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Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
Augmenting mobile 3 g using wifi
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Augmenting mobile 3 g using wifi

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Ke Huang, UMass Lowell 91.650 Spring 2011

Ke Huang, UMass Lowell 91.650 Spring 2011

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  • 1. Augmenng  Mobile  3G  Using  WiFi By:  Aruna  Balasubramanian,  Ratul  Mahajan,  Arun   Venkataramani Presenter:  Ke  HuangTuesday, April 12, 2011 1
  • 2. Demand  for  mobile  access  growing                        www.totaltele.com h+p://www.readwriteweb.com 2Tuesday, April 12, 2011 2
  • 3. Demand  for  mobile  access  growing                        www.totaltele.com h+p://www.readwriteweb.com 900  million  mobile  broadband  subscripons  today….                                                                                                                                                         www.3gamericas.org                                                       2Tuesday, April 12, 2011 2
  • 4. Mobile  demand  is  projected  to  far   3Tuesday, April 12, 2011 3
  • 5. Mobile  demand  is  projected  to  far   www.rysavy.com Current  spectrum 409.5  MHz Unallocated  spectrum   230  MHz (including  whitespaces) Projected  demand  by   800  MHz  –   2016   1000  MHz 3Tuesday, April 12, 2011 3
  • 6. Mobile  demand  is  projected  to  far   www.nyCmes.com www.rysavy.com Current  spectrum 409.5  MHz Unallocated  spectrum   230  MHz (including  whitespaces) Projected  demand  by   800  MHz  –   2016   1000  MHz 3Tuesday, April 12, 2011 3
  • 7. Mobile  demand  is  projected  to  far   www.nyCmes.com www.rysavy.com Current  spectrum 409.5  MHz Unallocated  spectrum   230  MHz (including  whitespaces) Projected  demand  by   800  MHz  –   2016   1000  MHz www.nyCmes.com“In  light  of  the  limited  natural  resource  of  spectrum,  we  have  to  look  at   the  ways  of  conserving  spectrum”  -­‐-­‐  Mark  Siegel  (AT&T) Reducing  cellular  spectrum  ulizaon  is  key! 3Tuesday, April 12, 2011 3
  • 8. How  can  we  reduce  spectrum  usage? blogs.chron.com 1.  Behavioral 2.  Economic 3.  Technical 4Tuesday, April 12, 2011 4
  • 9. How  can  we  reduce  spectrum  usage? blogs.chron.com 1.  Behavioral www.usatoday.com 2.  Economic 3.  Technical 4Tuesday, April 12, 2011 4
  • 10. How  can  we  reduce  spectrum  usage? blogs.chron.com 1.  Behavioral www.usatoday.com 2.  Economic 3.  Technical 4Tuesday, April 12, 2011 4
  • 11. Augmenng  Mobile  3G  using  WiFi                            Offload  data  to  WiFi  when  possible                              Focus  on  vehicular  mobility 5Tuesday, April 12, 2011 5
  • 12. Offloading  3G  data  to  WiFi 6Tuesday, April 12, 2011 6
  • 13. Offloading  3G  data  to  WiFi 6Tuesday, April 12, 2011 6
  • 14. Offloading  3G  data  to  WiFi 6Tuesday, April 12, 2011 6
  • 15. Offloading  3G  data  to  WiFi 6Tuesday, April 12, 2011 6
  • 16. Offloading  3G  data  to  WiFi 6Tuesday, April 12, 2011 6
  • 17. Offloading  3G  data  to  WiFi 6Tuesday, April 12, 2011 6
  • 18. Related  work  on  mulple  interfaces Improving  performance  using  handoffs  based  on   current  condions Reducing  power  consumpon  by  switching   across  mulple  interfaces   7Tuesday, April 12, 2011 7
  • 19. Related  work  on  mulple  interfaces Improving  performance  using  handoffs  based  on   current  condions Reducing  power  consumpon  by  switching   across  mulple  interfaces   This  work: 1.How  much  3G  data  can  be  offloaded  to  WiFi? 2.How  to  offload  without  hurng  applicaons? 7Tuesday, April 12, 2011 7
  • 20. Contribuons Measurement:    Joint  study  of  3G  and  WiFi   connecvity Across  three  cies:  Amherst,  Seagle,  SFO System:  Wiffler,  to  offload  3G  data  to  WiFi  while   respecng  applicaon  constraints   Deployed  on  20  vehicles 8Tuesday, April 12, 2011 8
  • 21. Measurement  setup Testbed:  Vehicles  with  3G  and  WiFi  (802.11b)  radios Amherst:  20  buses  +  1  car,  Seagle:  1  car,  SFO:  1  car Soiware:  Simultaneously  probes  3G  and  WiFi  for   Availability,  loss  rate,  throughput Duraon:  3000+  hours  of  data  over  12+  days 9Tuesday, April 12, 2011 9
  • 22. Open  WiFi  availability  low,  but  useful Availability    =  fracon  of  1-­‐second  intervals  when  at  least   one  packet  received                                             Availability (%) 10Tuesday, April 12, 2011 10
  • 23. Open  WiFi  availability  low,  but  useful Availability    =  fracon  of  1-­‐second  intervals  when  at  least   one  packet  received                                             86% Availability (%) 10Tuesday, April 12, 2011 10
  • 24. Open  WiFi  availability  low,  but  useful Availability    =  fracon  of  1-­‐second  intervals  when  at  least   one  packet  received                                             86% Availability (%) 11% 10Tuesday, April 12, 2011 10
  • 25. Open  WiFi  availability  low,  but  useful Availability    =  fracon  of  1-­‐second  intervals  when  at  least   one  packet  received                                             86% Availability (%) 11% 7% 10Tuesday, April 12, 2011 10
  • 26. Open  WiFi  availability  low,  but  useful Availability    =  fracon  of  1-­‐second  intervals  when  at  least   one  packet  received                                             86% Availability (%) 3G+WiFi  combinaCon  be+er  than  sum  pf  parts 11% 7% 10Tuesday, April 12, 2011 10
  • 27. WiFi  loss  rate  is  higher Loss  rate  =  Fracon  of  packets  lost  at  10  probes/sec Cumulative fraction WiFi 3G 11Tuesday, April 12, 2011 11
  • 28. WiFi  loss  rate  is  higher Loss  rate  =  Fracon  of  packets  lost  at  10  probes/sec Cumulative fraction 28%   WiFi 3G 11Tuesday, April 12, 2011 11
  • 29. WiFi  loss  rate  is  higher Loss  rate  =  Fracon  of  packets  lost  at  10  probes/sec Cumulative fraction 28%   WiFi 8%   3G 11Tuesday, April 12, 2011 11
  • 30. WiFi  (802.11b)  throughput  is  lower Throughput  =  Total  data  received  per  second WiFi Cumulative fraction 3G Upstream WiFi Cumulative fraction 3G Downstream 12Tuesday, April 12, 2011 12
  • 31. WiFi  (802.11b)  throughput  is  lower Throughput  =  Total  data  received  per  second WiFi Cumulative fraction 3G Upstream WiFi Cumulative fraction 3G Downstream 12Tuesday, April 12, 2011 12
  • 32. WiFi  (802.11b)  throughput  is  lower Throughput  =  Total  data  received  per  second WiFi Cumulative fraction 3G Upstream 0.35 WiFi Cumulative fraction 3G Downstream 12Tuesday, April 12, 2011 12
  • 33. WiFi  (802.11b)  throughput  is  lower Throughput  =  Total  data  received  per  second WiFi Cumulative fraction 3G Upstream 0.35 0.72 WiFi Cumulative fraction 3G Downstream 12Tuesday, April 12, 2011 12
  • 34. WiFi  (802.11b)  throughput  is  lower Throughput  =  Total  data  received  per  second WiFi Cumulative fraction 3G Upstream 0.35 0.72 WiFi Cumulative fraction 3G Downstream 12Tuesday, April 12, 2011 12
  • 35. Implicaons  of  measurement  study Strawman  augmentaon:  Use  WiFi  when   available Can  offload  only  ~11%  of  the  me Can  hurt  applicaons  because  of  WiFi’s  higher  loss   rate  and  lower  throughput 13Tuesday, April 12, 2011 13
  • 36. Key  ideas  in  Wiffler Increase  savings  for  delay-­‐ Reduce  damage  for  delay-­‐ tolerant  applicaons sensive  applicaons Problem:  Using  WiFi  only   Problem:  Using  WiFi   when  available  saves   whenever  available  can   ligle  3G  usage hurt  applicaon  quality Soluon:  Exploit  delay-­‐ Soluon:  Fast  switch  to  3G   tolerance  to  wait  to   when  WiFi  delays   offload  to  WiFi  when   availability  predicted exceed  threshold 14Tuesday, April 12, 2011 14
  • 37. Predicon-­‐based  offloading D  =  Delay-­‐tolerance  threshold  (seconds) S  =  Data  remaining  to  be  sent  (bytes) Each  second, 1. If  (WiFi  available),  send  data  on  WiFi   2. Else  if  (W(D)  <  S),  send  data  on  3G 3. Else  wait  for  WiFi. 15Tuesday, April 12, 2011 15
  • 38. Predicon-­‐based  offloading D  =  Delay-­‐tolerance  threshold  (seconds) S  =  Data  remaining  to  be  sent  (bytes) Each  second, 1. If  (WiFi  available),  send  data  on  WiFi   2. Else  if  (W(D)  <  S),  send  data  on  3G Predicted  WiFi   transfer  size  in   3. Else  wait  for  WiFi. next  D  seconds   15Tuesday, April 12, 2011 15
  • 39. Predicng  WiFi  capacity History-­‐based  predicon  of  #  of  APs  using  last  few   AP  encounters   WiFi  capacity  =  (expected  #APs)  x  (capacity  per  AP) Simple  predictor  yields  low  error  both  in  Amherst   and  Seagle 16Tuesday, April 12, 2011 16
  • 40. Predicng  WiFi  capacity History-­‐based  predicon  of  #  of  APs  using  last  few   AP  encounters   WiFi  capacity  =  (expected  #APs)  x  (capacity  per  AP) Simple  predictor  yields  low  error  both  in  Amherst   and  Seagle Negligible  benefits  with  more  sophiscated  predicon,  eg   future  locaon  predicon  +  AP  locaon  database 16Tuesday, April 12, 2011 16
  • 41. Fast  switching  to  3G Problem: WiFi  losses  bursty  =>  high  retransmission  delay Approach: If  no  WiFi  link-­‐layer  ACK  within  50ms,  switch  to  3G Else,  connue  sending  on  WiFi 17Tuesday, April 12, 2011 17
  • 42. Wiffler  implementaon Wiffler   proxy § Predicon-­‐based  offloading  upstream  +  downstream §  Fast  switching  only  upstream Ø Implemented  using  signal-­‐upon-­‐ACK  in  driver 18Tuesday, April 12, 2011 18
  • 43. Evaluaon  Roadmap Predicon-­‐based  offloading Deployment  on  20  DieselNet  buses  in  150  sq.  mi   region  around  Amherst Trace-­‐driven  evaluaon  using  throughput  data Fast  switching Deployment  on  1  car  in  Amherst  town  center Trace-­‐driven  evaluaon  using  measured  loss/delay   trace  using  VoIP-­‐like  probe  traffic 19Tuesday, April 12, 2011 19
  • 44. Deployment  results Data  offloaded  to  WiFi Wiffler’s  predicon-­‐based  offloading 30% WiFi  when  available 10% File  transfer  size:  5MB;  Delay  tolerance:  60  secs;     Inter-­‐transfer  gap:  random  with  mean  100  secs 20Tuesday, April 12, 2011 20
  • 45. Deployment  results Data  offloaded  to  WiFi Wiffler’s  predicon-­‐based  offloading 30% WiFi  when  available 10% File  transfer  size:  5MB;  Delay  tolerance:  60  secs;     Inter-­‐transfer  gap:  random  with  mean  100  secs %  Cme  good  voice  quality   Wiffler’s  fast  switching 68% WiFi  when  available  (no  switching) 42% VoIP-­‐like  traffic:  20-­‐byte  packet  every  20  ms   20Tuesday, April 12, 2011 20
  • 46. Trace-­‐driven  evaluaon Parameters  varied Workload,  AP  density,  delay-­‐tolerance,  switching  threshold Strategies  compared  to  predicon-­‐based  offloading: WiFi  when  available Adapted-­‐Breadcrumbs:  Future  locaon  predicon  +  AP  locaon   database Oracle  (Impraccal):  Perfect  predicon  w/  future  knowledge 21Tuesday, April 12, 2011 21
  • 47. Wiffler  increases  data  offloaded  to  WiFi Workload:  Web  traces  obtained  from  commuters   22Tuesday, April 12, 2011 22
  • 48. Wiffler  increases  data  offloaded  to  WiFi Workload:  Web  traces  obtained  from  commuters   14% WiFi  when   available  yields   ligle  savings 22Tuesday, April 12, 2011 22
  • 49. Wiffler  increases  data  offloaded  to  WiFi Workload:  Web  traces  obtained  from  commuters   Wiffler  close  to   42% Oracle 14% 22Tuesday, April 12, 2011 22
  • 50. Wiffler  increases  data  offloaded  to  WiFi Workload:  Web  traces  obtained  from  commuters   Wiffler  close  to   42% Oracle Sophiscated   14% predicon  yields   negligible  benefit 22Tuesday, April 12, 2011 22
  • 51. Wiffler  increases  data  offloaded  to  WiFi Workload:  Web  traces  obtained  from  commuters   Wiffler  close  to   42% Oracle Sophiscated   14% predicon  yields   negligible  benefit Wiffler  increases  delay  by  10  seconds  over  Oracle.   22Tuesday, April 12, 2011 22
  • 52. Even  more  savings  in  urban  centers 23Tuesday, April 12, 2011 23
  • 53. Fast  switching  improves  quality  of   delay-­‐sensive  applicaons 24Tuesday, April 12, 2011 24
  • 54. Fast  switching  improves  quality  of   delay-­‐sensive  applicaons 58% 24Tuesday, April 12, 2011 24
  • 55. Fast  switching  improves  quality  of   delay-­‐sensive  applicaons 58% 40% 24Tuesday, April 12, 2011 24
  • 56. Fast  switching  improves  quality  of   delay-­‐sensive  applicaons 73% 58% 40% 24Tuesday, April 12, 2011 24
  • 57. Fast  switching  improves  quality  of   delay-­‐sensive  applicaons 73% 58% 40% 30%  data  offloaded  to  WiFi  with  40ms  switching  threshold 24Tuesday, April 12, 2011 24
  • 58. Future  work Reduce  energy  to  search  for  usable  WiFi Improve  performance/usage  by  predicng  user   accesses  to  prefetch  over  WiFi Incorporate  evolving  metrics  of  cost  for  3G  and   WiFi  usage 25Tuesday, April 12, 2011 25
  • 59. Summary Augmenng  3G  with  WiFi  can  reduce  pressure  on   cellular  spectrum Measurement  in  3  cies  confirms  WiFi  availability  and   performance  poorer,  but  potenally  useful Wiffler:  Predicon-­‐based  offloading  and  fast  switching   to  offload  without  hurng  applicaons 26Tuesday, April 12, 2011 26
  • 60. Summary Augmenng  3G  with  WiFi  can  reduce  pressure  on   cellular  spectrum Measurement  in  3  cies  confirms  WiFi  availability  and   performance  poorer,  but  potenally  useful Wiffler:  Predicon-­‐based  offloading  and  fast  switching   to  offload  without  hurng  applicaons Questions? 26Tuesday, April 12, 2011 26
  • 61. Thank you!Tuesday, April 12, 2011 27

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