tcp-friendly congestion control 2002.4.16 presented by hyunjoo kim
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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
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