Article

CarTel: a distributed mobile sensor computing system

Authors:

Vladimir Bychkovsky,

Michel Goraczko,

Hari Balakrishnan,

Samuel MaddenAuthors Info & Claims

SenSys '06: Proceedings of the 4th international conference on Embedded networked sensor systems

Pages 125 - 138

https://doi.org/10.1145/1182807.1182821

Published: 31 October 2006 Publication History

Abstract

CarTel is a mobile sensor computing system designed to collect, process, deliver, and visualize data from sensors located on mobile units such as automobiles. A CarTel node is a mobile embedded computer coupled to a set of sensors. Each node gathers and processes sensor readings locally before delivering them to a central portal, where the data is stored in a database for further analysis and visualization. In the automotive context, a variety of on-board and external sensors collect data as users drive.CarTel provides a simple query-oriented programming interface, handles large amounts of heterogeneous data from sensors, and handles intermittent and variable network connectivity. CarTel nodes rely primarily on opportunistic wireless (e.g., Wi-Fi, Bluetooth) connectivity to the Internet, or to "data mules" such as other CarTel nodes, mobile phone flash memories, or USB keys-to communicate with the portal. CarTel applications run on the portal, using a delay-tolerant continuous query processor, ICEDB, to specify how the mobile nodes should summarize, filter, and dynamically prioritize data. The portal and the mobile nodes use a delay-tolerant network stack, CafNet, to communicat.CarTel has been deployed on six cars, running on a small scale in Boston and Seattle for over a year. It has been used to analyze commute times, analyze metropolitan Wi-Fi deployments, and for automotive diagnostics.

References

[1]

Dash Navigation Inc. home page. http://www.dash.net/.]]

[2]

D.J. Abadi, Y. Ahmad, M. Balazinska, U. Cetintemel, M. Cherniack, J.-H. Hwang, W. Lindner, A. Maskey, N. Tatbul, Y. Xing, and S. Zdonik. Design issues for second generation stream processing engines. In Proc. of the Conference for Innovative Database Research (CIDR), Asilomar, CA, Jan. 2005.]]

[3]

R. Adler, P. Buonadonna, J. Chhabra, M. Flanigan, L. Krishnamurthy, N. Kushalnagar, L. Nachman, and M. Yarvis. Design and Deployment of Industrial Sensor Networks: Experiences from the North Sea and a Semiconductor Plant. In ACM SenSys, 2005.]]

Digital Library

[4]

L. Amsaleg, M.J. Franklin, A. Tomasic, and T. Urhan. Scrambling query plans to cope with unexpected delays. In PDIS, pages 208--219, 1996.]]

Digital Library

[5]

N. Bansal and Z. Liu. Capacity, delay and mobility in wireless ad-hoc networks. In INFOCOM, 2003.]]

[6]

D. Barbara and T. Imielinski. Sleepers and workaholics: caching strategies in mobile environments. In SIGMOD, pages 1--12, 1994.]]

Digital Library

[7]

T. Brooke and J. Burrell. From ethnography to design in a vineyard. In Proceeedings of the Design User Experiences (DUX) Conference, June 2003.]]

Digital Library

[8]

V. Bychkovsky, B. Hull, A.K. Miu, H. Balakrishnan, and S. Madden. A Measurement Study of Vehicular Internet Access Using In Situ Wi-Fi Networks. In 12th ACM MOBICOM Conf., Los Angeles, CA, September 2006.]]

Digital Library

[9]

D. Carney, U. Centiemel, M. Cherniack, C. Convey, S. Lee, G. Seidman, M. Stonebraker, N. Tatbul, and S. Zdonik. Monitoring Streams-A New Class of Data Management Applications. In VLDB, 2002.]]

[10]

V. Cerf, S. Burleigh, A. Hooke, L. Torgerson, R. Durst, K. Scott, E. Travis, and H. Weiss. Interplanetary Internet (IPN): Architectural Definition. http://www.ipnsig.org/reports/memo-ipnrg-arch-00.pdf.]]

[11]

A. Cerpa, J. Elson, D.Estrin, L. Girod, M. Hamilton, and J. Zhao. Habitat monitoring: Application driver for wireless communications technology. In ACM SIGCOMM Workshop on Data Comm. in Latin America and the Caribbean, 2001.]]

Digital Library

[12]

Code of Federal Regulations. Title 40 Section 86 Subsection AA Appendix I.]]

[13]

S. Chandrasekaran, O. Cooper, A. Deshpande, M.J. Franklin, J.M. Hellerstein, W. Hong, S. Krishnamurthy, S.R. Madden, V. Raman, F. Reiss, and M.A. Shah. TelegraphCQ: Continuous dataflow processing for an uncertain world. In CIDR, 2003.]]

[14]

M. Cherniack, M. Franklin, and S. Zdonik. Expressing User Profiles for Data Recharging. IEEE Personal Communications, pages 32--38, Aug. 2001.]]

[15]

D. Clark and D. Tennenhouse. Architectural Considerations for a New Generation of Protocols. In ACM SIGCOMM, pages 200--208, 1990.]]

Digital Library

[16]

Emission Test Cycles: SFTP-US06. http://www.ietf.org/internet-drafts/draft-coene-sctp-multihome-04.txt, Apr. 2004.]]

[17]

M.D. Dikaiakos, S. Iqbal, T. Nadeem, and L. Iftode. VITP: an information transfer protocol for vehicular computing. In Workshop on Vehicular Ad Hoc Networks, pages 30--39, 2005.]]

Digital Library

[18]

S.C. Ergen, S.Y. Cheung, P. Varaiya, R. Kavaler, and A. Haoui. Wireless sensor networks for traffic monitoring (demo). In IPSN, 2005.]]

[19]

K. Fall. A delay-tolerant network architecture for challenged internets. In Proc. ACM SIGCOMM, pages 27--34, 2003.]]

Digital Library

[20]

M. Ghanem, Y. Guo, J. Hassard, M. Osmond, and M. Richards. Sensor Grids for Air Pollution Monitoring. In Proc. 3rd UK e-Science All Hands Meeting, Nottingham, UK, Sept. 2004.]]

[21]

Google Maps API. http://www.google.com/apis/maps/.]]

[22]

D. Goodman, J. Borras, N. Mandayam, and R. Yates. Infostations: A new system model for data and messaging services. In Proc. IEEE Vehicular Technology Conference, pages 969--973, May 1997.]]

[23]

K. Harras and K. Almeroth. Transport layer issues in delay tolerant mobile networks. In IFIP Networking, May 2006.]]

Digital Library

[24]

M. Ho and K. Fall. Poster: Delay tolerant networking for sensor networks. In SECON, October 2004.]]

[25]

E. Horvitz, J. Apacible, R. Sarin, and L. Liao. Prediction, expectation, and surprise: Methods, designs, and study of a deployed traffic forecasting service. In Twenty-First Conference on Uncertainty in Artificial Intelligence, July 2005.]]

[26]

Inrix home page. http://www.inrix.com/.]]

[27]

C. Intanagonwiwat, R. Govindan, and D. Estrin. Directed Diffusion: A Scalable and Robust Communication Paradigm for Sensor Networks. In MOBICOM, 2000.]]

Digital Library

[28]

S. Jain, R.C. Shah, G. Borriello, W. Brunette, and S. Roy. Exploiting mobility for energy efficient data collection in sensor networks. In WiOpt, March 2004.]]

[29]

D. Jea, A.A. Somasundara, and M.B. Srivastava. Multiple controlled mobile elements (data mules) for data collection in sensor networks. In DCOSS, pages 244--257, 2005.]]

Digital Library

[30]

P. Juang, H. Oki, Y. Wang, M. Martonosi, L. Peh, and D. Rubenstein. Energy-efficient computing for wildlife tracking: Design tradeoffs and early experiences with zebranet. In Proc. Architectural Support for Programming Languages and Operating Systems, 2002.]]

Digital Library

[31]

W. Kaiser, G. Pottie, M. Srivastava, G. Sukhatme, J. Villasenor, and D. Estrin. Networked Infomechanical Systems (NIMS) for Ambient Intelligence. Ambient Intelligence, 2004.]]

[32]

A. Kansal, M. Rahimi, W. Kaiser, M. Srivastava, G. Pottie, and D. Estrin. Controlled Mobility for Sustainable Wireless Networks. In IEEE SECON, 2004.]]

[33]

A. Kansal, A.A. Somasundara, D. Jea, M.B. Srivastava, and D. Estrin. Intelligent fluid infrastructure for embedded networking. In USENIX MobiSys, 2003.]]

Digital Library

[34]

U. Kubach and K. Rothermel. Exploiting location information for infostation-based hoarding. In MOBICOM, pages 15--27, 2001.]]

Digital Library

[35]

J. Lebrun, C.-N. Chuah, D. Ghosal, and M. Zhang. Knowledge-based opportunistic forwarding in vehicular wireless ad hoc networks. In IEEE Vehicular Tech. Conf., pages 2289--2293, 2005.]]

[36]

Q. Li and D. Rus. Sending messages to mobile users in disconnected ad-hoc wireless networks. In ACM MOBICOM, pages 44--55, 2000.]]

Digital Library

[37]

S. Madden, M. Franklin, J. Hellerstein, and W. Hong. Tag: A tiny aggregation service for ad-hoc sensor networks. In proc. of OSDI, 2002.]]

Digital Library

[38]

A. Mainwaring, J. Polastre, R. Szewczyk, and D. Culler. Wireless Sensor Networks for Habitat Monitoring. In WSNA, 2002.]]

Digital Library

[39]

R. Motwani, J. Widom, A. Arasu, B. Babcock, S. Babu, M. Data, C. Olston, J. Rosenstein, and R. Varma. Query Processing, Approximation and Resource Management in a Data Stream Management System. In CIDR, 2003.]]

[40]

Mobile Pollution Monitoring. http://www.toolkit.equator.ecs.soton.ac.uk/infrastructure/repository/mobilepollutionmonitor/web/index.html.]]

[41]

T. Nadeem, S. Dashtinezhad, C. Liao, and L. Iftode. TrafficView: Traffic data dissemination using car-to-car communication. MC2R, 8(3):6--19, 2004.]]

Digital Library

[42]

Executive summary of the conference on the prospect for miniaturization of mass spectrometry. Technical report, NSF, 2003. http://www.nsf-mass-spec-mini-forum.umd.edu/final_report.html.]]

[43]

J. Ott and D. Kutscher. A Disconnection-Tolerant Transport for Drive-thru Internet Environments. In INFOCOM, 2005.]]

[44]

PATH Project. http://www.path.berkeley.edu/.]]

[45]

PostgreSQL home page. http://www.postgresql.org/.]]

[46]

V. Raman, B. Raman, and J.M. Hellerstein. Online dynamic reordering for interactive data processing. In The VLDB Journal, pages 709--720, 1999.]]

Digital Library

[47]

A. Seth, P. Darragh, S. Liang, Y. Lin, and S. Keshav. An Architecture for Tetherless Communication. In DTN Workshop, 2005.]]

[48]

R.C. Shah, S. Roy, S. Jain, and W. Brunette. Data Mules: Modeling a Three-tier Architecture for Sparse Sensor Networks. In Proc. 1st IEEE SNPA Workshop, 2003.]]

[49]

T. Small and Z.J. Haas. The shared wireless infostation model: A new ad hoc networking paradigm (or where there is a whale, there is a way). In MOBIHOC, pages 233--244, 2003.]]

Digital Library

[50]

SmartTraveler. http://www.smartraveler.com.]]

[51]

B. Smith, H. Zhang, M. Fontaine, and M. Green. Cellphone probes as an ATMS tool. Technical Report STL-2003-01, Center for Transportation Studies, Univ. of Virginia, 2003. http://ntl.bts.gov/card_view.cfm?docid=23431.]]

[52]

G. Tolle, J. Polastre, R. Szewczyk, D. Culler, N. Turner, K. Tu, S. Burgess, T. Dawson, P. Buonadonna, D. Gay, and W. Hong. A macroscope in the redwoods. In ACM SenSys, pages 51--63, 2005.]]

Digital Library

[53]

H.-Y. Tong, W.-T. Hung, and C. Chun-shun. On-road motor vehicle emissions and fuel consumption in urban driving conditions. Journal of the Air and Waste Management Association, 50:543--554, Apr. 2000.]]

[54]

A. Unal, H.C. Frey, and N.M. Rouphail. Quantification of highway vehicle emissions hot spots based upon on-board measurements. Jour. of the Air & Waste Management Assn., 54:130--140, Feb. 2004.]]

[55]

I. Vasilescu, K. Kotay, D. Rus, M. Dunbabin, and P. Corke. Data collection, storage, and retrieval with an underwater sensor network. In ACM SenSys, pages 154--165, 2005.]]

Digital Library

[56]

M. Walfish, J. Stribling, M. Krohn, H. Balakrishnan, R. Morris, and S. Shenker. Middleboxes no longer considered harmful. In USENIX OSDI 2004, 2004.]]

Digital Library

[57]

G. Wiederhold. Mediators in the architecture of future information systems. In M.N. Huhns and M.P. Singh, editors, Readings in Agents, pages 185--196. Morgan Kaufmann, San Francisco, CA, USA, 1997.]]

Digital Library

[58]

Y. Yao and J. Gehrke. Query processing in sensor networks. In CIDR, 2003.]]

[59]

W. Zhao, M.H. Ammar, and E.W. Zegura. A message ferrying approach for data delivery in sparse mobile ad hoc networks. In MobiHoc, pages 187--198, 2004.]]

Digital Library

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Index Terms

CarTel: a distributed mobile sensor computing system
1. Software and its engineering
  1. Software organization and properties
    1. Software system structures
      1. Distributed systems organizing principles
        Organizing principles for web applications

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cover image ACM Conferences

SenSys '06: Proceedings of the 4th international conference on Embedded networked sensor systems

October 2006

444 pages

ISBN:1595933433

DOI:10.1145/1182807

General Chair:
Andrew Campbell
Dartmouth University
,
Program Chairs:
Philippe Bonnet
University of Copenhagen (DIKU), Denmark
,
John Heidemann
University of Southern California/ISI, USA

Copyright © 2006 ACM.

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Published: 31 October 2006

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https://doi.org/10.48175/IJARSCT-18205
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https://doi.org/10.1007/978-981-99-6921-0_1
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