Design, Implementation, and Field Experimentation of a Long-Lived Multi-hop Sensor Network for Vineyard Monitoring

  • Giuseppe Anastasi
  • Marco Conti
  • Mario Di Francesco
  • Ilaria Giannetti
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7200)


Precision agriculture can particularly benefit from wireless sensor networks, as they allow continuous and fine-grained monitoring of environmental data, which can thus be used to reduce management costs and improve crop quality. Such applications typically require long-term and unattended monitoring of large geographical areas. Therefore, sensor nodes must be able to self-organize and use their limited energy budget very efficiently, so as to prolong the network lifetime to many months or, even, years. In this chapter we present ASLEEP, an adaptive strategy for efficient power management in multi-hop WSNs targeted to periodic data collection. The proposed strategy dynamically adjusts the active periods of nodes to match the network demands with the minimum energy expenditure. In this chapter we focus on the implementation and the experimental evaluation of ASLEEP on a real testbed deployed in a vineyard, according to the case study considered in the project. We show that our adaptive approach actually reduces the energy consumption of sensor nodes, thus increasing the network lifetime up to several years.


Sensor Network Sensor Node Wireless Sensor Network Network Lifetime Delivery Ratio 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Akyildiz, I.F., Su, W., Sankarasubramaniam, Y., Cayirci, E.: Wireless Sensor Networks: a Survey. Computer Networks 38(4) (March 2002)Google Scholar
  2. 2.
    Anastasi G., Conti M., Di Francesco M.: An Adaptive Sleep Strategy for Energy Conservation in Wireless Sensor Networks. Technical Report DII-TR-2009-03, University of Pisa,
  3. 3.
    Anastasi, G., Conti, M., Di Francesco, M., Passarella, A.: Energy Conservation in Wireless Sensor Networks: a Survey. Ad hoc Networks 7(3), 537–568 (2009)CrossRefGoogle Scholar
  4. 4.
    Anastasi, G., Conti, M., Di Francesco, M.: Extending the Lifetime of Wireless Sensor Networks through Adaptive Sleep. IEEE Transactions on Industrial Informatics 5(3), 351–365 (2009)CrossRefGoogle Scholar
  5. 5.
    Baggio, A.: Wireless Sensor Networks in Precision Agriculture. In: Proceedings ACM Workshop on Real-World Wireless Sensor Networks (REALWSN 2005). ACM (2005)Google Scholar
  6. 6.
    Cao, Q., Abdelzaher, T., He, T., Stankovic, J.: Toward Optimal Sleep Scheduling in Sensor Networks for Rare Event Detection. In: Proc. IPSN 2005 (April 2005)Google Scholar
  7. 7.
    Hill, J., Szewczyk, R., Woo, A., Hollar, S., Culler, D., Pister, K.: System architecture directions for networked sensors. SIGPLAN Not. 35(11), 93–104 (2000)CrossRefGoogle Scholar
  8. 8.
    Hohlt, B., Doherty, L., Brewer, E.: Flexible Power Scheduling for Sensor Networks. In: IEEE and ACM International Symposium on Information Processing in Sensor Networks (April 2004)Google Scholar
  9. 9.
    Hohlt, B., Brewer, E.: Network Power Scheduling for TinyOS Applications. In: Proc. IEEE Int’l Conf. on Distributed Computing in Sensor Systems (DCOSS 2006), San Francisco, USA (2006)Google Scholar
  10. 10.
    Intanagonwiwat, C., Govindan, R., Estrin, D.: Directed Diffusion: a Scalable and Robust Communication Paradigm for Sensor Networks. In: Proc. ACM (MobiCOM 2000), Boston, USA (August 2000)Google Scholar
  11. 11.
    Jurdak, R., Baldi, P., Lopes, C.V.: Adaptive Low Power Listening for Wireless Sensor Networks. Transactions on Mobile Computing 6(8), 988–1004 (2007)CrossRefGoogle Scholar
  12. 12.
    Keshavarzian, A., Lee, H., Venkatraman, L.: Wakeup Scheduling in Wireless Sensor Networks. In: Proc. ACM MobiHoc 2006, Florence, Italy (May 2006)Google Scholar
  13. 13.
    Li, Y., Ye, W., Heidemann, J.: Energy and Latency Control, in Low Duty-cycle MAC Protocols. In: Proc. IEEE Wireless Communication and Networking Conference, New Orleans, USA (March 2005)Google Scholar
  14. 14.
    Lu, G., Krishnamachari, B., Raghavendra, C.S.: An Adaptive Energy-efficient and Low-latency Mac for Data Gathering in Wireless Sensor Networks. In: Proc. PDSP 2004 (April 2004)Google Scholar
  15. 15.
    Lu, G., Sadagopan, N., Krishnamachari, B., Goel, A.: Delay Efficient Sleep Scheduling in Wireless Sensor Networks. In: Proc. IEEE Infocom 2005 (March 2005)Google Scholar
  16. 16.
    Madden, S., Franklin, M., Hellerstein, J., Hong, W.: TAG: a Tiny AGgregation Service for Ad-Hoc Sensor Networks. In: Proc. of OSDI (2002)Google Scholar
  17. 17.
    Madden, S.: The Design and Evaluation of a Query Processing Architecture for Sensor Networks. UC Berkeley Ph.D. Thesis (2003)Google Scholar
  18. 18.
    Manjeshwar, A., Agrawal, D.P.: APTEEN: A Hybrid Protocol for Efficient Routing and Comprehensive Information Retrieval in Wireless Sensor Networks. In: Proc. International Workshop on Parallel and Distributed Computing Issues in Wireless Networks and Mobile Computing, Ft. Lauderdale, Florida (April 2002)Google Scholar
  19. 19.
    Mirza, D., Owrang, M., Schurgers, C.: Energy-efficient Wakeup Scheduling for Maximizing Lifetime of IEEE 802.15.4 Networks. In: Proc. International Conference on Wireless Internet (WICON 2005), Budapest (Hungary), pp. 130–137 (July 2005)Google Scholar
  20. 20.
    Paruchuri, V., Basavaraju, S., Kannan, R., Iyengar, S.: Random Asynchronous Wakeup Protocol for Sensor Networks. In: Proc. of BROADNETS 2004 (2004)Google Scholar
  21. 21.
    Ping, S.: Delay Measurement Time Synchronization for Wireless Sensor Networks. IRB-TR-03-013, Intel Research Berkeley Lab (2003)Google Scholar
  22. 22.
    Raghunathan, V., Schurgers, C., Park, S., Srivastava, M.B.: Energy Aware Wireless Microsensor Networks. IEEE Signal Processing Magazine 19(2), 40–50 (2002)CrossRefGoogle Scholar
  23. 23.
    Rhee, I., Warrier, A., Aia, M., Min, J.: Z-MAC: a Hybrid MAC for Wireless Sensor Networks. In: Proc. ACM SenSys 2005, S. Diego (USA) (November 2005)Google Scholar
  24. 24.
    Schurgers, C., Tsiatsis, V., Srivastava, M.B.: STEM: Topology Management for Energy Efficient Sensor Networks. In: Proc. of the IEEE Aerospace Conference 2002, Big Sky, MT, March 10-15 (2002)Google Scholar
  25. 25.
    Sivrikaya, F., Yener, B.: Time Synchronization in Sensor Networks: A Survey. IEEE Network 18(4), 45–50 (2004)CrossRefGoogle Scholar
  26. 26.
    Sohrabi, K., Gao, J., Ailawadhi, V., Pottie, G.J.: Protocols for Self-organization of a Wireless Sensor Network. IEEE Personal Communications 7(5) (October 2000)Google Scholar
  27. 27.
    TinyDB: a Declarative Database for Sensor Networks,
  28. 28.
    Tmote Sky Platform, MoteIV Corporation,
  29. 29.
    Woo, A., Tong, T., Culler, D.: Taming the underlying challenges of reliable multhop routing in sensor networks. In: Proc. of the 1st ACM Conference on Embedded Networked Sensor Systems (SenSys 2003), Los Angeles, California, pp. 14–27 (November 2003)Google Scholar
  30. 30.
    Yang, X., Vaidya, N.: A Wakeup Scheme for Sensor Networks: Achieving Balance between Energy Saving and End-to-end Delay. In: Proc. of the IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS 2004), pp. 19–26 (2004)Google Scholar
  31. 31.
    Zhang, Z.: Investigation of Wireless Sensor Networks for Precision Agriculture. In: Proceedings 2004 ASABE Annual Meeting. American Society of Agricultural and Biological Engineers (2004)Google Scholar
  32. 32.
    Zheng, R., Hou, J., Sha, L.: Asynchronous Wakeup for Ad Hoc Networks. In: Proc. ACM MobiHoc 2003, Annapolis (USA), June 1-3, pp. 35–45 (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Giuseppe Anastasi
    • 1
  • Marco Conti
    • 2
  • Mario Di Francesco
    • 3
    • 4
  • Ilaria Giannetti
    • 1
  1. 1.Dept. of Information Eng.Univ. of PisaItaly
  2. 2.Institute of Informatics and Telematics, CNRItaly
  3. 3.Dept. of Computer Science and EngineeringAalto UniversityFinland
  4. 4.CReWMaNUniversity of Texas at ArlingtonUSA

Personalised recommendations