enabling broadband data access for the digital watershed
TRANSCRIPT
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Enabling Broadband Data Access for the Digital Watershed with Heterogeneous Wireless Networks
Gayatri Venkatesh, Graduate Student, Electrical and Computer Engineering, Clemson UniversityK.-C. Wang, Assistant Professor, Electrical and Computer Engineering , Clemson University
Christopher Post, Assistant Professor, Forestry and Natural Resources , Clemson University
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A Broadband Network Connecting the Digital WatershedsChallenges Reside at the Edge – The Wireless Networks
In the Woods
AT&T Data
Coverage
Along the River
Over Woods & Hills
To
campus
In Woods & Ditches
To
campus
The Intelligent RiverTM
Cyberinfrastructure
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Challenges and Objectives
• Wireless networking challenges
• Foliage: Deep woods impede wireless communication range
• Remote: Lack of cellular coverage
• Terrains: Hills create absolute blockage for long distance links
• Costs: Cellular/satellite links incur recurring cost for limited bandwidth
• Our research objectives
• To develop a methodology for building wireless network infrastructure for current and future Intelligent RiverTM sites
• The solution will
• provide adequate and reliable bandwidth to all sensors
• economically scale to a large area
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Wireless around the Woods: State of the Art
• Great Duck Islands – UC Berkeley• Monitors bird nest microclimate• Wireless sensor “patches” + base station + satellite
• Redwood Macroscope – UC Berkeley• Monitors microclimate at different heights• Wireless sensor “chain” + base station (line of sight)
• Costa Rica Rainforest Station – UCLA• Monitors above-ground below-canopy climate• Wireless sensors + slide links between high towers
• Quail Ridge Reserve – UC Davis• Long range Wi-Fi + high towers with solar power
• HPWREN Res. and Edu. Network – UCSD• Very broadband wireless links over desert terrains
covering large parts of southern California
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Our Unique Challenges and Strategies• Diverse sensing site characteristics
• Challenge• Site characteristics change from river source to estuary
• Optimal solution cannot be one-size-fit-all
• Strategy• Study multiple technologies performance-cost tradeoff
• Pushing sensors “deeper” into the woods• Challenge
• Taming the forest rather than avoiding it
• Strategy• Quantify forest impact on wireless networks
• Exploring network reliability and controllability• Challenge
• Forest network condition changes over time
• Strategy• Identify control knobs for tuning forest wireless networks
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Background: Wireless Mesh Networks
• Wireless mesh networks are widely deployed today• Metropolitan mesh networks: Firetide, Motorola, Cisco, etc.
• Open/research mesh networks: MIT Roofnet, Houston TFA, Seattle wireless, etc.
• A wireless mesh network is composed of• Distributed base stations forming wireless network mesh covering a large area
• Distributed portable/mobile terminals connecting to a nearest base station
• Wireless mesh networks are known to• (+) Be a fast and economical solution for wide area coverage
• (+) Be a robust fault-tolerant solution for changing environments
• (!!) Have variable link rate at different location and time
• (!!) Need bandwidth provisioning to assure sufficient capacity
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A Forest Mesh Network Architecture
Long range transit link
In-forest mesh link
Sensor mesh linkInternet
Cyberinfrastructure
Fiber optic
network
Wireless sensor
Mesh router
Transit gateway
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Clemson Forest and Hunnicut Creek
• Two network testbeds for demonstration and characterization
1. Clemson Forest/Lake Issaqueena Reservoir
• Long range Wi-Fi (fixed direction): IEEE 802.11a & b/g
• Wi-Fi mesh network: IEEE 802.11b/g
• Zigbee sensor network: IEEE 802.15.4
2. Hunnicut Creek
• Long range Wi-Fi (steerable direction): IEEE 802.11b/g
• Wi-Fi mesh network: IEEE 802.11b/g
• Zigbee sensor network: IEEE 802.15.4
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Forest and Hunnicut Network Overview
325 m
240 m
160 m
325 m
240 m
160 m
4 miles
1 mile
4 miles
1 mile
Clemson Forest
Network
Hunnicut Creek
Network
sensor
cluster
transit
gateway
Internet
gateway
Long range Wi-Fi
over forest hill
• Cisco 1310
• IEEE 802.11b/g
• 2.4GHz band
• 21 dBi dish antenna
• Data rate: TBD
Long range Wi-Fi
over downtown
• Cisco 1410
• IEEE 802.11a
• 5GHz band
• 21 dBi dish antenna
• Data rate: 16 Mbps
Long range Wi-Fi
Steerable
• Fidelity Phocus
• IEEE 802.11b/g
• 2.4 GHz band
• steerable 22.5
• Data rate: 12 Mbps
Wi-Fi across woods
• Linksys WRT54G
• IEEE 802.11b/g
• 2.4 GHz band• Data rate: 2 Mbps
Wi-Fi into ditch
• Linksys WRT54G
• IEEE 802.11b/g
• 2.4 GHz band• Data rate: 5 Mbps
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Long Distance Transit Links
• Links must overcome distance, foliage, and hills
• Radio placement on high structure to get line-of-sight
• Directional antenna and power amplifiers
• Available control parameters
• Radio transmission power
• Antenna type (gain) and direction
• Layer 2 and 3 protocol parameters
Server side gatewayRelay gatewaysSensor side gateway
Forest
Mesh
NetworkIEEE
802.11b/g
IEEE
802.11a
Ethernet
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Clemson Forest Sensor Network• The Spring 2008 ECE 453
senior capstone project
• Undergraduate seniors
• inflow, outflow, temperature sensors
• Wireles sensors, relays, cellular modems
Zigbee
ZigbeeZigbee
Zigbee
Zigbee
Zigbee
ZigbeeZigbee
AT&T
cellular
Sensor
Cluster
Data
Outflow
pressure sensor
Inflow
aquarod
Temperature
sensor
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Broadband Forest Mesh Network
In Summer 2008• Evolved the senior project network to larger scope and bandwidth with
distributed sensor clusters and broadband mesh backbone• Evaluated control parameters: radio power, direction, foliage blockage
Sensor
Cluster
Sensor
Cluster
Sensor
Cluster
Sensor
Cluster
Sensor
Cluster
Lake
Issaqueena
Sensor
Cluster
Sensor
Cluster
Wi-Fi mesh
routers in forest
Wi-Fi linkZigbee link
* If router has steerable
directional antenna
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Steerable Directional Antenna Radio
• Potentially higher bandwidth at substantially longer distance
• Software controls radio to focus one direction at a time• Fidelity Comtech Phocus System (tested 15 miles line-of-sight range)• Potential use as 1) forest mesh routers and 2) long range gateways
• Current price is high as technology just released from military; expected future price reduction as it gain popularity
Sensor
Cluster
Sensor
Cluster
Sensor
Cluster
Sensor
Cluster
Sensor
Cluster1
2
3
4
5
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Measurement Studies of the Links
• Long range links: throughput v.s. direction and power
• Forest mesh links: throughput v.s. tree obstruction distance and power
• Steerable antenna links: throughput v.s. antenna alignment and power
• Study leveraged help from SC Governor School summer interns
• Study results published at ACM Wintech 2008 poster session
-90
-85
-80
-75
-70
-65
-60
-55
-50
-45
-40
-20 -10 0 10 20 30Horizontal Antenna Angle (Degrees)
Sig
na
l S
tren
gth
(d
Bm
)
0
4
8
12
16
20
Th
rou
gh
pu
t (M
bp
s)
Signal Strength Throughput
-80
-75
-70
-65
-60
-55
-50
12 14 16 18 20 22 24Transmit Power (dBm)
Receiv
ed
Sig
nal
Str
en
th (
dB
m)
0 45 90 135 1800
10
20
Th
ro
ug
hp
ut
(Mb
ps)
0 45 90 135 1800
20
40
60
Antenna Orientation (Degrees from Line-of-Sight)
SN
R (
dB
)
10 dBm 4 dBm 2 dBm 1 dBm
20 40 60 80 100 120 140 160 180 2000
5
10
15
Th
rou
gh
pu
t (M
bp
s)
20 40 60 80 100 120 140 160 180 200-100
-80
-60
-40
Router Distance (ft.)S
ign
al
Str
en
gth
(d
Bm
)
26mW 50mW 70mW
Long range link:
Throughput v.s.
signal strength v.s.
antenna direction
Long range link:
Signal strength v.s.
transmit power
Forest mesh link:
Throughput v.s.
signal strength v.s.
distance in forest
Steerable link:
Throughput v.s.
signal strength v.s.
antenna direction
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Summary
• Completed building Clemson Forest and Hunnicut networks
• Support sensor data reporting and video camera streaming
• Mesh routers ready for larger scale deployment
• Reliability and controllability are key concerns for a large scale sensing system
• Further measurement studies to develop forest wireless model for studying wireless network performance and design
• Further studies on assessment and control techniques for wireless network performance and reliability
• Further studies on large scale wireless network managementtechniques and software
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Can’t Do All This Without Them
Dan Schmiedt
CCIT Chief Network Engineer
Gayatri Venkatesh
ECE Grad StudentKnight Cox
Clemson Forest Manager
Sam, Forestry Grad Student
Larry, CCIT
Mike ECE Grad Student