measurement driven deployment of a two-tier urban mesh access...
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Measurement Driven Deployment of a Two-Tier Urban Mesh Access Network
J. Camp, J. Robinson, C. Steger, E. KnightlyRice Networks Group
MobiSys 20066/20/06
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Two-Tier Mesh Architecture
• Limited Gateway Nodes wired to Internet
• Mesh Nodes wirelessly forward bandwidth
• Backhaul Tier (Blue) - mesh node to mesh node
• Access Tier (Red) - mesh node to client node
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City-wide Two-tier Mesh: Houston RFP
• Three tiers of access: public service, Internet access, safety
• 620 square miles, Coverage:
• 95% Outside
• 90% Inside (window)
• $1 million startup capital downtown, $100 million total
• 18k mesh nodes, 3k gateways, Over 1 million end nodes!
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Technology For All/Rice Deployment
• TFA MISSION: “Empower low income communities through technology”
• Pilot neighborhood: Houston’s East End
• Per capita income 1/3 national average ($10k), 37% of children below poverty
• 64.2% of adults without GED
• 4.2 km2 covering 40,000 residents
• Education and work-at-home (“Learn-and-Earn” and Job-Tech)
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Outline
• TFA/Rice Background
• Objectives and Hardware
• Measurement Driven Deployment
• Single Hop Measurements
• Multihop Measurements
• Computational Placement Model
• Related Work
• Conclusion
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TFA Design Objectives
• Single wireline gateway (burstable to 100 Mb/sec)
• Coverage for entire 4 sq. km neighborhood (vs. only homes with mesh nodes)
• 1 Mb/sec minimum access rate
• $15k per square km
• Programmable platform for protocol design and measurement
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Off-the-Shelf Hardware• Mesh Node
• 802.11b, 200mW, Linux OS
• 1GHz x86, 4GB Flash
• 15 dBi antennas at 10 m (serve both access and backhaul)
• Client Node
• 802.11b, 200mW
• Engenius CB-3 Ethernet Bridge (like DSL/Cable modem)
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Methodology• Single Link Behavior = pathloss (ɑ), throughput as a f(SNR)
• Multihop Measurements = traffic matrices (β)
• Long-lived TCP flows, Static Rate Limited Flows, Web Traffic
• Placement Study = wire ratio (w), topology (regular grid, regular grid w/ perturbations, and random)
• Average mesh node throughput
• Network Reliability
ComputationalPlacement
Model
Single Link! & T(SNR)
Trafc Matrices"
Topology Generator(spacing, wire ratio)
Topology Information
(x, y)
Mesh PerformanceMetrics
Mesh Node Throughput(Average)
Mesh Node Reliability
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Single Hop Experiments
• Empirically measure importance of critical deployment factors
• Accurate understanding of propagation environment (pathloss)
• Accurate throughput to signal strength mapping
• Link Measurements
• Backhaul and Access* Links
* Not shown here, see results in paper
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Backhaul Link Measurements
• 235 Measurements (30 seconds)
• Concentrated measurements at distances > 175 meters
• Experiment Set-up
• 10 m height for fixed node
• 10 m height for portable node
• UDP traffic
• RTS/CTS enabled
• PHY layer autorate enabled
800 1000 1200 1400 1600 1800
600
700
800
900
1000
1100
1200
Pixels (Meters/1.9)
Pixe
ls (M
eter
s/1.
9)
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Throughput(SNR)
!100 !90 !80 !70 !60 !500
1000
2000
3000
4000
5000
6000
7000Slope = 240 kb/s/dBmX!Intercept = !86.4 dBm
Received Signal Strength (dBm)
UD
P Th
roug
hput
(kb/
s)
• Need to find throughput as a function of signal strength for model
• Manufacturer specification not sufficient (overly optimistic)
• Linear Approximation on logarithmic scale
• Target throughput for backhaul links 3 Mbps
• -75 dBm signal strength
• Access: -86 dBm for 1Mbps (DSL speeds)
ManufactureSpecification
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Pathloss
• Pathloss (α) = 3.3
• Theory - urban pathloss from 2 to 5
• Increased pathloss (access links 3.7)
• Increased height and better antenna
• Increased Shadowing, 5.9 where access links (4.1)
• 200-250 m range at -75 dBm for 3 Mbps
• Access: 150-200 m range at -86 dBm for 1 Mbps
0 100 200 300 400 500!100
!90
!80
!70
!60
!50
!40
!30
!20
!10
0
Distance (m)
Rec
eive
d Si
gnal
Pow
er (d
Bm)
Pathloss Exp = 3.2683Shadowing Std = 5.9427
MeasurementsFree SpaceMean+1 Stdev!1 Stdev+2 Stdev!2 Stdev
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Deployment Findings
• Accurate propagation measurements critical (theory says 2 to 5)
• Findings from placement model when we set internode spacing according to theory
• 2 yields completely disconnected network
• 3.5 yields overprovision factor of 55%
• 4 yields overprovision factor of 330%
• 5 yields 9 times overprovisioning (approx. $1 Billion vs. $100 million for Houston!)
• Accurate throughput-signal-strength function critical - manufacturers values overestimate link range 3X -> disconnected
• Requires only a few measurements
• 15 random measurements = std. dev. 3% about average
• 50 random measurements = std. dev. 1.5% about average
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• Issue: Spatial Bias
• Single Active Flow known
• Multiple active flow experiments measured
• Interflow and self-contention
• Experiments:
• Long-lived TCP Flows (Upload, Download*, Bidirectional*)
• Rate Limiting
• Web traffic* (download)
Multihop Experiments
* Not shown here, see results in paper
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TCP Long-lived Upload
• Upload experiences severe spatial bias
• Packet loss (from contention/collision)exacerbates effect
• RTS/CTS overhead outweighs fairness improvement for starved nodes
1 2 3 40
500
1000
1500
2000
2500
3000
Number of Hops from Gateway Node
Uplo
ad T
hrou
ghpu
t (kb
ps)
Concurrent Flows, RTS/CTS OffConcurrent Flows, RTS/CTS On
71%
58%
1%3%
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Rate Limiting
• Experiment: statically rate limit all nodes to the same rate (x-axis)
• Expect fair rate to be 1/9 (444 kbps) of effective capacity (4 Mbps)
• Result: 450 kbps has fair per-node throughput
• Upload still has spatial bias at 450 kbps
100 200 300 400 500 600 700 800 900 10000
100
200
300
400
500
600
700
800
900
1000
Static Rate Limit (kbps)
Down
load
Thr
ough
put (
kbps
)
1st Hop Node2nd Hop Node3rd Hop Node4th Hop Node
1234
567
89
Download
100 200 300 400 500 600 700 800 900 10000
100
200
300
400
500
600
700
800
900
1000
Static Rate Limit (kbps)
Uplo
ad T
hrou
ghpu
t (kb
ps)
1st Hop Node2nd Hop Node3rd Hop Node4th Hop Node
1234
567
89
Upload
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Multihop Measurement Findings
• Imperative to consider contending flows
• Single active flow measurements lead to large fraction of starving and disconnected nodes (comparing the β values yields avg. throughput per mesh node of twice actual -- 2x overestimation)
• Starvation in fully backlogged upload
• Compounding of MAC-induced loss & equal prioritization of intermediate node’s and forwarded traffic
• RTS/CTS overhead outweigh gains in starved nodes
• Proper limiting of flows alleviates starvation
• Web traffic allows statistical multiplexing to alleviate starvation (even without rate limiting)
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Placement Study
• Results
• Effect of Traffic Matrices
• Effect of Perturbations
• Reliability*
• Grid vs. Grid w/ Perturbations vs. Random*
• Case Study Network Deployment*
• Experimental Set-up
• Square (Manhattan) Grid, add perturbations
• Poisson placement for random topologies
* Not shown here, see results in paper
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Effect of Traffic Matrices
• Rate limited flows achieve approx. 1/2 of long-lived flows
• Unfair traffic pattern
• Web traffic able to achieve both high throughput and fairness
• Employing dynamic rate limiting w/ web traffic would be ideal
0 10 20 30 40 50 60 700
500
1000
1500
2000
2500
3000
3500
Node Density (nodes/km2)
Aver
age
Mes
h No
de T
hrou
ghpu
t
Parking Lot DownParking Lot UpRate Limited DownRate Limited UpWeb Emulation1/h Falloff
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Perturbations
• Increase in std. deviation as perturbation increase
• 6% increase in throughput up to 40 meters (1/6 of inter-node spacing)
• Not In My Backyard Scenario
• Uniform perturbation distribution
• 225 m spacing (grid)
0 10 20 30 40 50 60 70 801000
1100
1200
1300
1400
1500
1600
1700
1800
Average Perturbation (meters)
Aver
age
Mes
h No
de T
hrou
ghpu
t (kb
ps)
w=1/16
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Status of TFA Deployment
• 12 Nodes (Red) Deployed
• Approximately 2 square kilometers covered and growing
• 700+ users and rapidly growing
• New Devices (PDAs) and applications (health care)
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Related Work
• MIT Roofnet Measurements
• Strong line-of-sight component, Single Tier
• Single active multihop flows
• Philadelphia Wireless Spectrum Analysis
• Spectral scan of 49 points (135 mi.2)
• Signal strength measurements of access links
• Optimizing the Placement of iTAPs (Microsoft)
• Wired mesh node placement problem
• Analytical optimization formulation
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Conclusion
• Critical factors to consider in deploying mesh networks
• Accurate knowledge of propagation environment
• Accurate throughput-signal-strength function
• Traffic characterization must include concurrently contending multihop flows
• Rate Limiting to avoid starvation of multihop flows
• Placement Study to explore mesh deployment factors
• Random suitable for one-tier small scale but not large scale
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Future Work
• Management of TFA Network
• Traffic Management with QoS
• Dynamic rate allocation scheme to instill fairness
• Capacity Planning
• From Coverage Limited to Capacity Limited: The evolution of a mesh network
• Security, DDoS
• Mesh traffic force single point of failure, security is critical
• Rice TAPs/WARP Platform Collaboration
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Questions...?
Joseph [email protected]
www.ece.rice.edu/~camp
Rice Networks Groupwww.ece.rice.edu/networks
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Web Traffic
• Expect load to saturate at 30 users, where the first link becomes saturated
• 80 users - similar spatial bias to fully backlogged case
• Web traffic acts as singly active flows on small-scale of time
• On average, only one flow active up to 25 users
10 20 30 40 50 60 70 800
500
1000
1500
2000
2500
Number of Users Per Hop
Down
load
Thr
ough
put (
kbps
)
1st Hop Node2nd Hop Node3rd Hop Node4th Hop Node
Web-emulation script (C) - Two minute trials5 to 80 constant users on nodes B through E
Download 30 kB webpage, 7 second “think” time, exponentially distributedAssume gateway node is not the bottleneck