Congestion Control in Multi-hop Wireless Mesh Networks

Ihsan Ayyub Qazi

Background: Congestion Control

• What is congestion?– A network state where the arrival rate exceeds the service

rate• Throughput starts decreasing (due to packet losses)• Delay increases fast (queues build up)

• Why does congestion occur?– No admission control

• Where does congestion control take?– At the end hosts– congestion inferred from end-system observed loss and delay

Goals of Congestion Control• Avoid congestion

– Avoid packet losses, keep delays low

• Efficient use of resources– Given some demand, resource must be utilizable

• Fair use of resources– Allocate resources according to a fairness criteria– Max-Min fairness

• allocation is max-min fair if no rates can be increased without decreasing an already smaller rate

Transmission Control Protocol (TCP)

Only W packets may be outstanding

Rule for adjusting W If an ACK is received: W ← W+1/W If a packet is lost: W ←

W/2

4ihsan@cs.pitt.edu

Understanding Congestion Control in Multi-hop Wireless Mesh Networks

Sumit Rangwala, Apoorva Jindal, Ki-Young Jang, Konstantinos Psounis and Ramesh Govindan (MobiCom’08)

Acknowledgement: following slides taken from Sumit Rangwala, USC.

Mesh Networks

• Static multi-hop mesh networks have been proposed as an alternative to wired connectivity

• User’s satisfaction hinges on transport performance– TCP’s performance on 802.11 mesh networks is

known to be poor • Starvation

Is poor transport performance inherent to multi-hop mesh networks?

Can a correctly designed transport help make mesh networks a viable alternative?

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TCP’s Performance

• TCP only signals flows traversing the congested link– Link centric view of congestion

• Fails to account for neighborhood congestion

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1Capacity Region with Optimal SchedulingAchievable Rate Region with 802.11

Rate of Each Outer Flow (Mbps)

Rate

of M

iddl

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ow (M

bps)

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TCP

Optimal(Max Min)

What mechanisms can help us achieve near-optimal rates?

WCPCapWCP

Approach

AIMD Based Design

Neighborhood-centric Transport

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Explicit Rate Notification

Neighborhood of a Link

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Neighbors (overhearing)

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• Neighborhood of a link – All incoming and outgoing links of

• Sender• Receiver• One hop neighbors of the sender • One hop neighbors of the receiver

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91

Link → sender receiver pair

Prohibits channel captureProhibits channel capture at the sender or causes collision at the

receiverEnsuing ACK prohibits channel capture at the sender or causes

collision at the receiver

WCP: AIMD Based Design

When a link is congested, signal all flows traversing the neighborhood of a link to reduce their rate by half, i.e.,

rf = rf / 2 React to congestion after RTTneighborhood

Multiplicative Decrease

Key Insight: Congestion is signaled to all flows traversing neighborhood of a congested link

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WCP

During no congestion increase a flow’s rate as rf = rf + α

Every RTTneighborhood

Additive Increase

Key Insight: Rate adaptation is clocked at the largest flow RTT in a neighborhood

RTTneighborhood : Largest flow RTT within the neighborhood

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Simulations: Stack Topology

• WCP achieves near optimal performance – Through congestion sharing in the neighborhood

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9TCP WCP Optimal

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• Simulation setup– Qualnet 3.9.5 – 802.11b MAC with default

parameters– TCP SACK– Auto rate adaptation is off

WCPCapWCP

Approach

AIMD Based Design

Neighborhood-centric Transport

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Explicit Rate Notification

WCPCap: Explicit Rate Feedback

• Estimate residual capacity in a neighborhood– Need to know the achievable rate region for

802.11-scheduled mesh networks• Using only local information

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Challenge: Is a given set of rates achievable in a neighborhood?

Combine, incorporating link dependencies, individual probabilities to find net collision and idle probabilities of the link Combine, incorporating local link dependencies, individual probabilities to find net collision and idle probabilities for the link

Calculating Achievable Rates

Decompose the neighborhood topology of a link into canonical two-link topologies

Find collision and idle time probability of the link in every two-link topology

Compute expected packet service time for a link from collision and idle probability of the link

Check feasibility, i.e., for each link, Packet arrival rate × E[service time of a packet] ≤ U,

0 ≤ U ≤ 1

15Requires global informationUsing only local information

Jindal et. al., “The Achievable Rate Region of 802.11 Scheduled Multi-hop Networks”.

WCPCap: Explicit Rate Feedback• Every epoch

– Find, by binary search, the largest increment or smallest decrement, δ, such that the new rates are achievable yet fair

– Increase/decrease rate of each flow by δ

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Utilization Factor (U)

Aver

age

End-

to-E

nd D

elay

(m

s)

U=1 (100% utilization) would yield large delays, we target U=0.7

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TCPW

CP

WCPCap

Optim

al0

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Simulations: Stack Topology

• WCPCap slightly better than WCP– Yields smaller queue and thus smaller delays– Not as good as optimal as we target 70% utilization

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• Simulation setup– Qualnet 3.9.5 – 802.11b MAC with default

parameters– TCP SACK– Auto rate adaptation is off

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10

0.1

0.2

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1Capacity Region with Optimal SchedulingAchievable Rate Region with 802.11

Rate of Each Outer Flow (Mbps)

Rate

of M

iddl

e Fl

ow (M

bps)

TCP

OptimalWCPCap

WCP

Simulations: Diamond Topology

• WCP does not achieve max-min rates– Rates are dependent on the number of congested neighborhood and the

degree of congestion• WCPCap achieves max-min rates

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CP

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Experimental Setup

• Mini-PCs running Click and Linux 2.6.20– ICOP eBox-3854

• 802.11b wireless cards running the madwifi driver

• Omni directional antennas– some antennas covered with

aluminum foils to reduce transmission range

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TCP WCP Optimal0

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8001→34→67→9

Goo

dput

(kb

its/

sec)

Experimental Results: Stack Topology1

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4 5 6

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TCPW

CP

Max-M

in Ach

ievab

le Rat

e0

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8001→34→67→9

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dput

(kb

its/

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Simulations ExperimentsFor this topology, WCP’s simulation and experimental results are nearly identical

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TCP WCP TCP WCPExperiment 1 Experiment 2

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put (

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Experimental Results: Arbitrary Topology

• 14 nodes and five flows• TCP starves different flows during different runs

WCP consistently gives fair rates

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WXCP: Explicit Congestion Control for Wireless Multi-hop Networks

Yang Su and Thomas Gross (IWQoS’05)

Motivation

• In wireless networks, physical capacity is not fixed– Varies with the number of contending nodes and

the traffic load in the neighborhood• CC Protocols (such as XCP) that rely on link

capacity estimate for computing feedback tend to overestimate capacity– Gives rise to unfairness and fluctuating rates

Contribution

• Proposes an extension to XCP for wireless networks– Estimates how much capacity a flow has for fair access

by locally monitoring channels conditions• Proposes three metrics for measuring the state of

resource usage and the level of congestion at a node– Available bandwidth– Interface queue length– Average link layer retransmission

Congestion Metrics

• Available bandwidth– If estimation is made periodically, channel idle

time represents network capacity still available during the estimation period

TbwT

B free.busyfree TTT

=time used by station itself+physical carrier sense time+virtual carrier sense time

rt

j

tts

Congestion Metrics

• Interface queue length– When input rate > output rate queue builds up

• Average link layer retransmission

avgifq RtryQnBT ..1..

QSd ...

Performance

Packet drop rate and Fairness

Grid Topology

Thanks !