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.
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References
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)
Warneke, B., Last, M., Liebowitz, B., Pister, K.: Smart dust: communicating with a cubic-millimeter computer. Computer 34(1), 44–51 (2001)
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)
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)
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)
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)
Akyildiz, I., Su, W., Sankarasubramaniam, Y., Cayirci, E.: Wireless sensor networks: a survey. Computer networks 38(4), 393–422 (2002)
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)
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)
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)
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)
Mainwaring, A., Polastre, J., Szewczyk, R., Culler, D., Anderson, J.: Wireless sensor networks for habitat monitoring
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)
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)
Martinez, K., Ong, R., Hart, J., Stefanov, J.: GLACSWEB: a sensor web for glaciers. Technical University Berlin Telecommunication Networks Group, p. 46
ARGO — Global Ocean Sensor Network
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)
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)
Hu, W., Bulusu, N., Chou, C., Jha, S., Taylor, A.: Design and evaluation of a hybrid sensor network for cane toad monitoring (2009)
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)
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)
Union, E.: Official journal of the european union
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)
Joseph, A.: Energy harvesting projects. IEEE Pervasive Computing 4(1), 69–71 (2005)
Paradiso, J., Starner, T.: Energy scavenging for mobile and wireless electronics. IEEE Pervasive Computing 4(1), 18–27 (2005)
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)
Williams, C., Yates, R.: Analysis of a micro-electric generator for microsystems. Sensors & Actuators: A. Physical 52(1-3), 8–11 (1996)
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)
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)
Duracell, Ni-mh technical bulletin collection, http://www.duracell.com/oem/rechargeable/Nickel/nickel_metal_tech.asp
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)
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)
Tang, C., Raghavendra, C.: Compression techniques for wireless sensor networks. Wireless sensor networks, 207–231 (2004)
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)
Madden, S., Franklin, M., Hellerstein, J., Hong, W.: Tag: a tiny aggregation service for ad-hoc sensor networks
Boulis, A., Ganeriwal, S., Srivastava, M.: Aggregation in sensor networks: an energy–accuracy trade-off. Ad hoc networks 1(2-3), 317–331 (2003)
Goel, S., Imielinski, T.: Prediction-based monitoring in sensor networks: taking lessons from MPEG. ACM SIGCOMM Computer Communication Review 31(5), 82–98 (2001)
Cerpa, A., Estrin, D.: Ascent: Adaptive self-configuring sensor networks topologies. IEEE Transactions on Mobile Computing 3(3), 272–285 (2004)
Schurgers, C., Tsiatsis, V., Ganeriwal, S., Srivastava, M.: Optimizing sensor networks in the energy-latency-density design space. IEEE transactions on mobile computing (2002)
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)
Raghunathan, V., Ganeriwal, S., Srivastava, M.: Emerging techniques for long lived wireless sensor networks. IEEE Communications Magazine 44(4), 108–114 (2006)
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)
Tseng, Y., Wang, Y., Cheng, K., Hsieh, Y.: iMouse: an integrated mobile surveillance and wireless sensor system. Computer 40(6), 60–66 (2007)
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)
Jain, A., Chang, E.: Adaptive sampling for sensor networks. In: ACM International Conference Proceeding Series, vol. 72, pp. 10–16. ACM, New York (2004)
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)
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)
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)
Raghunathan, V., Schurgers, C., Park, S., Srivastava, M.: Energy-aware wireless microsensor networks. IEEE Signal Processing Magazine 19(2), 40–50 (2002)
Vuran, M., Akan, Ö., Akyildiz, I.: Spatio-temporal correlation: theory and applications for wireless sensor networks. Computer Networks 45(3), 245–259 (2004)
Pattem, S., Krishnamachari, B., Govindan, R.: The impact of spatial correlation on routing with compression in wireless sensor networks (2008)
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)
Akyildiz, I., Melodia, T., Chowdhury, K.: A survey on wireless multimedia sensor networks. Computer Networks 51(4), 921–960 (2007)
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)
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)
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)
Chu, D., Tavakoli, A., Popa, L., Hellerstein, J.: Entirely declarative sensor network systems. In: Proc. VLDB 2006, pp. 1203–1206 (2006)
Siemens, Sword - internal communication (2008)
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)
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)
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)
The Network Simulator - ns-2
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)
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)
Varga, A., et al.: The OMNeT++ discrete event simulation system. In: Proceedings of the European Simulation Multiconference (ESMí 2001), pp. 319–324 (2001)
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)
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)
Girod, L., Elson, J., Cerpa, A., Stathopoulos, T., Ramanathan, N., Estrin, D.: Emstar: a software environment for developing and deploying wireless sensor networks
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)
Al-Karaki, J., Kamal, A.: Routing techniques in wireless sensor networks: a survey. IEEE Wireless Communications 11(6), 6–28 (2004)
Akkaya, K., Younis, M.: A survey on routing protocols for wireless sensor networks. Ad Hoc Networks 3(3), 325–349 (2005)
P2ict lab monitoring the marine environment, http://www.prometeo.polimi.it/ict/icteng/ict_australia_eng.html
XBow, http://www.xbow.com/
MaxStream, http://www.maxstream.com/
International Society of Rock Mechanics, Suggested methods for monitoring rock movements using inclinometers and tiltmeters. Rock Mechanics 10, 81–106
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)
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
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)
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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
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