CitySense: An Open, Urban-Scale Sensor Network Testbed

1
CitySenseAn Open, Urban-Scale Sensor Network
Testbed

• Josh Bers
• BBN Technologies
• Mobile Networking Systems Group
• Matt Welsh
• Harvard University
• Division of Engineering and Applied Sciences

2
Sensor Network Testbeds

• Goal Support experimentation with wireless
  sensor networks at scale
• Simulations are valuable but inherently limited
• Understanding characteristics of real sensor
  networks in diverse environmentsrequires real
  testbeds and real applications
• Testbeds should be open and easily shared by
  multiple research groups
• CitySense Planned outdoor testbed of 100
  embedded PCs in Cambridge, MA
• Linux-based embedded PCs with meteorological and
  air quality sensors
• 802.11a/b/g interface with multihop wireless
  networking backbone
• Collaboration between BBN Technologies and
  Harvard University
• Funded by NSF under Computing Research
  Infrastructure program, 2006-2010

3
CitySense

• Joint effort between BBN Technologies and Harvard
  University (Prof. Matt Welsh, Co-PI)
• NSF Computing Research Infrastructure (CRI)
  program grant (4 years), Rita Rodriguez NSF
  Program Director.
• BBN taking lead on hardware design and deployment
  planning
• Harvard taking lead on software design and
  resource management
• Goal Deploy an outdoor, open wireless sensor
  network testbedacross the city of Cambridge, MA
• Nodes consist of Linux-based embedded PCs with
  802.11a/b/g
• Mounted on top of light poles with assistance
  from City of Cambridge
• Professional meterological sensor package for
  environmental monitoring
• Web-based interface for job scheduling,
  debugging, profiling
• Draw on experiences with MoteLab and extend to
  outdoor testbed
• Open resource for the sensor network community

4
CitySense Overview
5
CitySense Overview
Vaisala Mouting mast
Fixture Arm
Power input
Vaisala meterologicalsensor
Mounting Straps
WiFi Antennas

• Metrix embedded PC (Soekris single-board PC)
• Runs Pebble Linux distribution
• 133 Mhz AMD processor
• 64 MB RAM and flash, 1 GB USB flash drive
• Dual 802.11 a/b/g radios
• Multiple sensors possible weather, air quality,
  bio/chemagents, webcams, microphones

6
BBN Network Topology

• 3 Indoor nodes plus gateway
• 2 nodes on roof of buildings
• Racing
• Rosario
• Fully connected except for Gateway

7
Sensor Node Design Iter1 Racing
8
Why CitySense?

• Expand sensor networking testbeds beyond indoor
  deployments with resource-constrained nodes
• Outdoor testbed with large coverage area
• Powered nodes with substantial CPU/memory/radio
  bandwidth
• Provide blueprint for future sensor network
  designs and deployments
• Shared resource open to research community
• Leverage experience with Harvards MoteLab to
  provide shared experimental facility
• Provide bridge to broader scientific communities
• Partnership with Harvard School of Public Health
  urban air pollution study
• Educational impact at graduate, undergraduate,
  and K-12 levels
• Connection to NSF GENI initiative
• Shared facility for experimenting with sensor
  networks in realistic outdoor environment
• Opportunity for connection to evolving network
  standards and support forInternet scale sensor
  networking

9
CitySense sensor package

• Vaisala Weather Transmitter WXT510
• Wind speed and direction
• Precipitation
• Barometric pressure
• Temperature
• Relative humidity
• Well-calibrated sensors, robust packaging for
  outdoor environments
• Designed for precise measurement of
  environmentalconditions
• More accurate than typical component sensors used
  on motes
• Serial interface for configuration and data
  access

10
Example data

• Raw sensor ouput as received by our gateway via
  UDP packets multi-hopped from the sensor nodes
• Rain accumulation
• Wind Speed and Direction
• Pressure Temperature and Humidity
• Sensor Status Data
• Sensor data net.citysense.sensors.PTHSensorOutput
  _at_1decdec Device-typeVAISALA WXT510 Device-name0
  TimestampMon Mar 26 221510 EDT 2007 Sample
  Interval-1 Query commandN/A
• Measurement airPressure value1016.3
  unithPa
• Measurement airTemperature value6.3
  unitCelsius
• Measurement relativeHumidity value89.5
  unitPERCENT
• Sensor data net.citysense.sensors.WindSensorOutpu
  t_at_12a54f9 Device-typeVAISALA WXT510
  Device-name0 TimestampMon Mar 26 221514 EDT
  2007 Sample Interval-1 Query commandN/A
• Measurement directionAvg value294
  unitDEGREES
• Measurement directionMax value330
  unitDEGREES
• Measurement directionMin value278
  unitDEGREES
• Measurement speedAvg value0.9
  unitMETERS_PER_SECOND
• Measurement speedMax value1.2
  unitMETERS_PER_SECOND
• Measurement speedMin value0.6
  unitMETERS_PER_SECOND
• Go to http//citysense.bbn.com/ReadVaisala.pl
  for live data feed.

11
CitySense Networking

• Most CitySense nodes will not have wired network
  connectivity
• Several nodes (at BBN and Harvard) will act as
  gateways to the Internet.
• Must use wireless mutihop network for all
  communications to nodescontrol/management,
  debugging, application traffic
• Plan Use multihop routing network based on OLSR
• 100's of meters range between nodes possible with
  appropriate antennas
• Provide stable communications backplane with IP
  routing to individual nodes
• User applications may implement their own routing
  protocols directly on 802.11 MAC
• CitySense testbed will be timeshared across
  multiple users
• CPU, memory, and radio bandwidth must be shared
  across applications
• While not as limited as motes, this still raises
  some important resource management questions
• We expect demands on CitySense to vary widely
  across research groups.

12
CitySense Plug-and-Play Sensors
Sensor Description Document

• On-node software enables easy addition of new
  sensors
• Adaptation layer defines a common meta-data for
  sensors to declare themselves to the shared
  infrastructure
• Meta-data are used to allocate nodes to
  applications based upon their sensing
  requirements

maintains
Sensor Adaptation Layer (SAL)
Device Independent Control API
Sensor Adaptor
Vendor-specific sensor API
Sensor Hardware
Sensor Hardware
Sensor Hardware
Sensor Hardware
13
Open Challenges

• Remote maintenance and programming
• Physical access to nodes difficult or impossible
• Must ensure software can be updated safely
• Rollback to known-good safe mode if node loses
  network connectivity
• Resource management and sandboxing
• CitySense will be open to research community
• How to prevent naïve or malicious users from
  dominating resources?
• What are appropriate scheduling policies?
• Application programming model
• Should we allow arbitrary Linux binaries? Or
  require users to conform to constrained
  interface?
• What distributed services should the system
  provide to applications?
• Experimental support
• Time synchronization, GPS vs. NTP
• Distributed control separate channel for
  management plane vs. in band
• Some non-goals of this project
• Reinvent mesh networking try to leverage
  existing solutions
• Provide public Internet access too latency
  sensitive not appropriate for multihop mesh

14
GENI Wireless Research Enabled

• Characterize URBAN RF environment good urban
  propagation models do not exist
• Wireless Network Management
• Dynamic RF channel selection

15
Summary

• CitySense presents huge opportunityfor the
  sensor network community
• Develop, deploy, and experiment with sensor
  networks at scale in complex real-world outdoor
  urban environment
• Shared research facilities for supporting diverse
  research groups
• Planned 100-node outdoor testbed in Cambridge, MA
• Linux-based embedded PCs with 802.11 and
  professional weather sensor
• Planned future sensors include pollution/smog
  sensors.
• For more information
• Josh Bers (jbers_at_bbn.com) and Matt Welsh
  (mdw_at_eecs.harvard.edu)
• http//www.citysense.net

16
Related Work / Facilities

• WINLab, ORBIT Rutgers Raychaudhari
• ENL, USC motes Govindan
• sMote, Berkeley Culler
• RoofNET, MIT Morris, et. al
• U Colorado Sicker Grunwald
• Others
• Community networks
• CUWin, Corpus Christie, TEX, etc.

17
Acknowledgements

• BBN
• Abhimanyu Gosain, Tufts Intern
• Frank Bronzo
• Harvard
• Amal Fahad
• Jon Hyman
• Kevin Bombino
• Geoff Mainland
• Rohan Murty
• Matt Tierney

18
Current Status

• BBN Testbed
• 3 indoor nodes
• 2 outdoors with weather sensors
• Node Design
• 2 Prototype designs tested
• Working on City approval of streetlight mounted
  enclosure
• Wireless Network
• OLSR mesh active
• Characterized basic performance
• City Streetlight Mounting
• Received approval from City of Cambridge

19
Next Steps

• BBN Harvard Testbeds
• Grow size of each testbed to 10 nodes outdoors
• Link 2 networks via advantaged nodes
• Wireless Network
• Characterization
• Establish performance benchmark suite
• Management plane
• Test high-power, 700 mW, 900 MHz radios (ubiquiti
  networks)
• City Deployment
• First Nodes targeted for Summer-Fall 07

20
Preliminary Results Urban RF Activity

• From BBNs rooftop mounted nodes
• Total 5MHz Channels in use 29 out of 74
• 802.11b/g 11/14
• 802.11a lower 11/40, upper 7/20
• Total devices seen (distinct MAC addresses)
• in 15 days 205
• in 12 hours 25

21
Collaborators / Target Users

• Magid Ezzati Co-PI Harvard School of Public
  Health ? Urban pollution studies
• Ken Mandl Director of CHIPs program Childrens
  Hospital, Boston ? real-time tracking of ER
  symptom reports
• David Gute Tufts University EE department water
  quality sensors
• Tom Little BU EECS video sensors
• Chris Rogers Marina Bers Tufts EE Educational
  Outreach ? K-12 curriculum in sensor nets.