TCP Congestion Control Beyond Bandwidth-Delay Product for ...bleong/slides/conext17-proprate.pdf ·...
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TCP Congestion ControlBeyond Bandwidth-Delay Product for Mobile Cellular NetworksWai Kay Leong , Zixiao Wang, Ben Leong
The 13th International Conference on emerging Networking EXperiments and Technologies
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Mobile Internet usage exceeds Desktop
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What's different about cellular?Negligible random packet losses◦ Hybrid ARQ scheme◦ As compared to 802.11 Wi-Fi
Large buffers◦ In the Megabytes
Asymmetric uplink/downlink◦ ACK delay
Fair scheduling at “base station”◦ No contention with other users
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Why Traditional TCP does not workIN MOBILE/CELLULAR NETWORKS
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1. Large/Deep buffers
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Deep buffer causes high latency (hundreds of ms)
Cwnd
Time
Buffer overflow
Packets in flight (buffer)
Actual RTT
Lack of congestion signalCUBICReno
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2. Uplink CongestionMore predominant in slower 3G/HSPA networks
ACK gets delayed in return uplink◦ Stuck in deep buffer/ high volume of users◦ Server is prevented from sending new packet even though downlink is clear
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Data
ACK ……
Idle link
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Rethink congestion control for mobile networksTraditional TCP congestion control◦ Lack of congestion signal (ECN not popular)◦ Long delay/high latency (CUBIC)◦ ACK clocked
Rise in new mobile TCP algorithms◦ Sprout◦ Verus◦ PCC◦ BBR
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Key IdeaPurpose of congestion control is to ◦ avoid congestion◦ finding the correct rate to send packets ◦ ideally keep 1×BDP packets in transit
Why not just send at the correct rate?◦ Vary conditions of mobile networks◦ Try to forecast the condition (Sprout, PROTEUS, Verus, etc.)◦ Try to build a model (PCC, Remy)
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Our Insight:Timely estimation of the bandwidth
+ quick reaction to new network condition is sufficient
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Our ApproachAbandon ACK clocking
Pure rate-based sending of packets1. Estimate current bandwidth/receive rate2. Send packets at estimated rate3. Observe buffer delay4. Update send rate
Takes advantage of large buffer
Congestion with others mitigated by fair scheduling in base station
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We need a means to1. Estimate the bandwidth/receive rate
2. Detect congestion by measuring one-way delay
Make use of TCP timestamp option◦ Enabled by default on most servers and phones
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Estimating Receive RateReceiver will send ACK when packet is received
ACK will be timestamped
Compute rate by◦ comparing timestamps: tr1 – tr0 = Δt◦ and bytes ACK: ΔACK/Δt = ρ
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Sender Receiver
TSval = tr0
TSval = tr1
Δt
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Estimating Buffer/Queuing Delay
Only relative increase/decrease of tbuff matters
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Sender Receiver
TSval = tack
Relative delayRD = tack – tsnd
Actual delay
Queuing delaytbuff = RD – RDmin
tsnd
tack
(RDmin)
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Putting it together
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Estimate Receive Rate/Bandwidth
Detect Congestion from Queuing delay
Pure Rate-based Mechanism
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Self-oscillating feedback loop
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Increase in queuing delay
tbuff > TLink Congested
Decrease in queueing delaytbuff < T
No Congestion
Buffer Drain StateSend slower than
bandwidth(σd<ρ)
Buffer Fill StateSend faster than
bandwidth(σf>ρ)
Slow StartSend burst of
10 packets
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2 3
Estimatebandwidth (ρ)
ρ and tbuffconstantly updated
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BufferDrainState
Buffer FillState
Packet Trace, aka Sawtooth
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Time
Pack
ets i
n bu
ffer/
Que
uing
Del
ay
delay
delay
Takes at least 1×RTT to get feedback on queuing delay
Latency oscillates between the peaks and throughs
T
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PropRateSending rate is a proportion of bandwidth/receive rate◦σf = kf ρ◦σd = kd ρ
Three parameters controls the sawtooth◦ kf – proportion to fill buffer◦ kd – proportion to drain buffer◦T – threshold for switching state
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ParametersBy adjusting the parameters, kf , kd and T, we can change the shape of the sawtooth.
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Time
Pack
ets i
n bu
ffer/
Que
uing
Del
ay
T
Average latency
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ParametersBy adjusting the parameters, kf , kd and T, we can change the shape of the sawtooth.
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Time
Pack
ets i
n bu
ffer/
Que
uing
Del
ay
T
Average latency
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ParametersBy adjusting the parameters, kf , kd and T, we can change the shape of the sawtooth.
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Time
Pack
ets i
n bu
ffer/
Que
uing
Del
ay T
Average latency
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ParametersBy adjusting the parameters, kf , kd and T, we can change the shape of the sawtooth.
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Time
Pack
ets i
n bu
ffer/
Que
uing
Del
ay
T Average latency
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ParametersBy adjusting the parameters, kf , kd and T, we can change the shape of the sawtooth.
Throughput is maximum because buffer is always filled
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Time
Pack
ets i
n bu
ffer/
Que
uing
Del
ay
TAverage latency
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ParametersThroughput is maximum because buffer is always filled
Average latency can be adjusted
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Time
TAverage latency
Pack
ets i
n bu
ffer/
Que
uing
Del
ay
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ParametersThroughput is maximum because buffer is always filled
Average latency can be adjusted
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Time
T Average latency
Pack
ets i
n bu
ffer/
Que
uing
Del
ay
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Average latency
Two optimization modesOptimizing for Throughput◦ Buffer to be kept filled◦ Implies maximum throughput◦ Latency suffers due to queuing delay
Optimizing for Latency◦ Buffer needs to be emptied◦ Reduced utilization reduced
throughput◦ More responsive latencies
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T
Que
uing
Del
ay
Time
TTime
Average latency
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Please read our paperParameter tuning◦ Specify target latency to set the parameter
Updating Threshold ◦ Due to network volatility
Some math
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읽으십시오
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Evaluation
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Performance Evaluation1. Compare with other TCP
protocols◦ Traditional TCP: CUBIC, Vegas,
Westwood, LEDBAT◦ State-of-art Mobile: Sprout, PCC,
Verus, BBR
2. Delayed ACK/Saturated Uplink
3. Throughput vs Delay tradeoff
4. Fairness/Contention
5. Computation overhead
Two Scenarios1. Emulated networks
2. Real cellular networks
Three flavours of PropRateLow, Medium, High
+ FrontierEnumerate parameter space
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Trace-based EmulationKeep network constant – for fair comparison
Cellsim Emulator (from MIT)
Actual Network Traces◦ Three local cellular ISPs◦ Two scenarios: stationary (in our lab) and mobile (on a bus)◦ MIT traces [Winstein et al.]
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Mobile Cellsim Serverwired wired
uplinkdownlink
10100010010111001011
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Results – Local ISP, Stationary
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Good throughput/Bad latency
Good latency/Bad throughput
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Results – Local ISP, Mobile
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Good throughput/Bad latency
Good latency/Bad throughput
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Results – Real LTE Network
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ResultsPropRate more optimal than other TCP variants◦ Achieves higher throughput◦ or, lower latency
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Congested/Saturated Uplink
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Mobile ServerUSB Tether
congested uplinkdownlink
LTE
Smartphone
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Congested Uplink – Real LTE Network
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ResultsPropRate more optimal than other TCP variants◦ Achieves higher throughput◦ or, lower latency
Decoupling ACK clocking improves resilience◦ Towards asymmetric links
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Performance Frontiers
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ResultsPropRate more optimal than other TCP variants◦ Achieves higher throughput◦ or, lower latency
Decoupling ACK clocking improves resilience◦ Towards asymmetric links
Frontier hull shows PropRate is always most optimal
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Fairness – Self Contention
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Fairness – Contention from others
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ResultsPropRate more optimal than other TCP variants◦ Achieves higher throughput◦ or, lower latency
Decoupling ACK clocking improves resilience◦ Towards asymmetric links
Frontier hull shows PropRate is always most optimal
PropRate can compete with CUBIC flows
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Whither the future?Resurgence in interest in TCP◦ Different emergent networks: Datacenter, Wi-Fi, Cellular, etc.
Traditional TCP: CUBIC/Compound◦ Floods buffer Increased latency
Delay-based algorithms: Vegas, Westwood, etc.◦ Good latency◦ Starved by CUBIC
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Is TCP ready for rate-based algorithms?Pure rate-based algorithms: PropRate & BBR◦ Handles bufferbloat◦ Compete well against CUBIC
Can co-exist with CUBIC◦ Facilitate transition to better rate-based TCP algorithms
PropRate builds on a framework◦ More optimal algorithms in the future?◦ Better integration with TCP stack in the future?
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Thank YouQUESTIONS?
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감사합니다