skip to main content
10.1145/1859983.1859994acmconferencesArticle/Chapter ViewAbstractPublication PagesmobicomConference Proceedingsconference-collections
research-article

Opportunistic collaboration in participatory sensing environments

Published:24 September 2010Publication History

ABSTRACT

The proliferation of networked mobile devices that can capture and communicate various kinds of data provides an opportunity to design novel man-machine sensing environments of which this paper considers participatory sensing. To achieve energy efficiency and reduce data redundancy, we propose Aquiba protocol that exploits opportunistic collaboration of pedestrians. Sensing activity is reduced according to the number of available pedestrians in nearby area. The paper investigates the benefit of opportunistic collaboration in large-scale scenarios through simulation studies. To take microscopic interaction of social crowds into consideration, we adapt the social force model and include it as one of three mobility models applied in our studies. Though the simulation results depend on mobility models, they validate the benefit of opportunistic collaboration employed by Aquiba protocol.

References

  1. }}F. Bai, N. Sadagopan, and A. Helmy. The IMPORTANT framework for analyzing the Impact of Mobility on Performance Of RouTing protocols for Adhoc NeTworks. Ad Hoc Networks, 1(4):383--403, Nov. 2003.Google ScholarGoogle ScholarCross RefCross Ref
  2. }}J. Broch, D. A. Maltz, D. B. Johnson, Y.-C. Hu, and J. Jetcheva. A performance comparison of multi-hop wireless ad hoc network routing protocols. In Proceedings of the 4th ACM International Conference on Mobile Computing and Networking (MobiCom 1998), pages 85--97, Dallas, Texas, USA, Oct. 1998. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. }}J. Burke, D. Estrin, M. Hansen, A. Parker, N. Ramanathan, S. Reddy, and M. B. Srivastava. Participatory sensing. In Proceedings of the Workshop on World-Sensor-Web (WSW 2006), pages 6--10, Boulder, Colorado, USA, Nov. 2006.Google ScholarGoogle Scholar
  4. }}A. T. Campbell, N. D. Lane, E. Miluzzo, R. A. Peterson, H. Lu, X. Zheng, M. Musolesi, K. Fodor, S. B. Eisenman, and G.-S. Ahn. The rise of people-centric sensing. IEEE Internet Computing, 12(4):12--21, July/August 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. }}Casio Computer Co.,Ltd. G'zOne W62CA. http://k-tai.casio.jp/products/w62ca/, accessed July 2010.Google ScholarGoogle Scholar
  6. }}D. Cuff, M. Hansen, and J. Kang. Urban sensing: out of the woods. Communications of the ACM, 51(3):24--33, Mar. 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. }}S. B. Eisenman, E. Miluzzo, N. D. Lane, R. A. Peterson, G.-S. Ahn, and A. T. Campbell. The BikeNet mobile sensing system for cyclist experience mapping. In Proceedings of the 5th International Conference on Embedded Networked Sensor Systems (SenSys 2007), pages 87--101, Sydney, Australia, Nov. 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. }}W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan. An application-specific protocol architecture for wireless microsensor networks. IEEE Transactions on Wireless Communications, 1(4):660--670, Oct. 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. }}D. Helbing, L. Buzna, A. Johansson, and T. Werner. Self-organized pedestrian crowd dynamics: Experiments, simulations, and design solutions. Transportation Science, 39(1):1--24, Feb. 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. }}D. Helbing and P. Molnár. Social force model for pedestrian dynamics. Physical Review E (Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics), 51(5):4282--4286, May 1995.Google ScholarGoogle Scholar
  11. }}B. Hull, V. Bychkovsky, Y. Zhang, K. Chen, M. Goraczko, A. Miu, E. Shih, H. Balakrishnan, and S. Madden. CarTel: A distributed mobile sensor computing system. In Proceedings of the 4th International Conference on Embedded Networked Sensor Systems (SenSys 2006), pages 125--138, Boulder, Colorado, USA, Nov. 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. }}J. C. R. Licklider. Man-computer symbiosis. IRE Transactions on Human Factors in Electronics, HFE-1:4--11, Mar. 1960.Google ScholarGoogle ScholarCross RefCross Ref
  13. }}L. Luo, C. Huang, T. Abdelzaher, and J. Stankovic. EnviroStore: A cooperative storage system for disconnected operation in sensor networks. In Proceedings of the 26th Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM 2007), pages 1802--1810, Anchorage, Alaska, USA, May 2007.Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. }}E. Miluzzo, N. D. Lane, K. Fodor, R. Peterson, H. Lu, M. Musolesi, S. B. Eisenman, X. Zheng, and A. T. Campbell. Sensing meets mobile social networks: the design, implementation and evaluation of the CenceMe application. In Proceedings of the 6th International Conference on Embedded Networked Sensor Systems (SenSys 2008), pages 337--350, Raleigh, North Carolina, USA, Nov. 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. }}P. Mohan, V. N. Padmanabhan, and R. Ramjee. Nericell: rich monitoring of road and traffic conditions using mobile smartphones. In Proceedings of the 6th International Conference on Embedded Networked Sensor Systems (SenSys 2008), pages 323--336, Raleigh, North Carolina, USA, Nov. 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. }}S. M. Mousavi, H. R. Rabiee, M. Moshref, and A. Dabirmoghaddam. MobiSim: A framework for simulation of mobility models in mobile ad-hoc networks. In Proceedings of the 3rd IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob 2007), page 82, New York, USA, Oct. 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. }}M. Musolesi, M. Piraccini, K. Fodor, A. Corradi, and A. T. Campbell. Supporting energy-efficient uploading strategies for continuous sensing applications on mobile phones. In Proceedings of the 8th International Conference on Pervasive Computing (Pervasive 2010), pages 355--372, Helsinki, Finland, May 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. }}Network simulator - ns--2. http://www.isi.edu/nsnam/ns/, accessed July 2010.Google ScholarGoogle Scholar
  19. }}L. Rabiner and B.-H. Juang. Fundamentals of Speech Recognition. Prentice Hall Signal Processing Series. Prentice Hall PTR, Apr. 1993. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. }}S. Reddy, D. Estrin, and M. Srivastava. Recruitment framework for participatory sensing data collections. In Proceedings of the 8th International Conference on Pervasive Computing (Pervasive 2010), pages 138--155, Helsinki, Finland, May 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. }}R. C. Shah, S. Roy, S. Jain, and W. Brunette. Data mules: Modeling a three-tier architecture for sparse sensor networks. In Proceedings of the 1st IEEE International Workshop on Sensor Network Protocols and Applications (SNPA 2003), pages 30--41, Anchorage, Alaska, USA, May 2003.Google ScholarGoogle ScholarCross RefCross Ref
  22. }}T. Small and Z. J. Haas. Resource and performance tradeoffs in delay-tolerant wireless networks. In Proceedings of the ACM Workshop on Delay Tolerant Networking (WDTN 2005), pages 260--267, Philadelphia, Pennsylvania, USA, Aug. 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. }}T. Spyropoulos, K. Psounis, and C. S. Raghavendra. Spray and wait: An efficient routing scheme for intermittently connected mobile networks. In Proceedings of the ACM Workshop on Delay Tolerant Networking (WDTN 2005), pages 252--259, Philadelphia, Pennsylvania, USA, Aug. 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. }}Texax Instruments. CC2420: single-chip 2.4-GHz IEEE 802.15.4 complaint and ZigBee-ready RF transceiver. http://focus.ti.com/docs/prod/folders/print/cc2420.html.Google ScholarGoogle Scholar
  25. }}A. Vahdat and D. Becker. Epidemic routing for partially-connected ad hoc networks. Technical Report CS-2000-06, Duke University, July 2000.Google ScholarGoogle Scholar
  26. }}C.-Y. Wan, S. B. Eisenman, A. T. Campbell, and J. Crowcroft. Overload traffic management for sensor networks. ACM Transactions on Sensor Networks, 3(4):18, Oct. 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. }}Weathernews Inc. Weathernews. http://weathernews.com/, accessed July 2010.Google ScholarGoogle Scholar

Index Terms

  1. Opportunistic collaboration in participatory sensing environments

          Recommendations

          Comments

          Login options

          Check if you have access through your login credentials or your institution to get full access on this article.

          Sign in
          • Published in

            cover image ACM Conferences
            MobiArch '10: Proceedings of the fifth ACM international workshop on Mobility in the evolving internet architecture
            September 2010
            54 pages
            ISBN:9781450301435
            DOI:10.1145/1859983

            Copyright © 2010 ACM

            Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

            Publisher

            Association for Computing Machinery

            New York, NY, United States

            Publication History

            • Published: 24 September 2010

            Permissions

            Request permissions about this article.

            Request Permissions

            Check for updates

            Qualifiers

            • research-article

            Acceptance Rates

            Overall Acceptance Rate47of92submissions,51%

          PDF Format

          View or Download as a PDF file.

          PDF

          eReader

          View online with eReader.

          eReader