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CA-RTO: A Contention-Adaptive Retransmission Timeout
I. Psaras, V. Tsaoussidis, L. MamatasDemokritos University of Thrace, Xanthi, Greece
This study was presented in the International Conference on Computer Communications and Networks (ICCCN 2005)
COMputer NETworks Group (COMNET) 2
Contributions of this work
Our perspective: When contention increases, the timeout becomes the scheduler for
the link
Our observations: When contention increases, timeout decreases! Congestion events cause synchronization, at least to some extend.
Our solutions: We integrate a contention adaptive parameter into the timeout
algorithm Unnecessary retransmissions are reduced
We introduce randomness to avoid synchronization
COMputer NETworks Group (COMNET) 3
Research Steps We investigated the timeout behavior towards various types of contention We observed that when contention increases, RTO undertakes the role of
the transmission scheduler for the link We focused on scenarios with high contention
RTT can not always capture efficiently the network conditions RTO is a bad scheduler for the link
We fixed the timeout value to correspond to different contention levels We concluded that different levels of contention call for distinct timeout
adjustments We ran simulation results
COMputer NETworks Group (COMNET) 4
TCP Retransmission Timeout
The timer is adaptive to varying delay The timeout is calculated every RTT Given a sample RTT measurement M and the history of
average RTT A, the distance from the average is measured:
Diff = M – A, the average is updated:
A = A + gDiff (where g=0.125), the RTT Deviation is calculated:
Dev = Dev +d(|Diff| – Dev) (where d = 0.25) and finally, the RTO value is adjusted to:
RTO = A + 4D
COMputer NETworks Group (COMNET) 5
Observations: Anomalies of the TCP
Retransmission Timer
SCENARIO Setup
Dumbbell Topology DropTail: 50 pkts BxD = 10 packets Contention Increase 0 – 250s: 1 flow 250 – 500s: 100 flows
COMputer NETworks Group (COMNET) 6
Contention Grows, Timeout Shrinks Contention Increase Scenario
RTT RTO = A + 4D
COMputer NETworks Group (COMNET) 7
Contention Grows, Timeout Shrinks
Contention Increase Scenario
RTO = A +4 D
COMputer NETworks Group (COMNET) 8
Contention Grows, Timeout Shrinks
`
Router Router’s Buffer
Some flows always find some empty space
Some flows always get rejected
√
Every arriving packet will occupy the last position, if it comes from the Lucky group of flows
X
COMputer NETworks Group (COMNET) 9
Contention Grows, Timeout Shrinks
In this case: 4D 0 Hence, RTO = A3. Timeout Decreases instead of Increasing (there is no
Deviation)4. Smoothed RTT (A) does not differentiate between
different flows5. Synchronization is possible (although buffers are always
full)6. Fairness is not guaranteed
COMputer NETworks Group (COMNET) 10
The Proposed Algorithm (CA-RTO)
CA-RTO: RTO = A + 4D + c*p We incorporate contention: c = 1/cwnd_ cont_diff_ = max_cwnd_ - cwnd_ cont_diff_ = cont_diff_ / 100 We introduce retransmission randomness: p = Random(0, cont_diff_) CA-RTO: RTO = A + 4D + c*p
COMputer NETworks Group (COMNET) 11
Behavior of theProposed Algorithm (CA-RTO)
The max_cwnd_ ever reached is 200pkts
Step 1: c = 1/cwnd_
Step 2:cont_diff_ = max_cwnd_ - cwnd_
cont_diff = cont_diff_/100
c = 1/cw nd_
0
0,02
0,04
0,06
0,08
0,1
0,12
10 20 30 40 50 60 70 80 90 100 150 200
Congestion Window
Par
amet
er c
c = 1/cwnd_
Contention Difference (max_cwnd_=200)
00,20,40,60,8
11,21,41,61,8
2
10 20 30 40 50 60 70 80 90 100 150 200
Congestion Window
con
t_d
iff_
COMputer NETworks Group (COMNET) 12
Behavior of theProposed Algorithm (CA-RTO)
Step 3:p = Random(0, cont_diff_)
Finally:
CA-RTO = RTO + c*p
Randomization Factor p (max_cwnd_=200)
0
0,5
1
1,5
2
10 20 30 40 50 60 70 80 90 100 150 200
Congestion Window
Par
amet
er p
Factor c*p (max_cwnd_=200)
00,020,040,060,08
0,1
0,120,140,160,18
0,2
10 20 30 40 50 60 70 80 90 100 150 200
Congestion Window
c*p
COMputer NETworks Group (COMNET) 13
Behavior of theProposed Algorithm (CA-RTO)
Contention Increase Scenario
CA-RTO = RTO + c*p
COMputer NETworks Group (COMNET) 14
Behavior of theProposed Algorithm (CA-RTO)Small congestion window: gives big value to parameter cc = 1/cwnd_
may result in big cont_diff_cont_diff_ = max_cwnd_ - cwnd_
Big congestion window: gives small value to parameter c results in small cont_diff_
We do not want to affect RTO’s performancein low contention scenaria
We try to capture high contention
We get aware of dynamic network conditions, e.g. contention increase
COMputer NETworks Group (COMNET) 15
Possible Further Enhancements The algorithm may “punish” flows with small windows by
extending their RTO value (e.g. during startup) maybe a parameter indicating the history of cwnd_ has to be integrated instead of the current cwnd_
The current mechanism used to capture contention may not be very accurate
The randomization factor used to split flows in time can be further improved
COMputer NETworks Group (COMNET) 16
Evaluation Methodology We target high contented links/networks We simulate large numbers of flows transmitting in low
capacity channels
Hence: Fair-share is small Flows are operating with small windows Buffers are always full
COMputer NETworks Group (COMNET) 17
Evaluation Methodology
We use the dumbbell network topology
Bandwidth x Delay = 10 or 100 packets
We use both DropTail and RED queuing policies
We implement CA-RTO in TCP-Reno and compare the two versions
We measure Goodput, Throughput, Fairness and Number of Retransmitted Packets
COMputer NETworks Group (COMNET) 18
Experimental ResultsScenario 1
B x D = 10 packets Buffer size = 50 packets, DropTail
Fairness Retransmitted Packets(up to 0.2 Index Points) (up to 4000 less retransmissions)
COMputer NETworks Group (COMNET) 19
Experimental ResultsScenario 1
Throughput (in Bps) Goodput (in Bps)
COMputer NETworks Group (COMNET) 20
Experimental ResultsScenario 2
B x D = 100 packets Buffer size = 100 packets, DropTail
Fairness Retransmitted Packets (at least 0.15 Index Points) (25 % less retransmissions, 4500pkts)
COMputer NETworks Group (COMNET) 21
Experimental ResultsScenario 3
bw_bb = 100Mbps, B x D = 250 pkts Buffer size = 100 packets, DropTail CA-RTO affects TCP’s performance only if needed…
Goodput
COMputer NETworks Group (COMNET) 22
Experimental ResultsScenario 4
B x D = 10 packets Buffer size = 50 packets, DropTail Packet Error Rate: 10%
Fairness Index Retransmitted Packets
COMputer NETworks Group (COMNET) 23
Conclusions Current RTO presents some behavioral anomalies
when contention increases A Contention-Adaptive RTO proves to be more
efficient in terms of successful retransmissions. That calls for further investigation of the energy potential of CA-RTO
A Randomization Factor in the RTO schedules the participating flows in a more fair manner