Skip to main content

From Labs to Real Environments: The Dark Side of WSNs

  • Chapter
Recent Advances in Sensing Technology

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 49))

Abstract

Distributed environmental monitoring with wireless sensor networks (WSNs) is one of the most challenging research activities faced by the embedded system community in the last decade. Here, the need for pervasive, reliable and accurate monitoring systems has pushed the research to address aspects related to the realization of credible deployments able to survive in harsh environments for long time and not only toy applications working in laboratories. Designing an effective WSN requires a good piece of engineer work, not to mention the research contribution needed to provide a credible deployment. As a matter of fact, to solve our application, we are looking for a monitoring framework scalable, adaptive with respect to topological changes in the network, intelligent in its ability to react to evolutions in the external environment, power-aware in its middleware components and endowed with energy harvesting mechanisms to grant a long lifetime for the network. The paper addresses all main aspects related to the design of a WSN ranging from the possible- need of an ad-hoc embedded system, to sensing, local and remote transmission, data storage and visualization. Two applications, namely monitoring the marine environment and forecasting the collapse of rock faces in mountaineering areas will be the experimental leitmotiv of the chapter.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Kahn, J., Katz, R., Pister, K.: ‘Next century challenges: mobile networking for “Smart Dust”. In: Proceedings of the 5th annual ACM/IEEE international conference on Mobile computing and networking, pp. 271–278. ACM, New York (1999)

    Chapter  Google Scholar 

  2. Warneke, B., Last, M., Liebowitz, B., Pister, K.: Smart dust: communicating with a cubic-millimeter computer. Computer 34(1), 44–51 (2001)

    Article  Google Scholar 

  3. Kahn, J., Katz, R., Pister, K.: Mobile networking for smart dust. In: ACM/IEEE Intl. Conf. on Mobile Computing and Networking (MobiCom 1999), Seattle, WA, pp. 271–278 (1999)

    Google Scholar 

  4. Anderson, R., Chan, H., Perrig, A.: Key infection: Smart trust for smart dust. In: Proceedings of the 12th IEEE International Conference on Network Protocols. ICNP 2004, pp. 206–215 (2004)

    Google Scholar 

  5. Romer, K.: Tracking real-world phenomena with smart dust. In: Karl, H., Wolisz, A., Willig, A. (eds.) EWSN 2004. LNCS, vol. 2920, pp. 28–43. Springer, Heidelberg (2004)

    Google Scholar 

  6. Estrin, D., et al.: Instrumenting the world with wireless sensor networks. In: Proc. of the IEEE Acoustic, Speech, and Signal Proc. Conf., vol. 4, pp. 2033–2036 (2001)

    Google Scholar 

  7. Akyildiz, I., Su, W., Sankarasubramaniam, Y., Cayirci, E.: Wireless sensor networks: a survey. Computer networks 38(4), 393–422 (2002)

    Article  Google Scholar 

  8. Sohrabi, K., Gao, J., Ailawadhi, V., Pottie, G.: Protocols for self-organization of a wireless sensor network. IEEE Personal Communications 7(5), 16–27 (2000)

    Article  Google Scholar 

  9. Gamage, C., Bicakci, K., Crispo, B., Tanenbaum, A.: Security for the Mythical Air-dropped Sensor Network. In: Proceedings of the 11th IEEE Symposium on Computers and Communications, pp. 41–47. IEEE Computer Society, Washington (2006)

    Google Scholar 

  10. Van Hoesel, L., Nieberg, T., Wu, J., Havinga, P.: Prolonging the lifetime of wireless sensor networks by cross-layer interaction. IEEE Wireless Communications 11(6), 78–86 (2004)

    Article  Google Scholar 

  11. Madan, R., Cui, S., Lall, S., Goldsmith, A.: Cross-layer design for lifetime maximization in interference-limited wireless sensor networks. In: Proceedings IEEE INFOCOM 2005. 24th Annual Joint Conference of the IEEE Computer and Communications Societies, vol. 3 (2005)

    Google Scholar 

  12. Mainwaring, A., Polastre, J., Szewczyk, R., Culler, D., Anderson, J.: Wireless sensor networks for habitat monitoring

    Google Scholar 

  13. Hartung, C., Han, R., Seielstad, C., Holbrook, S.: FireWxNet: A multi-tiered portable wireless system for monitoring weather conditions in wildland fire environments. In: Proc. International conference on Mobile systems, applications and services, pp. 28–41 (2006)

    Google Scholar 

  14. Werner-Allen, G., Johnson, J., Ruiz, M., Lees, J., Welsh, M.: Monitoring volcanic eruptions with a wireless sensor network. In: Proceeedings of the Second European Workshop on Wireless Sensor Networks, pp. 108–120 (2005)

    Google Scholar 

  15. Martinez, K., Ong, R., Hart, J., Stefanov, J.: GLACSWEB: a sensor web for glaciers. Technical University Berlin Telecommunication Networks Group, p. 46

    Google Scholar 

  16. ARGO — Global Ocean Sensor Network

    Google Scholar 

  17. Tolle, G., Polastre, J., Szewczyk, R., Culler, D., Turner, N., Tu, K., Burgess, S., Dawson, T., Buonadonna, P., Gay, D., et al.: A macroscope in the redwoods. In: Proceedings of the 3rd international conference on Embedded networked sensor systems, pp. 51–63. ACM, New York (2005)

    Chapter  Google Scholar 

  18. Juang, P., Oki, H., Wang, Y., Martonosi, M., Peh, L., Rubenstein, D.: Energy-efficient computing for wildlife tracking: Design tradeoffs and early experiences with zebranet. Computer Architecture News 30(5), 96–107 (2002)

    Article  Google Scholar 

  19. Hu, W., Bulusu, N., Chou, C., Jha, S., Taylor, A.: Design and evaluation of a hybrid sensor network for cane toad monitoring (2009)

    Google Scholar 

  20. He, T., Krishnamurthy, S., Luo, L., Yan, T., Gu, L., Stoleru, R., Zhou, G., Cao, Q., Vicaire, P., Stankovic, J., et al.: VigilNet: An integrated sensor network system for energy-efficient surveillance. ACM Transactions on Sensor Networks (TOSN) 2(1), 1–38 (2006)

    Article  Google Scholar 

  21. Beckwith, R., Teibel, D., Bowen, P.: Pervasive computing and proactive agriculture. In: Advances in Pervasive Computing: A Collection of Contributions Presented at PERVASIVE 2004. Österreichische Computer Gesellschaft, p. 309 (2004)

    Google Scholar 

  22. Union, E.: Official journal of the european union

    Google Scholar 

  23. Ottman, G., Hofmann, H., Bhatt, A., Lesieutre, G.: Adaptive piezoelectric energy harvesting circuit for wireless remote power supply. IEEE Transactions on Power Electronics 17(5), 669–676 (2002)

    Article  Google Scholar 

  24. Joseph, A.: Energy harvesting projects. IEEE Pervasive Computing 4(1), 69–71 (2005)

    Article  Google Scholar 

  25. Paradiso, J., Starner, T.: Energy scavenging for mobile and wireless electronics. IEEE Pervasive Computing 4(1), 18–27 (2005)

    Article  Google Scholar 

  26. Roundy, S., Leland, E., Baker, J., Carleton, E., Reilly, E., Lai, E., Otis, B., Rabaey, J., Wright, P., Sundararajan, V.: Improving power output for vibration-based energy scavengers. IEEE Pervasive computing 4(1), 28–36 (2005)

    Article  Google Scholar 

  27. Williams, C., Yates, R.: Analysis of a micro-electric generator for microsystems. Sensors & Actuators: A. Physical 52(1-3), 8–11 (1996)

    Article  Google Scholar 

  28. Raghunathan, V., Kansal, A., Hsu, J., Friedman, J., Srivastava, M.: Design considerations for solar energy harvesting wireless embedded systems. In: IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005, pp. 457–462 (2005)

    Google Scholar 

  29. Alippi, C., Galperti, C.: An Adaptive System for Optimal Solar Energy Harvesting in Wireless Sensor Network Nodes. IEEE Transactions on Circuits and Systems I: Regular Papers 55(6), 1742–1750 (2008)

    Article  Google Scholar 

  30. Duracell, Ni-mh technical bulletin collection, http://www.duracell.com/oem/rechargeable/Nickel/nickel_metal_tech.asp

  31. Alippi, C., Galperti, C.: Energy storage mechanisms in low power embedded systems: twin batteries and supercapacitors. In: Proceedings of Wireless Vitae 2009, Aalborg, Denmark, May 17-20, pp. 17–20 (2009)

    Google Scholar 

  32. Anastasi, G., Conti, M., Di Francesco, M., Passarella, A.: How to prolong the lifetime of wireless sensor networks. In: Denko, M., Yang, L. (eds.) Mobile Ad Hoc and Pervasive Communications (to appear)

    Google Scholar 

  33. Tang, C., Raghavendra, C.: Compression techniques for wireless sensor networks. Wireless sensor networks, 207–231 (2004)

    Google Scholar 

  34. Sadler, C., Martonosi, M.: Data compression algorithms for energy-constrained devices in delay tolerant networks. In: Proceedings of the 4th international conference on Embedded networked sensor systems, pp. 265–278. ACM, New York (2006)

    Chapter  Google Scholar 

  35. Madden, S., Franklin, M., Hellerstein, J., Hong, W.: Tag: a tiny aggregation service for ad-hoc sensor networks

    Google Scholar 

  36. Boulis, A., Ganeriwal, S., Srivastava, M.: Aggregation in sensor networks: an energy–accuracy trade-off. Ad hoc networks 1(2-3), 317–331 (2003)

    Article  Google Scholar 

  37. Goel, S., Imielinski, T.: Prediction-based monitoring in sensor networks: taking lessons from MPEG. ACM SIGCOMM Computer Communication Review 31(5), 82–98 (2001)

    Article  Google Scholar 

  38. Cerpa, A., Estrin, D.: Ascent: Adaptive self-configuring sensor networks topologies. IEEE Transactions on Mobile Computing 3(3), 272–285 (2004)

    Article  Google Scholar 

  39. Schurgers, C., Tsiatsis, V., Ganeriwal, S., Srivastava, M.: Optimizing sensor networks in the energy-latency-density design space. IEEE transactions on mobile computing (2002)

    Google Scholar 

  40. Ganesan, D., Cerpa, A., Ye, W., Yu, Y., Zhao, J., Estrin, D.: Networking issues in wireless sensor networks. Journal of Parallel and Distributed Computing 64(7), 799–814 (2004)

    Article  Google Scholar 

  41. Raghunathan, V., Ganeriwal, S., Srivastava, M.: Emerging techniques for long lived wireless sensor networks. IEEE Communications Magazine 44(4), 108–114 (2006)

    Article  Google Scholar 

  42. Schott, B., Bajura, M., Czarnaski, J., Flidr, J., Tho, T., Wang, L.: A modular power-aware microsensor with > 1000X dynamic power range. In: Fourth International Symposium on Information Processing in Sensor Networks. IPSN 2005, pp. 469–474 (2005)

    Google Scholar 

  43. Tseng, Y., Wang, Y., Cheng, K., Hsieh, Y.: iMouse: an integrated mobile surveillance and wireless sensor system. Computer 40(6), 60–66 (2007)

    Article  Google Scholar 

  44. Deshpande, A., Guestrin, C., Madden, S., Hellerstein, J., Hong, W.: Model-driven data acquisition in sensor networks. In: Proceedings of the Thirtieth international conference on Very large data bases. VLDB Endowment, vol. 30, pp. 588–599 (2004)

    Google Scholar 

  45. Jain, A., Chang, E.: Adaptive sampling for sensor networks. In: ACM International Conference Proceeding Series, vol. 72, pp. 10–16. ACM, New York (2004)

    Google Scholar 

  46. Willett, R., Martin, A., Nowak, R.: Backcasting: adaptive sampling for sensor networks. In: Proceedings of the 3rd international symposium on Information processing in sensor networks, pp. 124–133. ACM, New York (2004)

    Chapter  Google Scholar 

  47. Zhou, J., De Roure, D., Vivekanandan, S.: Adaptive Sampling and Routing in a Floodplain Monitoring Sensor Network. In: Proc. IEEE WiMob, pp. 19–21 (2006)

    Google Scholar 

  48. Alippi, C., Anastasi, G., Galperti, C., Mancini, F., Roveri, M.: Adaptive sampling for energy conservation in wireless sensor networks for snow monitoring applications. In: Proc. IEEE International Workshop on Mobile Ad Hoc and Sensor Systems for Global and Homeland Security (MASS-GHS 2007), Pisa, Italy (2007)

    Google Scholar 

  49. Raghunathan, V., Schurgers, C., Park, S., Srivastava, M.: Energy-aware wireless microsensor networks. IEEE Signal Processing Magazine 19(2), 40–50 (2002)

    Article  Google Scholar 

  50. Vuran, M., Akan, Ö., Akyildiz, I.: Spatio-temporal correlation: theory and applications for wireless sensor networks. Computer Networks 45(3), 245–259 (2004)

    Article  MATH  Google Scholar 

  51. Pattem, S., Krishnamachari, B., Govindan, R.: The impact of spatial correlation on routing with compression in wireless sensor networks (2008)

    Google Scholar 

  52. Vuran, M., Akyildiz, I.: Spatial correlation-based collaborative medium access control in wireless sensor networks. IEEE/ACM Transactions on Networking (TON) 14(2), 316–329 (2006)

    Article  Google Scholar 

  53. Akyildiz, I., Melodia, T., Chowdhury, K.: A survey on wireless multimedia sensor networks. Computer Networks 51(4), 921–960 (2007)

    Article  Google Scholar 

  54. Alippi, C., Baroni, G., Bersani, A., Roveri, M.: Unsupervised feature selection algorithms for Wireless Sensor Network. In: Proc. IEEE-CIMSA 2009, Hong Kong, China, May 11-13 (2009)

    Google Scholar 

  55. Madden, S.R., Franklin, M.J., Hellerstein, J.M., Hong, W.: Tinydb: an acquisitional query processing system for sensor networks. ACM Trans. Database Syst. 30(1), 122–173 (2005)

    Article  Google Scholar 

  56. Aberer, K., Hauswirth, M., Salehi, A.: Infrastructure for data processing in large-scale interconnected sensor networks. In: Mobile Data Management (MDM 2007), Mannheim, Germany (2007)

    Google Scholar 

  57. Chu, D., Tavakoli, A., Popa, L., Hellerstein, J.: Entirely declarative sensor network systems. In: Proc. VLDB 2006, pp. 1203–1206 (2006)

    Google Scholar 

  58. Siemens, Sword - internal communication (2008)

    Google Scholar 

  59. Schreiber, F., Camplani, R., Fortunato, M., Marelli, M., Pacifici, F.: PERLA: A Data Language for Pervasive Systems. In: PerCom 2008. Sixth Annual IEEE International Conference on Pervasive Computing and Communications, pp. 282–287 (2008)

    Google Scholar 

  60. Beyer, S., Taylor, R., Mayes, K.: Operating system support for dynamic code loading in sensor networks. In: Fourth Annual IEEE International Conference on Pervasive Computing and Communications Workshops. PerCom Workshops 2006, p. 5 (2006)

    Google Scholar 

  61. Egea-Lopez, E., Vales-Alonso, J., Martinez-Sala, A., Pavon-Marino, P., Garcia-Haro, J.: Simulation scalability issues in wireless sensor networks. IEEE Communications Magazine 44(7), 64 (2006)

    Article  Google Scholar 

  62. The Network Simulator - ns-2

    Google Scholar 

  63. Naoumov, V., Gross, T.: Simulation of large ad hoc networks. In: Proceedings of the 6th ACM international workshop on Modeling analysis and simulation of wireless and mobile systems, pp. 50–57. ACM, New York (2003)

    Chapter  Google Scholar 

  64. Sobeih, A., Chen, W., Hou, J., Kung, L., Li, N., Lim, H., Tyan, H., Zhang, H.: J-sim: A simulation environment for wireless sensor networks. In: Proceedings of the 38th annual Symposium on Simulation, pp. 175–187. IEEE Computer Society, Washington (2005)

    Chapter  Google Scholar 

  65. Varga, A., et al.: The OMNeT++ discrete event simulation system. In: Proceedings of the European Simulation Multiconference (ESMí 2001), pp. 319–324 (2001)

    Google Scholar 

  66. Levis, P., Lee, N., Welsh, M., Culler, D.: TOSSIM: Accurate and scalable simulation of entire TinyOS applications. In: Proceedings of the 1st international conference on Embedded networked sensor systems, pp. 126–137. ACM, New York (2003)

    Chapter  Google Scholar 

  67. Polley, J., Blazakis, D., McGee, J., Rusk, D., Baras, J.: Atemu: A fine-grained sensor network simulator. In: 2004 First Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks. IEEE SECON 2004, pp. 145–152 (2004)

    Google Scholar 

  68. Girod, L., Elson, J., Cerpa, A., Stathopoulos, T., Ramanathan, N., Estrin, D.: Emstar: a software environment for developing and deploying wireless sensor networks

    Google Scholar 

  69. Alippi, C., Camplani, R., Galperti, C., Roveri, M., Sportiello, L.: Towards a credible WSNs deployment: a monitoring framework based on an adaptive communication protocol and energy-harvesting availability. In: IEEE Instrumentation and Measurement Technology Conference Proceedings, 2008. IMTC 2008, pp. 66–71 (2008)

    Google Scholar 

  70. Al-Karaki, J., Kamal, A.: Routing techniques in wireless sensor networks: a survey. IEEE Wireless Communications 11(6), 6–28 (2004)

    Article  Google Scholar 

  71. Akkaya, K., Younis, M.: A survey on routing protocols for wireless sensor networks. Ad Hoc Networks 3(3), 325–349 (2005)

    Article  Google Scholar 

  72. P2ict lab monitoring the marine environment, http://www.prometeo.polimi.it/ict/icteng/ict_australia_eng.html

  73. XBow, http://www.xbow.com/

  74. MaxStream, http://www.maxstream.com/

  75. International Society of Rock Mechanics, Suggested methods for monitoring rock movements using inclinometers and tiltmeters. Rock Mechanics 10, 81–106

    Google Scholar 

  76. Lynch, P.: An overview of wireless structural health monitoring for civil structures, ser. A. In: Philosophical Transactions of the Royal Society of London. A Mathematical and Physical Sciences. The Royal Society, London (2005)

    Google Scholar 

  77. Green, L.G., Maürer, H., Spillmann, T., Heincke, B., Willenberg, H.: High-resolution geophysical techniques for improving hazard assessment of unstable rock slopes. Swiss Federal Institute of Technology, Zurich

    Google Scholar 

  78. Alippi, C., Camplani, R., Galperti, G.: Lossless compression techniques in wireless sensor networks: Monitoring microacoustic emissions. In: IEEE International Workshop on RObotic and Sensors Environments, ROSE 2007, Ontario, Canada, October 12-13, pp. 1–5 (2007)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Alippi, C., Camplani, C., Galperti, C., Roveri, M. (2009). From Labs to Real Environments: The Dark Side of WSNs. In: Mukhopadhyay, S.C., Gupta, G.S., Huang, R.YM. (eds) Recent Advances in Sensing Technology. Lecture Notes in Electrical Engineering, vol 49. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00578-7_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-00578-7_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-00577-0

  • Online ISBN: 978-3-642-00578-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics