded by Centro 2020 program, Portugal 2020, European Union, through the European Regional Development Fund, and by the FCT Grant SFRH/BD/96553/2013.

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Meneses, F., Guimarães, C., Magalhães, T. et al. Deviceless Communications: Cloud-Based Communications for Heterogeneous Networks. Wireless Pers Commun 100, 25–46 (2018). https://doi.org/10.1007/s11277-018-5621-9

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