CitySense: An Open, Urban-Scale Sensor Network Testbed

1. Josh Bers BBN Technologies Mobile Networking Systems Group Matt Welsh Harvard University Division of Engineering and Applied Sciences CitySense:An Open, Urban-Scale Sensor Network Testbed

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 • 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… Fixture Arm Power input Vaisala meterologicalsensor Mounting Straps WiFi Antennas

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 Iter#1: 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 Harvard’s 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 for“Internet 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@1decdec Device-type=VAISALA WXT510 Device-name=0 Timestamp=Mon Mar 26 22:15:10 EDT 2007 Sample Interval=-1 Query command=N/A • Measurement airPressure value=1016.3 unit=hPa • Measurement airTemperature value=6.3 unit=Celsius • Measurement relativeHumidity value=89.5 unit=PERCENT • Sensor data: net.citysense.sensors.WindSensorOutput@12a54f9 Device-type=VAISALA WXT510 Device-name=0 Timestamp=Mon Mar 26 22:15:14 EDT 2007 Sample Interval=-1 Query command=N/A • Measurement directionAvg value=294 unit=DEGREES • Measurement directionMax value=330 unit=DEGREES • Measurement directionMin value=278 unit=DEGREES • Measurement speedAvg value=0.9 unit=METERS_PER_SECOND • Measurement speedMax value=1.2 unit=METERS_PER_SECOND • Measurement speedMin value=0.6 unit=METERS_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 nodes:control/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@bbn.com) and Matt Welsh (mdw@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 BBN’s 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 CHIP’s 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.