wb-rto: a window-based retransmission timeout ioannis psaras demokritos university of thrace,...

WB-RTO: A Window-Based Retransmission Timeout

Ioannis Psaras

Demokritos University of Thrace, Xanthi, Greece

COMputer NETworks Group (COMNET)

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Outline of the presentation

Contributions of this work The current Retransmission Timeout Algorithm Recent Related Work on the subject The proposed algorithm: WB-RTO

The algorithm Expected Behavior

Evaluation Plan Experimental Results


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Contributions of this work

Our perspective: When contention increases, the timeout becomes the scheduler for

the link.

Our observations: TCP-RTO should not be solely based on RTT estimations. Congestion events cause retransmission synchronization. Wireless burst errors should not be interpreted as congestion events.

Our solutions: Approximation of the current level of network contention Estimation of the contribution of each flow to congestion Allowance for asynchronous retransmissions when timeout happens.


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The current Retransmission Timeout Algorithm

Upon each ACK arrival, the sender: Calculates the RTT Variation:

Updates the expected RTT prior to calculating the timeout:

Calculates the Retransmission Timeout value:


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Recent Related Work on the subject Eifel RTO Algorithm

Uses the timestamp option to detect a spurious timeout. Forward RTO Algorithm

Uses the first 3 ACKs after the timeout to decide if the timeout was spurious or not.

Peak-Hopper RTO Algorithm Uses 2 timers: one is aggressive and one is conservative.

Each time it decides which one to follow. CA-RTO: A Contention-Adaptive RTO

Integrates a contention-adaptive parameter and introduces retransmission randomness.


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Window-Based RTO (1/4): Proportional Timeout

Estimation of the contribution of the flow to congestion:

c = f(cwnd , max cwnd ) Compare the current cwnd_ with the max_cwnd_:

If cwnd_ < max_cwnd_ / 2, c = 1: minimal charge

If max_cwnd_ / 2 < cwnd_ < (3/4)* max_cwnd_, c = 1,5: medium charge

If (3/4)* max_cwnd_ < cwnd_ < max_cwnd_, c = 2: major charge


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Window-Based RTO (2/4): Contention Estimation

Flow classification according to its cwnd_ history (awnd_):

ai = g(awnd , Thresholdi)where Thresholds 1 to 4 represent different levels of

network contention: Threshold 1 corresponds to very high contention, Threshold 4 corresponds to low contention.

3. 10 < awnd_ < 30: a3 = 34. 30 < awnd_ < 50: a4 = 2

1. awnd_ < 5: a1 = 102. 5 < awnd_ < 10: a2 = 5


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Window-Based RTO (3/4): Timeout Adjustment

Calculation of the Window-Based RTO:

WB − RTO = random(rtt, c × ai)or

WB − RTO = random(rtt, f(cwnd , max cwnd ) × g(awnd , Thresholdi))

1. rtt, avoids timeout expiration prior to the estimated RTT measurement

2. Parameter c captures the contribution of the flow to congestion

3. Parameter a approximates the current level of flow contention

4. Randomization guarantees asynchronous retransmission attempts


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Window-Based RTO (4/4): Expected Behavior

High penalties result in high timeout values.

As awnd_ increases timeout settles to smaller values.

but Large windows do not

always mean large timeout values.

WB-RTO vs awnd_


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Performance Evaluation Plan

WB-RTO is implemented in TCP-Reno Topologies used:

Evaluation Scenarios Simple Wired Scenario Interaction with Active Queue Management (i.e. RED) Satellite Environment Traffic Diversity (Mice with Elephants)


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An Important Note…

WB-RTO does not improve the Goodput performance of TCP significantly,

but here we focus on the Retransmission Timeout Algorithm of

TCP

hence we pay more attention on the combination of the

retransmission effort and the Goodput performance, rather than on the Goodput performance alone.


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Simple Wired Scenario (1)

Topology: Dumbbell Queuing Policy: DropTail DBP = Buffer Size = 10 pkts 5 participating flows 1500 sec total simulation time Flows ideal rate = 2 pkts/wnd We trace: Seqno progress, RTT,

RTO

TCP-RTO

WB-RTO


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Simple Wired Scenario (2)

For the TCP-RTO performance, we observe: RTT stabilization Similar timeout values 50% more retransmitted pkts Less Goodput RTT (in secs)

RTO (in secs)


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Interaction with AQM (i.e. RED) (1)

Topology: Dumbbell Queuing Policy: RED DBP = Buffer Size = 40 pkts min_thresh = 4 pkts max_thresh = 12 pkts 1500 sec total simulation time Goodput (in B/s)

Retransmitted PacketsNumber of Timeouts


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Interaction with AQM (i.e. RED) (2)

We observe: Similar Goodput Significant difference in

Retransmission Effort (50%) WB-RTO results in 66% less

timeout expirations TCP-RTO causes inefficient

queue utilization The average queue length

always overcomes the max_thresh, when using TCP-RTO

TCP-RTO

WB-RTO


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Satellite Scenario (1)

Topology: Cross-Traffic Bottleneck Queuing Policy: RED The rest of the buffers use DT bw_bottleneck = 20Mbps bw_delay = 300ms Buffer Size = 200 pkts min_thresh = 20 pkts max_thresh = 60 pkts 150 sec total simulation time PER = 0,0001 3 blackouts on the backbone link

No blackout

After 3 blackouts


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Satellite Scenario (2)

We observe that: TCP-RTO interprets the

second timeout as a congestion signal

WB-RTO does not extend the timeout, due to low contention and hence exploits bandwidth faster

TCP-RTO still waits for the extended timeout to occur,

while WB-RTO resumes

transmission immediately

TCP-RTO

WB-RTO


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Traffic Diversity (Mice and Elephants) (1)

Topology: Dumbbell Bottleneck Queuing Policy: RED bw_bottleneck = 10Mbps bw_delay = 30ms Buffer Size = 40 pkts

Goodput (KB/s)

Retransmitted PacketsGoodput per flow (KB/s)


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Traffic Diversity (Mice and Elephants) (2) We observe:

Simultaneous timeout events for TCP-RTO

All flows timeout during the Slow-Start

Flows 7-9 timeout simultaneously 10 times during the experiment

Short flows: 83 vs 50 timeouts Long flows: 43 vs 12 timeouts

We conclude that: most of the timeouts are

spurious WB-RTO achieves an

important goal: it reduces the number of timeouts

TCP-RTO

WB-RTO


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Conclusions RTT measurements cannot always reflect the level of network

contention TCP-RTO should not be solely based on RTT samples A contention-aware RTO proves to be more efficient, since it

is aware of current network conditions. A randomization factor in the RTO schedules retransmissions

in a fairer manner.


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WB-RTO: A Window-Based Retransmission Timeout

Thank you!!

Presented by Ioannis Psaras

e-mail: [email protected]

URL: utopia.duth.gr/~ipsaras

wb-rto: a window-based retransmission timeout ioannis psaras demokritos university of thrace,...

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