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Configurable restoration in overlay networks. Matthew Caesar, Takashi Suzuki. Motivation. Today’s internet core has bursty losses Backbones have low average loss rates (
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Configurable restoration in overlay networks
Matthew Caesar, Takashi Suzuki
MotivationToday’s internet core has bursty losses
Backbones have low average loss rates (<0.2%), but experience large bursts in loss
Loss durations vary from 10ms to 33.72sec 6 out of 7 providers experienced large outage periods 10-
220sec for 1-2 times per day
Difficult for multimedia applications to recover from repeated loss (e.g. with FEC)Commonly used restoration techniques insufficient
Link layer recovery, MPLS not yet uniformly deployed RON too slow (20 sec), not scalable
real-time recovery desired
“Assessment of VoIP Quality over Internet Backbones,” Markopoulou, Tobagi, Karam (INFOCOM 2002)
ApproachTechnique: Overlay based, real-time recovery
Use Link-state routing Determine link
cost from packet receipt delay
Adaptively dampen, localize route advertisements
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Link Cost Advertisements
Link Failure
Probe Packets
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Link Health Estimation
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Link Cost Advertisements
Link Failure
Probe Packets
text
Link Health Estimation
Link Cost Advertisements
Link Failure
Probe Packets
text
Link Failure
Probe Packets
text
Link Health Estimation
Desirable properties: Speed: Low end-to-
end failure time Stability: Few route
oscillations Accuracy: Avoid
reacting to transient failures
Scalability: Low probing/communication overhead
Layer 3
Layer 2
Layer 1
MeasureLink cost
AverageLink cost
UpdateLink cost
Incomingprobe packet
Calculateerror
counter
F()
G()
α
MIMD
Updatethreshold
Routingalgorithm
Phase 1: Detection MechanismGoal: Calculate link cost
Link Cost Estimation (LCE): Estimates failure
probability from packet loss
“Delay-deficit algorithm”
Adaptive Tracking (AT): Filters noise Reacts quickly to
changes
Route Stabilization (RS): Dampens route flaps
RS
AT
LCE
Phase 1: ExampleShow detailed actions of layers
Link Cost Estimation (LCE):
metric representing probability link has failed
spikes result from packet losses
Adaptive Tracking (AT): metric with noise filtered
Route Stabilization (RS): advertised value for link
Setup Link Failure at t=[150s-
170s] Probe every 300ms, 10%
loss
Results First Detection in 0.92s,
next at 5.42 A false positive due to
cold start. Stabilizes in 5 seconds.
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
0 10 20 30 40 50Time [seconds]
Lin
k co
st
Layer 1 (Sm)Layer 2 (Sav)Layer 3 (S)
LCE output
AT output
RS output
Phase 1: Comparison
Compared LCA, RON, and “Oracle-based” routing. Results:
RON requires 4 to 10x more advertisements than LCA
RON’s overhead increases exponentially with probe speed, LCA’s overhead increases linearly
Packet loss has an extreme effect on RON, moderate effect on LCA
LCA can achieve subsecond reactions on most internet links
Number of advertisements required to acheive desired loss rate (0% loss)
0
50
100
150
200
250
0 50 100 150 200
total packets dropped due to failure
tota
l # o
f req
uire
d ad
verti
sem
ents
RON 0%loss
RRAPID 0%loss
Number of advertisments required to acheive desired loss rate (5% loss)
0
1000
2000
3000
4000
5000
0 50 100 150 200 250 300
total packets dropped due to failure
tota
l # o
f req
uire
d ad
verti
sem
ents
RON 5%loss
RRAPID 5%loss
achieve desired
achieve
LCA
LCA
Phase 2: RoutingGoals:
Limit scope of link effects Configurable tradeoff between availability and overhead
Related work:
No existing scheme autonomously scopes dissemination with respect to links
Hierarchy (HIPR, HSR…)
Backbone-based (CEDAR, Span)
Flat no-coordination(LS, DV, DSR, DSDV, TORA, …)
Flat coordinated (AODV, FSR, ZRP)
LSA scoped based on link characteristics?
No Partially No No
Autonomous? No No Yes No
Phase 2: SolutionSolution idea: Autonomously localize LSA propagation
Unstable cost changes propagated locally
Stable changes propagated further
Application can control distance of propagation based on its requirements
Mechanism: Localized Reaction Global level propagates link
existence Local level propagates up to
date link state Create boundary around link Only nodes inside boundary
receive LSAs from link Dynamically resize the boundary
based on link characteristics
D
S
Phase 2: Simulation Results
Compared: Localized Reaction (LR)
Stability-sensitive LR (LRS)
Cost-sensitive LR (LRC) Random Hierarchies (RH)
Performance with heterogeneous link cost
0
0.2
0.4
0.6
0.8
1
1.2
0 0.5 1 1.5Average Path cost
Ov
erh
ea
d
RH
LR
LRC
Performance with heterogeneous link stability
0
5
10
15
20
25
30
0 0.5 1 1.5Average Path Cost
Ov
erh
ea
d
RH
LRS
Flooding smaller, more stable costs further improves performanceHowever, LR not appropriate for all environments
Works best for large, heterogeneous
Conclusions
1. Can achieve sub-second reactions on most links with reasonable stability Congested links increase reaction time Can react well on most internet links
2. Localization of route updates Scoping state dissemination with
respect to links improves performance in heterogeneous network
Can achieve resiliency close to link-state with fraction of overhead