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Multimedia and Mobile communications Laboratory Augmenting Mobile 3G Using WiFi Aruna Balasubramanian, Ratul Mahajan, Arun Venkataramani 2011-04-04 Jimin.

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Presentation on theme: "Multimedia and Mobile communications Laboratory Augmenting Mobile 3G Using WiFi Aruna Balasubramanian, Ratul Mahajan, Arun Venkataramani 2011-04-04 Jimin."— Presentation transcript:

1 Multimedia and Mobile communications Laboratory Augmenting Mobile 3G Using WiFi Aruna Balasubramanian, Ratul Mahajan, Arun Venkataramani 2011-04-04 Jimin Lee jmlee@mmlab.snu.ac.kr

2 2/23 Outline Introduction Measurement Wiffler  Prediction-based offloading  Fast switching Evaluation Conclusion

3 3/23 Introduction Mobile Internet access is suffering today  The ubiquitous deployment of cellular data networks has drawn millions of users  Mobile data is growing exponentially  This is creating immense pressure on the limited spectrum of networks  Is more spectrum the answer?

4 4/23 Measurement To study 3G and WiFi network characteristics  What is the availability of 3G and WiFi networks as seen by a vehicle user?  What are the performance characteristics of the two networks? Testbeds  Outdoor testbeds that include effects present in real vehicular settings such as noise, interference, traffic patterns  Conducted across three cities  Amherst, Seattle, Sfo  Vehicular nodes with 3G and WiFi radios  Amherst: 20 buses  Seattle: 1car  Sfo: 1car

5 5/23 Measurement Methodology  The vehicles visit many locations multiple times each day  Amherst : 12days, Seattle: 6days, Sfo: 3days  The software on the vehicle includes the two programs  First program scans the 3G and WiFi channels simultaneously  Second program sends and receives data to a server  Both server and vehicle log the characteristics of the data transfer

6 6/23 Measurement Availability  The server and the vehicle periodically send data to each other over UDP  An interface(3G or WiFi) is considered available if at least one packet was received in the interval  Availability is defined as the number of available 1-second intervals divided by the total number of intervals

7 7/23 Measurement Availability (cont’d)  WiFi availability is lower than 3G

8 8/23 Measurement Performance  To measure the upstream and downstream UDP throughput  The server and the vehicle send 1500-byte packets every 20ms.  WiFi throughput is lower than 3G

9 9/23 Measurement Summary  The availability of WiFi is poorer than 3G  WiFi throughput is also much lower than 3G throughput Augmenting 3G using WiFi  How can we reduce 3G usage by using WiFi?  The simplest policy  To send data on WiFi when available and switch 3G when WiFi is unavailable  First, Availability of WiFi can be low : 11%  Second, WiFi throughput is lower than 3G

10 10/23 Wiffler Key techniques  Leveraging delay tolerance  Exploit the delay tolerance of apps to increase data offloaded to WiFi  Fast switching  For apps with strict quality of service requirements  Such as VoIP and video stream

11 11/23 Leveraging delay tolerance The simplest solution  To wait until the delay tolerance threshold to transfer data on WiFi when available  It may significantly increase the completion time So, Wiffler uses the predictor to estimate offload capability of WiFi network

12 12/23 Leveraging delay tolerance (cont’d) Prediction-based offloading  Transfer required: S bytes by D seconds  D: earliest delay tolerance threshold among queued transfers  W: predicted WiFi capacity over future D seconds if(WiFi is available) Send data on WiFi If(W < S and 3G is available) Send data on 3G Parallel Operating

13 13/23 Leveraging delay tolerance (cont’d) WiFi throughput prediction  We predict WiFi offload capacity  Based on an estimate of the average throughput offered by an AP and a prediction of the number of APs that will be encountered  AP meetings occur in bursts  So, we can predict the number of AP encounters using a history- based predictor  Future AP encounters depend on recent past  The mobile node keeps track of the last N Aps  By using this information, we can compute the (# of APs) * (capacity per AP)

14 14/23 Fast switching to 3G Poor WiFi connectivity will hurt demanding apps  Such as VoIP, video streaming If WiFi is losing or delaying packets, we should send them on 3G as soon as possible  Link-layer retransmissions take much time  Variable medium access delays

15 15/23 Fast switching to 3G (cont’d) Motivation  Waiting for WiFi link-layer retransmissions incurs delay  Losses are bursty in the vehicular environment The simple mechanism  It sends the packet on 3G if the WiFi link-layer fails to deliver the packet within a delay threshold  It’s better to send time-sensitive packets on 3G rather than waiting for likely more failures on WiFi

16 16/23 Evaluation Deployment on 20 vehicular nodes Simulations

17 17/23 Evaluation Deployment on 20 vehicular nodes  Prediction-based offloading Data offloaded to WiFi Prediction-based offloading30% WiFi when available11% Transfer size: 5MB, Delay tolerance: 60 secs, Inter-transfer gap: random with mean 100 secs

18 18/23 Evaluation Deployment on 20 vehicular nodes  Fast switching to 3G Time w/ good voice quality Fast switching68% WiFi when available42% VoIP-like traffic: 20-byte packet every 20 ms With standard MOS metric

19 19/23 Evaluation Simulations  To evaluate Wiffler’s prediction-based offloading and fast switching from others  Alternative strategies  Impatient : use WiFi when available  Patient : waits until the threshold  Oracle : perfect future knowledge

20 20/23 Evaluation Wiffler increases data offloading to WiFi

21 21/23 Evaluation Prediction reduces completion time

22 22/23 Evaluation Fast switching improves performance of demanding apps

23 23/23 Conclusion Paper develops techniques to combine mutiple interfacees with different costs and ubiquitousness  3G is costly but more ubiquitous  WiFi is cheaper but intermittently available It overcomes WiFi’s poor availability by leveraging delay tolerance of applications and a fast switching mechanism


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