TCP-Friendly Congestion Control

2002.4.16

presented by Hyunjoo Kim

TCP-friendly SIMD Congestion Control and Its Convergence Behavior

Shudong Jin, Liang Guo, Ibrahim Matta, Acer Bestavros

Contents

Congestion control schemes AIMD Binomial algorithm TFRC TEAR

SIMD Experimental Results Conclusion

Congestion control

window-based schemes equation-based schemes

Requirements for Congestion control

TCP-compatibility TCP-friendliness Smoothness Aggressiveness Responsiveness Convergence

TCP-friendly congestion control schemes

AIMD binomial algorithms TFRC TEAR

Binomial algorithms

nonlinear congestion control algorithm for Internet transport protocols and applications

k+l rule trade-off between aggressiveness, congestion

responsiveness TCP-compatibility : k+l=1 and l1 converge to fairness as long as k0, l0, k+l>0

IIAD Inverse-Increase/Additive decrease k = 1, l = 0

TFRC

TCP-Friendly Rate Control Protocol equation-based congestion control sequence number for measuring RTT receiver

feedback message for sender to measure RTT calculate loss event rate

sender calculate a new value for the allowed sending

rate

TEAR

TCP emulation at receiver hybrid approach flow control for multimedia streaming TEAR emulates the TCP sender’s flow control functi

ons at receivers determine the appropriate receiving rates of receiv

ers based on congestion signals observed at the receiver (packet arrival, packet loss, timeout)

Sender sends data at reported rate

SIMD

Square-Increase/Multiplicative-Decrease TCP-like window-based congestion

control improve transient behavior using history self-clocking nature of window-based

scheme, and simple modification of TCP

Control rules

AIMD

Binomial algorithm

SIMD

SIMD control rule

.... (1) SIMD can grow aggressive with time

SIMD control rule

define as

(1) becomes ..... (2)

Increase rule is proportional to SIMD can be a special case of AIMD ( is always varying) high smoothness using small high aggressiveness when a sudden increase of available b.w. better convergence behavior

Synchronized feedback assumption

by (Chiu and Jain) all users sharing the same bottleneck will recei

ve the same feedback based on this feedback, the users try to adjust

their load for sharing efficiently, and equally synchronous feedback and control loop

Vector representation of a two-user case

Convergence of SIMD

fairness index : max (x1/x2, x2/x1) bring the system to the intersection of the fairness

line and the efficiency line

(a) AIMD trajectory (a) SIMD trajectory

SIMD < AIMD < IIAD in convergence time

Convergence Speed

(a) Increase Trajectory (b) AIMD vs SIMD (=1/16)

Simulation Results

TCP-friendliness TCP-Compatibility Convergence to Fairness and

Efficiency

TCP-friendliness Results

single flow, single fat link drop packets w.p. p

TCP-Compatibility Results

n SIMD flows, n standard TCP SACK flows 4 background TCP flows to introduce random ACK

delays

TCP competing with SIMD(1/16), RED with ECN

TCP-Compatibility Results

TCP competing with SIMD(1/16), RED without ECN

TCP-Compatibility Results

TCP competing with SIMD(1/16), RED with DropTail

Simulation topology for convergence test

Convergence to Fairness Results (W1+W2=W,

W1<W2)

Two flows converge to fair share of bandwidth

(a) TCP (b) AIMD(1/10, 1/16)

(c) IIAD (d) SIMD(1/16)

Convergence to Efficiency Results

(W1<W2<W/2)

Two flows converge to fair share of bandwidth

(a) TCP (b) AIMD(1/10, 1/16)

(c) IIAD (d) SIMD(1/16)

Conclusion

window-based congestion control algorithm, SIMD

history information in control rules multiplicative decrease, time square

increase in window size TCP-friendly, TCP-compatible under RED faster convergence than memory-less

algorithms

A Memory-Based Approach for a TCP-Friendly Traffic Conditioner in DiffServ Networks

K.R.R.Kumar, A.L.Ananda, LillyKutty Jacob

Contents

DiffServ Memory Based Marker (MBM) Experimental results Conclusion

DiffServ

by IETF DWG (DiffServ Working Group) scalable solution for providing service diff

erentiation among flows premium service assured service (AS)

target rate marking mechanism, queue management

RIO based scheme

RED with In/Out Active Queue Management (AQM)

at core router differentiated dropping of packets

during congestion in-profile, out-profile

Traffic Conditioner

marking the packets as in-profile, out-profile at edge router

Token-Bucket (TB) based avg. rate estimator based

(Time Sliding Window (TSW) profile meter)

TB-based marking

measuring the amount of data that flows generate in any time interval

not easy to decide the optimal value of bucket size

if small, avg. packet rate of in-profile < target rage

if large, unfairness in bandwidth sharing

TSW profile meters (TSW-TC)

two components rate estimator

avg. sending rate over time window (Tw) a marker

two approaches Tw is large

cannot reflect the traffic dynamics of TCP Tw RTT

avg rate of in-profile packet is much more than the target rate in the under-subscribed scenario

Memory based marker

Design issue which understands the TCP dynamics which helps in reducing the influence of RTT

and window size on TCP performance which reduce the burstiness of the marked/u

nmarked packes

MBM Marking algorithm

For each packet arrivalIf avg_rate cir then

mp = mp+(1-avg_rate/cir)+(par-avg_rate)/avg_rate;par = avg_rate;

mark the packet using:cp 11 w.p. mpcp 00 w,p. (1-mp)

else if avg_rate cir thenmp = mp+(par-avg_rate)/avg_rate;par = avg_rate;

mark the packet using:cp 11 w.p. mpcp 00 w.p. (1-mp)

Simulation Scenario

Assured service for aggregates

<Achieved Rates(Ra) for different Target Rates(Rt)>

2 sets of priority TCP flows(each having 6 micro flows) a set of 9 best effort TCP micro flows

Effect of different RTT

5 pairs of flow aggregates (6 micro flows) link bandwidth from R1 to R5 : 28Mbps

Effect of different window sizes

5 assured TCP flows having the same RTT (500ms) target rate of 3Mbps link bandwidth from R1 to R5 : 18 Mbps optimum window size : 125 KB

Protection from best effort UDP flows

a set of priority TCP flows, a set of BE UDP and TCP flows link bandwidth : 10 Mbps

Effect of UDP flows with target rates

a set of priority TCP, AS UDP flow with a target rate of 3 Mbps

Conclusion

memory-based approach in providing better quality of service for TCP flows

simplicity least sensitivity to TCP and marker

parameters MBM helps in achieving target rate with a

better fairness better result using TCP extensions such

as SACK

References

Shudong Jin, Liang Guo, Ibrahim Matta, Azer Bestavros, “TCP-friendly SIMD Congestion Control and Its Convergence Behavior”

K.R.R.Kumar, A.L.Ananda, Lillykutty Jacob, “A Memory-based Approach for a TCP-Friendly Traffic Conditioner in DiffServ Networks”

D.Bansal and H.Balakrishnan, “Binomial congestion control algorithms”, In Proceedings of IEEE INFOCOM, April 2001

S.Floyd, M.Handley, J.Padhye, J.Widmer, “Equation-based congestion control for unicast applications”, in Proceedings of ACM SIGCOMM, Aug 2000

I.Rhee, V.Ozdemir, Y.Yi., “TEAR: TCP Emulation at Receivers – flow control for multimedia streaming”, Technical report, Dept. of Computer Science, North Carolina State Univ. Apr. 2000

S.Blake, D.L.Black, M.Carlson, E.Davies, Z.Wang, and W.Weiss, “An architecture for differentiated services”, RFC 2475, Dec. 1998