UNIVERSITY OF MASSACHUSETTS, AMHERST • Department of Computer Science
Anticipatory Wireless Bitrate Control for Blocks
Xiaozheng Tie, Anand Seetharam, Arun Venkataramani, Deepak Ganesan,
Dennis Goeckel
University of Massachusetts Amherst
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science 2
Wireless bitrate controlGoal: To optimize goodput by adapting effective sending rate to channel quality
Data packet
Channel feedback
6Mbps
1Mbps
2Mbps
Badchannel
Goodchannel
Goodchannel
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Blocks reduce overheadBlocks = Large batch of packets
E.g., 64KB MAC block in 802.11n1MB block in Hop transport [NSDI’09]
Packet
Ack
DIFSBackoff
SIFSXX
Packet transmission
DIFSBackoff
XX
Block transmission
SIFSTimeoutBackoff DIFS
Backoff
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science 4
Responsiveness vs. overhead 6Mbp
s
1Mbps
2Mbps
XXX
Block transmission Low responsiveness Low overhead
6Mbps6Mbps6Mbps6Mbps6Mbps6Mbps6Mbps
Packet bitrate control High responsiveness High overhead
Can we have both high responsiveness and low overhead?
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OutlineWhy anticipatory bitrate control BlockRate design and implementation EvaluationConclusion
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
Overhead vs. responsiveness (1)Overhead matters more in static settings
6
(Packet-based)(Block-based)(Block-based)
1.6x
[Mobisys’08]
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Overhead vs. responsiveness (2)Both overhead and responsiveness matter in mobile settings
30mphData
2x 6Mbps6Mbps6Mbps6Mbps
6Mbps6Mbps12Mbps12Mbps
12Mbps
Charm+Block Oracle+Block
1.7x
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OutlineWhy anticipatory bitrate control BlockRate design and implementation EvaluationConclusion
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Anticipatory bitrate controlAnticipatory = Selecting multiple bitrates predictive of future channel conditions.
Bitrate control for packets
6Mbps
Anticipatory bitrate control for blocks
6Mbps
12Mbps
Goodchannel
6Mbps
6Mbps6Mbps6Mbps
12Mbps12Mbps12Mbps
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Predict SNR trend: Slow-changingLinear regression model
Assumes SNR linearly varies with time in slow-changing scenarios
StaticPedestrian (1m/s)
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Predict SNR trend: Fast-changingPath loss model
Assumes SNR logarithmically varies with distance in fast-changing scenarios
30mphSNR(d)= SNR(d0) – 10αlog(d/d0)
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BlockRate design summary
30dB
40dB
6Mbps
6Mbps
12Mbps12Mbps
2. Lookup SNR-Bitrate table to select anticipatory bitrate
1. Predict future SNR based on mobility pattern
SNR Bitrate… …40dB 12Mbps… …
Linear regression
Path loss
Slow mobility
?YesNo
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SNR-Bitrate tableMaintains bitrate that maximizes goodput at each SNR
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OutlineWhy anticipatory bitrate controlBlockRate design and implementation EvaluationConclusion
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Experimental setupVehicular Pedestrian Static
V-to-V: 20 buses
V-to-AP: 2 cars
Mesh:16 MacMini nodes2 mobile laptops
ns3 simulation
Pedestrian
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Performance in V2V testbedBlockRate Charm+Block Charm SampleRate
#V2V contacts
1745 1822 1524 1719
1.3x
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Performance in V-to-AP testbed
30mph
Data
1.6x
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Performance in pedestrian mobility Pedestrian mobility trace-driven simulation in ns-3
(Uses PHY-hint) (Uses movement-hint)
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ConclusionState-of-the-art bitrate control schemes must pick one: low overhead or high responsiveness
BlockRate achieves both benefits Anticipatory bitrate control using blocks reduces overhead while being responsive
Thank you!