Energy-Efficient Congestion Control

Opportunistically reduce link capacity to save energy

Lingwen Gan1, Anwar Walid2, Steven Low1

1Caltech, 2Bell Labs

Improve network efficiency by 1000 times!

Network links consumea lot of electricity

Electricity consumptionof network links > Electricity consumption

of the United Kingdom

Fiber optics, copper cable

0%6%

12%

yearly growth rate

Reduce electricity consumption of network links.

Exploit low link utilization

What we do: dynamically manage link capacity.

on average off-peak0%5%

10%15%20%25%30%35%40%

link utilization

Technologies to change link capacity

Link bundle

Sleep mode [Gupta’03]

Voltage and frequency speed scaling [Pillai’01]

component linkto sleep

Link bundle

router router... 2~20

Linear power consumption

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 50

0.51

1.52

2.53

3.54

4.55

Identical component links

# active component links

Power consumption(units)

energy saving reduced capacity

Outline

• Challenge• Goals• Algorithm• Simulations

Challenge: interaction with TCP

Reduce traffic throughput

TCP reacts

capacity

congestionthroughput

Adjust capacity slowly.

Adjust capacity fast, but TCP friendly.Packet time scale. [Francini’10]…Flow time scale.

• Fast response• Small overhead

Routing time scale. [He’06] [Fisher’10]

Two approaches

This work

Goals

Dynamic Bandwidth Adjustment (DBA) Algorithm, such that

1) Operate at flow time scale.

2) Do not reduce throughput.

3) Save as much energy as possible.

4) Throughput does not oscillate---stability.

Recall TCP

at steady state

transmissionrate

packet loss probability

TCP

packet lossprobability

transmission rate

Recall Random Early Discard (RED)link

incoming traffic link capacity

buffer size

buffer size

packet drop probability

Recall network solves NUM

Transmission rates

Throughput on the links

Ideal throughputIdeal capacity

Thm [Kelly’98, Low’99]: The network model

solves the Network Utility Maximization problem:

Bottleneck & non-bottleneck links

buffer size

packet drop probability

Bottleneck link:

Non-bottleneck link:

buffer size

packet drop probability

• Do not reduce capacity

• Reduce capacity• Keep 0 packet drop

Keep the buffer at the “right” place

buffer size

packet drop probability

targetbuffer

DBA Algorithm (for each link)

1. Pick a target delay satisfying

2. At any time, set target buffer size

current buffer sizecapacity

and update capacity as

zero throughput reduction &maximum energy saving

Thm: Network under DBA algorithm, modeled by

converges to (original) target throughput(zero throughput reduction)

with minimum energy consumption

(maximum energy saving)

Current networkarchitecture

Model network delay

Global stability

TCP sources Links

?

transmission rate

packet loss

incoming traffic

packet drop

No network delay With network delay

delay

Local stability under network delayThm: Network (with DBA)

is locally asymptotically stable,

provided some mild conditions hold.

in the presence of network delay modeled as

Goals

Dynamic Bandwidth Adjustment (DBA) Algorithm, such that

1) Operate at flow time scale.

2) Do not reduce throughput.

3) Save as much energy as possible.

4) Throughput does not oscillate---stability.

✔✔✔✔

Standardsimplifying assumptions

ns2 simulation to verify.

ns2 is a standard and accurate simulation software.

Simulation setup

Node 1

Node 2

1Mb/s

1Mb/s

1Mb/s

1Mb/s

TCP Source 1

TCP Source 20

TCP sink 1

TCP sink 20Compare two configurations• static: 50Mb/s• DBA: 5~50Mb/s

20 additional TCP flows come and go abruptly.

time (s)

Thro

ughp

ut (M

b/s)

staticDBA

Zero throughput reduction

TCP flowscome

TCP flowsgo

Initial dip

Fast recovery

Throughput doesnot oscillate.

throughputpreservation

instantincrease

throughputpreservation

throughputpreservation

capa

city

(Mb/

s)

time (s)

staticDBA

Maximum energy saving

TCP flowscome

TCP flowsgo

capacity rampsup fast

capacity rampsdown slowly

same asthroughput

same as throughput

same as throughput

short transient

Network link is lightly utilized, can reduce capacity to save energy.

Stability: locally asymptotically stable.

Optimality: zero throughput reduction, maximum energy saving.

Concluding remarks

Verified by ns2 simulations.

Propose DBA to adjust link capacity in TCP flow time scale.

Thank you!