http://iet.metastore.ingenta.com
1887

Add-net: adaptive dichotomy based network-centric cellular to Wi-Fi offloading

Add-net: adaptive dichotomy based network-centric cellular to Wi-Fi offloading

For access to this article, please select a purchase option:

Buy article PDF
£12.50
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Communications — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

Over last 4–5 years, there has been an exponential increase in the amount of traffic transmitted over cellular network. Importantly, with humongous increase in the Wi-Fi hotspots across many places, subscribers tend to manually switch from cellular to Wi-Fi network. However, in this process, the operator loses the visibility of subscribers, and is not able to control the congestion in network, and importantly, is not able to provide a guaranteed quality of experience (QoE) to the subscribers. In this study, a network-centric near-real-time mechanism is proposed for maintaining QoE among the subscribers but is found to be a non-deterministic problem. Importantly, an adaptive dichotomic classification based mechanism is proposed and investigated for offloading the cellular subscribers to Wi-Fi network, while keeping the computational complexity to less than O(log(n)), where n is the number of nodes in a binary tree. Further, an algorithm is proposed for intelligent selection of subscriber profile that would enable faster completion of the offloading process. An extensive simulation of the proposed algorithm and comparison with state-of-the-art mechanisms reveal up to seven time reduction in computational time; with additional performance increase occurring with increasing number of subscribers.

References

    1. 1)
      • 1. Gartner Report: ‘Mobile data growth worldwide’. Available at http://www.gartner.com/newsroom/id/3098617, accessed 3 September 2015.
        .
    2. 2)
      • 2. ‘3GPP system to wireless local area network (WLAN) interworking: system description’, 3GPP TS23.234 – accessed 2 September 2015.
        .
    3. 3)
      • 3. Wired/Wireless Network: ‘A new class-defining wireless broadband data traffic management and offloading solution’. Available at http://www.kt.com/eng/biz/gs_01_02.jsp, accessed 3 September 2015.
        .
    4. 4)
      • 4. ‘Mobile network offload: end to end cost comparisons for femto cell, Wi-Fi and MacroRAN’, Whitepaper by ABI Research, Q2, 2012.
        .
    5. 5)
    6. 6)
      • J. Li , Y. Yi , S. Chong .
        6. Li, J., Yi, Y., Chong, S., et al: ‘Economics for Wi-Fi offloading: trading delay for cellular capacity’, IEEE Trans. Wirel. Commun., 2014, 3, (3), pp. 15401554.
        . IEEE Trans. Wirel. Commun. , 3 , 1540 - 1554
    7. 7)
      • J. Huang .
        7. Huang, J.: ‘Mobile data offloading: a tutorial’. IEEE Int. Conf. on Communications (ICC), Sydney, Australia, 10–14 June 2014.
        . IEEE Int. Conf. on Communications (ICC)
    8. 8)
      • 8. ‘Mobile data offloading through Wi-Fi’. Available at http://www.aptilo.com/mobile-data-offloading/wifi-offload-3g-4g, accessed 3 September 2015.
        .
    9. 9)
      • 9. Coleago Consulting: ‘Will Wi-Fi relieve congestion on cellular networks’, Prepared for GSMA, 2014.
        .
    10. 10)
      • 10. The Mobile Broadband Standard. Available at http://www.3gpp.org/release-13, accessed 5 October 2015.
        .
    11. 11)
      • 11. 4G Americas: ‘Mobile broadband evolution towards 5G: Rel. 12, Rel. 13 and beyond’, June 2015.
        .
    12. 12)
      • S. Dimatteo , P. Hui , B. Han .
        12. Dimatteo, S., Hui, P., Han, B., et al: ‘Cellular traffic offloading through Wi-Fi networks’. IEEE Int. Conf. on Mobile Adhoc and Sensor Systems (MASS), 17–22 October 2011, pp. 192201.
        . IEEE Int. Conf. on Mobile Adhoc and Sensor Systems (MASS) , 192 - 201
    13. 13)
      • 13. Architecture enhancements for non 3GPP access’, 3GPP TS23.402 – accessed 2 September 2015.
        .
    14. 14)
      • Y. Fukagawa , T. Nomura .
        14. Fukagawa, Y., Nomura, T.: ‘Understanding WLAN offload’, WhitePaper by Anritsu Corporation, June 2014.
        .
    15. 15)
      • B. Han , P. Hui , V. Kumar .
        15. Han, B., Hui, P., Kumar, V., et al: ‘Cellular traffic offloading through opportunistic communications: a case study’. ACM CHANTS 2010, September 2010.
        . ACM CHANTS 2010
    16. 16)
      • V.A. Siris , D. Kalyvas .
        16. Siris, V.A., Kalyvas, D.: ‘Enhancing mobile data offloading with mobility prediction and prefetching’. Proc. Seventh ACM Int. Workshop on Mobility in Evolving Internet Architecture (MobiArch), 2012, pp. 1722.
        . Proc. Seventh ACM Int. Workshop on Mobility in Evolving Internet Architecture (MobiArch) , 17 - 22
    17. 17)
    18. 18)
      • S. Krishna , A. Goldsmith , M. Carlton .
        18. Krishna, S., Goldsmith, A., Carlton, M.: ‘Seamless handoff, offload, and load balancing in integrated Wi-Fi/small cell systems’, Patent Publication No. US20130077482A1, 2013.
        .
    19. 19)
      • H. Venkataraman , P. Bauskar , A. Joshi .
        19. Venkataraman, H., Bauskar, P., Joshi, A.: ‘A computer implemented system and method for offloading data’, Patent Filed, Filing No: 1113/MUM/2014, 2014.
        .
    20. 20)
    21. 21)
    22. 22)
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-com.2015.0958
Loading

Related content

content/journals/10.1049/iet-com.2015.0958
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address