R3: Robust Replication Routing in Wireless
Networks with Diverse Connectivity
Characteristics
Xiaozheng Tie, Arun Venkataramani,
Aruna Balasubramanian
University of Massachusetts Amherst
University of Washington
UNIVERSITY OF MASSACHUSETTS, AMHERST • Department of Computer Science
Wireless routing compartmentalized
Protocols designed for well-connected
meshes
OLSR, ETT, ETX, EDR, …
Research question:
Can
we design
a simple routing
protocol that
Protocols
designed
for intermittentlyensures
robustMANETs
performance across networks
connected
withAODV,
diverse
connectivity
DSDV,
DSR, … characteristics all the
way from well-connected meshes to mostlyProtocols designed
for sparselydisconnected
DTNs and everything
in between?
connected DTNs
DTLSR, RAPID, Prophet, Maxprop, EBR,
Random, …
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
2
Outline
Compartmentalized design harmful
Quantifying replication gain
R3 design and implementation
Evaluation
Conclusion
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
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Fragile performance
Protocols perform poorly outside target
environment
Normalized delay

Replication wasteful
2.1x
Mesh testbed
Mesh protocols perform
poorly in DTNs


Normalized delay
DTN protocols perform
poorly in mesh

No contemporaneous path
2.2x
DTN testbed
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
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Spatial connectivity diversity
DieselNet-Hybrid
Vehicular DTN + Wifi Mesh
20 buses in Vehicular DTN
4 open AP WiFi mesh clusters
< 100 contacts
100 – 200 contacts
> 200 contacts
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
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Temporal connectivity diversity
Haggle
Fraction of
connected nodes
Mobile ad hoc network
8 mobile and 1 stationary imotes
9 hour trace in Intel Cambridge Lab
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
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Compartmentalized design harmful
1. Fragile performance under spatiotemporal diversity
2. Makes interconnection of diverse
networks difficult
Makes management difficult
Conflates cross-layer concerns
Stifles long-term innovation
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
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Outline
Compartmentalized design harmful
Quantifying replication gain
R3 design and implementation
Evaluation
Conclusion
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
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Replication: Key difference
DTN
Sparsely connected
Replication
MANET
Intermittently connected
Mesh
Well connected
Forwarding
Key question: Under what conditions and by how much
replication improves performance?
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
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Model to quantify replication gain
X1
X2
Src
Dst
Xi


Random variable denoting
the delay of path i
Xn

• Expected delay of forwarding  minE[X1],E[X2 ],...,E[Xn ]

• Expected delay of replication (1)  E[min{ X1, X 2,...,X n }]

Replication gain


(1)
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
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Example of replication gain
X1
Src
Dst
X2

P(X1  0.1)  90%
P(X1 10) 10%
P(X 2  0.3)  90%
P(X 2  30) 10%
E(X1) 1
E(X 2 )  3
Replication
gain depends on path delay distributions,

not justdelay
expected
value

• Expected
of forwarding
  minE[X ],E[X ] min1,3 1
 1

• Expected delay of replication
Replication
gain

2
(1)  E[min{ X1, X 2}]  0.2

5
(1)
5x delay improvement
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
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Replication gain vs. number of paths
Trace-driven analysis on DieselNet-DTN
and Haggle
Two paths suffice to capture much of the gain
Vehicular DTN in DieselNet
Haggle
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
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Outline
Compartmentalized design harmful
Quantifying replication gain
R3 design and implementation
Evaluation
Conclusion
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
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R3 design overview
Link-state
Estimate per-link
delay distribution
Replication
Select replication
paths using model
Adapt replication to be

load-aware
Source routing along
selected path(s)
Dst
Src
Y1
Y3
Y2


UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
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Estimate link delay distribution
Link delay
Link availability delay
Delay to successfully
transfer packet
Node 2
Node 1
T=0
T=1
T=0: probe 0 unacked
T=1: probe 1 unacked
T=2: probe 2 acked at T=2.1
T=2
Delay = 2.1-0 = 2.1
Delay = 2.1-1 = 1.1
Delay = 2.1-2 = 0.1
Delay samples = {2.1, 1.1, 0.1}
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
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R3 design overview
Link-state
Estimate per-link
delay distribution
Src
Dst
Replication
Select replication
paths using model
Adapt replication to be
load-aware
Source routing along
selected path(s)
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
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Path selection using model
X1
X2
Src
Dst


First path

Xi
Xn
Path i s.t. E[X
 i ] is smallest
Selected using Dijkstra’s shortest path algorithm
Second path
Path
 j s.t. E[min{X i , X j }] is smallest

Selected using delay distributions and model
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
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Adapting replication to load
Problem
Replication hurts performance under high load
Solution
Load aware replication
actual_delay > t * model_estimated_delay
Start
Replication
Forwarding
actual_delay ≤ t * model_estimated_delay
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
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R3 design overview
Link-state
Estimate per-link
delay distribution
Src
Dst
Replication
Select replication
paths using model
Adapt replication to be
load-aware
Source routing along
selected path(s)
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
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Outline
Compartmentalized design harmful
Quantifying replication gain
R3 design and implementation
Evaluation
Deployment on a DTN and mesh testbed
Simulation based on real traces
Emulation using mesh testbed
Conclusion
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
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R3 Deployment
DieselNet DTN testbed
20 buses in a 150 sq. mile
area
Mesh testbed
16 nodes in one floor
Simulator validation using
DieselNet deployment
< 10% of deployment result
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
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R3 Trace-driven simulation
Experimental settings
Temporal diversity inherent in Haggle
Spatial diversity inherent in DieselNet-Hybrid
Varying load
Compared protocols
Replication: RAPID, Probabilistic
Forwarding: DTLSR, AODV, OLSR
Multi-configuration: SWITCH (RAPID+OLSR)
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
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Robustness to temporal diversity
Delay (min)
Goodput (pkt/min)
Simulation based on Haggle trace
Hour
Hour
R3 reduces delay by up to 60%
R3 increases goodput by up to 30%
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
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Robustness to spatial diversity
6
9
1
5
8
2
4
Delay (min)
Simulation based on DieselNet-Hybrid trace
3
7
Grid
R3 improves median delay by 2.1x
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
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Emulating intermediate connectivity
Mesh-based
emulation approach
R3 reduces delay by up to 2.2x
Delay (sec)
Brings link up and down
to vary connectivity
Emulates connectivity
diversity (but not
mobility)
Hour
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
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Conclusion
Compartmentalized design harmful
R3 ensures robust performance across
diverse connectivity characteristics
Unified link metric based on delay distributions
Replication based on delay uncertainty model
Adaptive replication based on network load
Thank you!
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
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UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
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Robustness to varying load
Simulation based on DieselNet-Hybrid trace
R3 reduces delay by up to 2.2x over SWITCH
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
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More paths in DieselNet-Hybrid
Average delay when R3 uses k=2, 3, 4, 5 replication paths.
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
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