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
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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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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
Fragile performance under spatiotemporal diversity
Makes interconnection of diverse
networks difficult
Manageability
Separation of concerns
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


Xn

Random variable denoting
the delay of path i
• Delay of forwarding   min E[X1], E[X 2 ],..., E[X n ]

• 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
Src
X1
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,
• Delay of forwarding  min E[X1 ], E[X2 ] min 1,3  1
not just expected value

• Delay of replication
Replicationgain

(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
Delay to successfully transfer
pkt
Link availability delay
Time
20s
0.1s
10s
30s
Delay samples = {30.1s, 20.1s, 10.1s}
Estimate link delay using periodic probes
Unacked probe

Half of time since sending probe and
receiving an ack for subsequent probe
Acked probe

Half of round-trip 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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Path selection using model
X1
X2
Src
Dst


First path

Xi
Xn
Path i s.t. it minimizes E[X k ] k {1,2,...,n}

Selected using Dijkstra’s shortest path algorithm
Second path

Path j s.t. it minimizesE[min{ X i ,X k }] k {1,2,...,n}

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 > 2 * model_estimated_delay
Start
Replication
Forwarding
actual_delay ≤ 2 * 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, Random
Forwarding: DTLSR, AODV, OLSR
Multi-configuration: SWITCH (RAPID+OLSR)
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
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Robustness to spatial diversity
Simulation based on DieselNet-Hybrid trace
6
9
1
5
8
2
4
3
7
R3 improves median delay by 2.1x
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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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
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
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Q&A
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
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When is replication gain high?
Theorem: Replication gain is high iff path
delays are highly unpredictable
Predictability of a random variable X = Smallest 
such that P[X  E[X]] 1 

Corollary: Replication can yield unbounded gain even with

two paths
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
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Estimating path delay distribution
Y1
Y2
Yi
Yn
X

Link delay distribution

Path delay distribution


Path delay X  Y1 Y2  ...Yn
Expected delay: E[X]  E[Y1] E[Y2 ] ... E[Yn ]
Delay distribution of X : convolutions of


Y1,Y2,...,Yn
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
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Robustness to temporal diversity
Simulation based on Haggle trace
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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Emulating intermediate connectivity
Mesh-based
emulation approach
Brings link up and down
to vary connectivity
Emulates connectivity
diversity (but not
mobility)
R3 reduces delay by up to 2.2x
UNIVERSITY OF MASSACHUSETTS AMHERST • Department of Computer Science
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