When David helps Goliath: The Case for 3G Onloading

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Access link can often be the bottleneck for application performance. In this paper, we propose to augment wired connections using cellular ones, that we term “3G onloading (3GOL)". 3GOL utilizes available mobile devices and alreadypaid-for data volumes to augment and improve performance of applications on wired network. We motivate 3GOL by understanding bottlenecks present in the wired and the cellular networks. In order to understand the potential benefits of 3GOL, we conduct active experiments using mobile devices. We show that capacity gains can scale linearly with the number of devices on the downlink while also seeing improvements on the uplink. Using real traces we show how video on demand can benefit with 3GOL, even when volume caps are in place. We design 3GOL as an over the top service, and highlight research challenges.

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When David helps Goliath: The Case for 3G Onloading

  1. 1. When David helps Goliath:The case for 3G OnloadingNarseo Vallina-Rodriguez, Vijay Erramilli, Yan Grunenberger,Laszlo Gyarmati, Nikos Laoutaris, Rade Stanojevic,Dina PagagiannakiUniversity of CambridgeTelefonica Research / Telefonica Digital HotNets 2012, Redmond, WA
  2. 2. David and Goliath 100xWired Network (DSL) Cellular Network 200m5.8 Gbps downlink 47 Mbps downlink 2.3 Gbps uplink 5.6 Mbps uplink Narseo Vallina-Rodriguez, University of Cambridge/Telefonica Research, HotNets12 2
  3. 3. Can David help Goliath? YES!¤  For 1 ADSLà the entire BS is not David¤  For all ADSLs à David can become Goliath FOR SHORT PERIODS OF TIME Narseo Vallina-Rodriguez, University of Cambridge/Telefonica Research, HotNets12 3
  4. 4. 3G Onloading¤  Offload traffic from the wired network onto the cellular network ¤  Speed up wired connections ¤  Improve applications’ performance¤  Limitations: ¤  3GOL cannot assist all wired connections ¤  Cannot help applications at all times Narseo Vallina-Rodriguez, University of Cambridge/Telefonica Research, HotNets12 4
  5. 5. Scenario 1: David helps Goliath ¤  Video-streaming application ¤  Well provisioned area 4.7 Mbps ¤  Spare capacity on A cellular network ¤  Powerboost 3.4 Mbps ¤  Use-and-release Narseo Vallina-Rodriguez, University of Cambridge/Telefonica Research, HotNets12 5
  6. 6. Scenario 2: David becomes Goliath ¤  Constrained wired networks ¤  Cellular network can 4.7 Mbps provide more capacity than wired networks A 2 Km2.8 Mbps Narseo Vallina-Rodriguez, University of Cambridge/Telefonica Research, HotNets12 6
  7. 7. Design Considerations¤  The Network ¤  3G throughput is highly variable ¤  Control-plane latency¤  The User Economics: volume caps in data plans ¤  40 % of the mobile users use less than 10% of their cap¤ The Service ¤  Network integrated service ¤  Over the top Narseo Vallina-Rodriguez, University of Cambridge/Telefonica Research, HotNets12 7
  8. 8. Preliminary results¤  How much additional throughput?¤  Performance improvement?¤  Increase in cellular traffic? Narseo Vallina-Rodriguez, University of Cambridge/Telefonica Research, HotNets12 8
  9. 9. How much additional throughput?Scenario Time DSL (d/u) Mbps 1. The Network¤  Densely populated residential 1 am 3.44 / 0.30area (city center) ¤  3G throughput depends on a number of factors ¤  Limited 3G network backhaul capacity2. Office area rush hour 4 pm 4.51 / 0.47 ¤  Signaling delay3. Residential Area in tourist 10 pm 6.72 / 0.84¤  The Economics hotspot ¤  Data volume caps 4. Sparsely populated residential 1 am 2.84 / 0.45¤  The Service area (suburbs) ¤  Network integrated service5. Popular shopping center in peak 2 pm ¤  Over the top n/atime Narseo Vallina-Rodriguez, University of Cambridge/Telefonica Research, HotNets12 9
  10. 10. How much additional throughput? Upstream Downstream Upstream Upstream Upstream Aggregated Throughput (Kbps) Upstream Upstream Downstream Downstream Downstream Downstream Downstream 15000 Aggregated Throughput (Kbps) Aggregated Throughput (Kbps) Aggregated Throughput (Kbps)Aggregated Throughput (Kbps) Aggregated Throughput (Kbps) 15000 15000 15000 1500015000 10000 10000 10000 10000 10000 10000 5000 5000 5000 5000 50005000 0 0 0 0 0 0 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 7 8 9 4 5 7 8 9 Cluster Size 672 710 894 96 106 8 9 10 10 1 12 23 34 45 561 672 783 894 196 2 7 1 8 2 9 3 104 10 561 3 83 5 10 7 3 4 5 6 1 2 3 10 5 10 106 3 1 4 2 5 3 6 45 2 17 8 9 4 5 7 8 9 Cluster Size Size Cluster SizeSize Cluster Size Cluster Cluster Densely location Location1 Residential Location3 Location2 Location4 Shopping Location5 Office center populated location Location2 location area. Location1 Location3 Location2 Location1 Location3 location Location1 Location2 Location4 Location3 Location2 Location4 Location1 Location1 Location2 locationlocation Suburbs Location3 Location5 Location4 Location3 Location5Location4Location5 Location5 Location4 Location5 area (city center) area Tourist hotspot Narseo Vallina-Rodriguez, University of Cambridge/Telefonica Research, HotNets12 10
  11. 11. How much additional throughput?Scenario Time DSL (d/u) Cellular (d/u) 3GOL/DSL Mbps Mbps (d/u)1. Densely populated 1 am 3.44 / 0.30 4.37 / 1.64 2.3 / 6.5residential area (city center)2. Office area rush hour 4 pm 4.51 / 0.47 4.56 / 5.18 2.0 / 12.03. Residential Area in tourist 10 pm 6.72 / 0.84 1.92 / 1.53 1.3 / 2.8hotspot4. Sparsely populated 1 am 2.84 / 0.45 4.67 / 3.89 2.7 / 9.7residential area (suburbs)5. Popular shopping center in 2 pm n/a 5.31 / 2.64 n/apeak time Narseo Vallina-Rodriguez, University of Cambridge/Telefonica Research, HotNets12 11
  12. 12. Performance improvement: Video-streaming Empirical CDF Empirical CDF 1 1 0.9 0.9 0.8 0.8 50% of the videos 0.7 have a speed up factor 0.7fraction of videos fraction of users 0.6 of 10 and below 0.6 0.5 0.5 0.4 0.4 40% of users have a speed up around 20% 0.3 0.3 0.2 0.2 0.1 Unlimited 0.1 Capped 0 0 0 5 10 15 20 1 1.2 1.4 1.6 1.8 2 2.2 2.4 2.6 dsl/3GOL dsl/3GOl(40MB) Narseo Vallina-Rodriguez, University of Cambridge/Telefonica Research, HotNets12 12
  13. 13. Increase in 3G traffic 5 10 3GOL(20Mb budget) 3GOL(Unlim) load on nwk (Mbs) 4 10 Cell capacity 3 Overload 10 Available Bandwidth 2 10 1 10 0 2 4 6 8 10 12 14 16 18 20 22 24 time (5min bins) Narseo Vallina-Rodriguez, University of Cambridge/Telefonica Research, HotNets12 13
  14. 14. Prototype implementation Narseo Vallina-Rodriguez, University of Cambridge/Telefonica Research, HotNets12 14
  15. 15. Research challenges¤  Decide when to use 3GOL ¤  Which apps and when!¤  Use the right devices ¤  Cell Nets are best effort! ¤  Pre-fetching radio channel¤  How much data to onload¤  How to aggregate different connections: ¤  Same Wi-Fi AP ¤  ClubDSL [Mobicom 2011] Narseo Vallina-Rodriguez, University of Cambridge/Telefonica Research, HotNets12 15
  16. 16. Related Work¤  Wired networks performance. ¤  Sundaresan et al. Broadband internet performance: a view from the gateway. ACM SIGCOMM 2011. ¤  Kreibich et al. NetAlyzr, IMC 2010¤  3G Offloading ¤  Badam et al. The hare and the tortoise: taming wireless losses by exploiting wired eliability. In MobiHoc, 2011. ¤  Lee et al. Mobile data offloading: how much can wifi deliver? CoNext 2010¤  Mobile networks ¤  Ha et al. Tube. ACM Sigcomm, 2012 ¤  Huang et al. A close examination of performance and power characteristics of 4G/LTE networks ¤  Qiang et al. Characterizing radio resource allocation for 3g networks ¤  Vallina-Rodriguez et al. Breaking for commercials (To appear) IMC 2012 Narseo Vallina-Rodriguez, University of Cambridge/Telefonica Research, HotNets12 16
  17. 17. Summary¤  David can help Goliath ¤  Powerboost-like service ¤  Constrained wired networks¤  Overhead in cellular network can be controlled ¤  Use and release ¤  Data caps¤  Better performance expected with LTE deployment Narseo Vallina-Rodriguez, University of Cambridge/Telefonica Research, HotNets12 17
  18. 18. Questions?Narseo Vallina-Rodrigueznv240@cam.ac.ukUniversity of Cambridge /Telefonica Research Narseo Vallina-Rodriguez, University of Cambridge/Telefonica Research, HotNets12 18

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