Comparison of MaxNet and XCP: Network Congestion Control using explicit signalling
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Comparison of MaxNet and XCP: Network Congestion Control using explicit signalling Speaker: Bartek Wydrowski. Compiled from work by: Lachlan Andrew (2), Steven Low (1), Iven Mareels (2), Bartek Wydrowski (1) , Moshe Zukerman (2). (2). (1). Talk Overview. MaxNet & XCP Overview.

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Comparison of MaxNet and XCP: Network Congestion Control using explicit signallingSpeaker: Bartek Wydrowski

Compiled from work by: Lachlan Andrew (2), Steven Low (1),

Iven Mareels (2), Bartek Wydrowski (1), Moshe Zukerman (2).

(2)

(1)


Talk overview
Talk Overview using explicit signalling

  • MaxNet & XCP Overview.

  • Steady state: Rate allocation properties.

  • Summary of Maxnet and XCP.

  • Maxnet: A little more details

    • Stability.

    • Convergence Speed.


Network congestion control
Network Congestion Control using explicit signalling

L1

S1

D1

L2

S2

D2

L3

S3

D3

Sources transmit at a rate

controlled by a “congestion signal”

Links generate the congestion signal

based on level of congestion at link

Congestion level of end-to-end

path is fed back to source


Network congestion control1
Network Congestion Control using explicit signalling

Congestion signal on the Internet is implicit, and can be modelled as the sum of the end-to-end link congestion levels – this is where XCP, MaxNet differs.

S

p

p

p

i

1

2

N

Link 1

Link 2

Link N

Source

Destination

Link l drops packets at rate pl:

Link l ECN marks packets at rate pl:

Link l delays packets for time pl:

Link 1

Link 2

Link 1

Link 2

Link 1

Link 2

T1

T2


MaxNet: Overview using explicit signalling


MaxNet: Quick Overview using explicit signalling

  • MaxNet is:

  • A Fully distributed flow control architecture for large networks.

  • Max-Min fair in principle.

  • Stable for networks of arbitrary topology, number of users, capacity and delay.

  • Fast convergence properties.

  • Addresses short-flow control.

  • Philosophy:

  • Simple Architecture.

  • Ability to scale.

  • Simplicity  ability to design/predict.


MaxNet: Packet Format using explicit signalling

Packet

Data

CongestionSignal

N Bits

(price_k)


Maxnet source algorithm
MaxNet: Source Algorithm using explicit signalling

x– Transmission Rate

p - Price

Source Algorithm – Demand Function.

Each source can have a different demand function which determines the source’s relative need for capacity.

Xi = D(price_k)

Congestion Feedback from ACK k

Source rate

Source demand function


MaxNet: Packet Marking using explicit signalling

Source 1

Packet Signal = max(PacketSignal,p1(t))

Source 2

Packet Signal = max(PacketSignal ,p2(t))

Packet Signal = max(PacketSignal ,p3(t))

Signal =max(p2,p3)

Signal =max(p1,p2,p3)


Maxnet link algorithm
MaxNet: Link Algorithm using explicit signalling

Router Algorithm: Packet marking according to

Price_k = max ( Price_k , pl(t) )

Link price

updated at each control

interval, say every 10ms.

(single price for all flows on link)

Congestion signal

in pkt k

pl(t+1) = pl(t) + b(y(t)-aC)

Constant: convergence speed

Link capacity

Aggregate

input rate

Constant to control

Link utilization


Maxnet steady state properties
MaxNet: Steady State Properties using explicit signalling

S0

2 Mbps

D0

L1

3 Mbps

S1

D1

L2

2 Mbps

S2

D2

L3

S3

D3

q0 = p1 = max(p1)

q1 = p1 = max(p1,p2)

q2 =p1= max(p1,p2,p3)

q3 = p3= max(p2, p3)

p1

p2

p3

Mbps

S3

1.33

S0,S1,S2

0.66

q3

q0, q1, q2

Price


MaxNet: Steady State Properties using explicit signalling

Link 2 capacity

Link 2 capacity

3 Mbps

3 Mbps

1 Mbps

1 Mbps

T1

T2

T1

T2


XCP: Overview using explicit signalling


Xcp architecture
XCP Architecture using explicit signalling

XCP Packet Header

H_cwnd

H_rtt

H_feedback

Receiver

Sender

router

router

1. Initializes pkt k:

H_throughput_k

H_rtt_k

H_feedback_k

2. Each Router Computes Feedback:

H_feedback_k = min(H_feedback_k,H_lk)

Where H_lk = link l’s feedback for pkt k.

Thus, feedback from router with minimum ‘feedback signal’ is obtained from source to destination path.

3. Send header

back to sender

in ACK.


Xcp architecture1
XCP Architecture using explicit signalling

Source Algorithm:

  • Rate is governed by window

  • Source sends packet containing XCP header

  • Source receives feedback in ACK and adjusts window

Feedback from ACK

Change in source window

Source transmission rate


Xcp architecture2
XCP Architecture using explicit signalling

Router Algorithm: Feedback computed for each packet

H_feedback_k = min (H_feedback_k,H_feedback_i)

Round trip time of source i in packet

Feedback in Pkt

k header

Window of source i in packet

Mean of all RTTs

Packet size

Sum over control interval

Aggregate input rate

Link capacity

Queue


MaxNet, XCP: using explicit signalling Steady State Properties


Maxnet steady state properties1
MaxNet: Steady State Properties using explicit signalling

MaxNet is Max-Min fair for homogenous sources.

If all sources have the same demand function (homogenous),then MaxNet results in a max-min rate allocation.Max-min fairness maximises the minimum rate allocation,and maximizes each subsequently larger rate without reducingthe smaller rates.


MaxNet: Steady State Properties using explicit signalling

For general demand functions, MaxNet is weighted min-max fair. (Min-Max price fair)

Sources can prioritizetheir rate allocation bychanging their demandfunctions. Roughly speaking,their rate allocation will be in proportion to the magnitude

of the demand function.

Transmission rate

x1

x2

Link price


Xcp steady state properties
XCP: Steady State Properties using explicit signalling

  • Analysis to compute XCP equilibrium rates for arbitrary topology: Steven H. Low, Lachlan L. H. Andrew, Bartek P. Wydrowski, “Understanding XCP: Equilibrium and Fairness”.

    Rate allocation is a solution to a max-min problem with additional constraints

  • Effects of additional constraint:

    • Utilization can be below 100%.

    • Rates can be arbitrarily small fraction of max-min fair rates

    • In some topologies, residual terms are redundant.


Xcp steady state properties1
XCP: Steady State Properties using explicit signalling

  • Given a topology, our analysis can predict rate allocation.

  • Matches NS2 results very precisely

  • Predicts interesting pathological cases


Xcp steady state properties2
XCP: Steady State Properties using explicit signalling

  • Utilization of a link varies with number of sources bottlenecked at other links.

  • Lower and upper bound are:

  • ρl = fraction of flows at link l not bottlenecked at link l

  • l= fraction of traffic at link l not bottlenecked at link l

  •  = shuffling parameter  ,  = XCP parameters (conv speed,buffer)

  • With standard alpha and gamma parameters, utilization is at least 80%.


Xcp scenario 1
XCP Scenario 1 using explicit signalling

C1=155 Mbps C2=200 Mbps

Alpha = 0.4 Beta = 0.226 Gamma = 0.1


Xcp utilisation
XCP Utilisation using explicit signalling


Xcp scenario 11
XCP Scenario 1 using explicit signalling

Rate allocation can be arbitrarily smaller than max-minfair rates.

Eg: C1=155 Mbps C2=C1(n-1)/n

i=n^2-1 j=1

Alpha = 0.4 Beta = 0.226 Gamma = 0.1


Xcp max min fairness
XCP Max-Min Fairness using explicit signalling


Xcp stability counter example
XCP- Stability counter-example using explicit signalling

Sources

0..9

Sink

Source

10

200Mbps

1x = 50ms

5x = 250ms

10x = 500ms

100Mbps

50ms


Maxnet xcp comparison
MaxNet & XCP comparison using explicit signalling


Xcp maxnet research status
XCP & MaxNet Research status using explicit signalling


MaxNet: using explicit signalling Stability Properties


MaxNet Stability using explicit signalling

MaxNet is stable (local proven) over arbitrary network dimensions of:

Number of sources, links,hops, delay, capacity

Same properties as were shown for SumNet in:

F. Paganini, J.C. Doyle and S.H. Low, “Scalable laws for stable network congestion control,” in Proc. IEEE Conf. Decision Contr. (CDC), (Orlando, FL), 2001, pp. 185-90.


Network control model
Network Control Model using explicit signalling

L1

S1

D1

L2

S2

D2

L3

S3

D3

Physical Network

Control Model Network

Model quantities are small signal variations about equilibrium.

S1

Source Rate

x

Aggregate price

q

S2

S3

0

0

0

0

L1

0

L2

0

0

L3

0

Aggregate Rate

y

Link price

d


Network control model1
Network Control Model using explicit signalling

MaxNet open-loop transfer function.

S1

S2

S3

0

0

0

0

L1

0

L2

0

0

L3

0

Source Gain

Link Gain

Link Integrator

Action

Backward Routing Matrix

Forward Routing Matrix


MaxNet Stability Requirements using explicit signalling

x– Transmission Rate

p - Price

Source Gain

Constrains slope

Of source demand

function

Link Gain

Constrains speedof link control law

pl(t+1) = pl(t) + b(y(t)-aC)


MaxNet: using explicit signalling Convergence Properties


Maxnet convergence speed
MaxNet: Convergence Speed using explicit signalling

MaxNet has faster asymptotic convergence than the SumNet architecture.

(MaxNet is able to place the dominant pole further to the left than SumNet.)


Sumnet maxnet simulations
SumNet, MaxNet simulations using explicit signalling


Conclusion
Conclusion using explicit signalling

  • MaxNet steady state, stability and speed properties have been investigated.

  • XCP steady state properties were recently analyzed.

  • MaxNet offers (at least) steady state and implementation simplicity, advantages over XCP.


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