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 ID: 308454
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Congestion Control in Multi-hop Wireless Mesh Networks
Ihsan Ayyub QaziSlide2
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 Slide3
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 resourcesAllocate resources according to a fairness criteriaMax-Min fairnessallocation is max-min fair if no rates can be increased without decreasing an already smaller rateSlide4
Transmission Control Protocol (TCP)
Only
W
packets
may be outstanding
Rule for adjusting
WIf an ACK is received: W ← W+1/W
If a packet is lost: W ← W/24
ihsan@cs.pitt.eduSlide5
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.Slide6
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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TCP
Optimal
(Max Min)
What mechanisms can help us achieve near-optimal rates?Slide8
WCPCap
WCP
Approach
AIMD Based Design
Neighborhood-centric Transport
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Explicit Rate Notification Slide9
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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Link →
sender receiver pair
Prohibits channel capture
Prohibits channel capture at the sender or causes collision at the receiver
Ensuing ACK prohibits channel capture at the sender or causes collision at the receiverSlide10
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.,
r
f = rf / 2 React to congestion after RTT
neighborhood
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
r
f
= r
f + α Every RTTneighborhood
Additive Increase
Key Insight: Rate adaptation is clocked at the largest flow RTT in a neighborhood
RTT
neighborhood
: Largest flow RTT within the neighborhood11Slide12
Simulations: Stack Topology
WCP achieves near optimal performance
Through congestion sharing in the neighborhood
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Simulation setup
Qualnet
3.9.5
802.11b MAC with default parameters
TCP SACK
Auto rate adaptation is off Slide13
WCPCap
WCP
Approach
AIMD Based Design
Neighborhood-centric Transport
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Explicit Rate Notification Slide14
WCPCap: Explicit Rate Feedback
Estimate residual capacity
in a
neighborhood
Need to know the achievable rate region for
802.11-scheduled mesh networksUsing only local information
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Challenge: Is a given set of rates achievable in a neighborhood?Slide15
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 ≤ 115
Requires global information
Using only local information
Jindal et. al., “The Achievable Rate Region of 802.11 Scheduled Multi-hop Networks”.Slide16
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
U=1 (100% utilization) would yield large delays, we target U=0.7
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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
TCP
Optimal
WCPCap
WCPSlide18
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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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 range19Slide20
Experimental Results: Stack Topology
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Simulations
Experiments
For this topology, WCP’s simulation and experimental results are nearly identical
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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)Slide23
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 ratesSlide24
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 lengthAverage link layer retransmissionSlide25
Congestion Metrics
Available bandwidth
If estimation is made periodically, channel idle time represents network capacity still available during the estimation period
=time used by station itself+physical carrier sense time+virtual carrier sense timeSlide26
Congestion Metrics
Interface queue length
When input rate > output rate
queue builds up
Average link layer retransmissionSlide27
PerformanceSlide28
Packet drop rate and FairnessSlide29
Grid TopologySlide30
Thanks !