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Energy Efficiency

, Volume 10, Issue 2, pp 331–357 | Cite as

Quality of service optimization in solar cells-based energy harvesting wireless sensor networks

  • Soledad EscolarEmail author
  • Stefano Chessa
  • Jesús Carretero
Original Article

Abstract

In energy harvesting wireless sensor networks, the sensors are able to harvest energy from the environment to recharge their batteries and thus prolong indefinitely their activities. Widely used energy harvesting systems are based on solar cells, which are predictable (i.e., their energy production can be predicted in advance). However, since the energy production of solar cells is not constant during the day, and it is null at night time, these systems require algorithms able to balance the energy consumption and production of the sensors. In this framework, we approach the design of a scheduling algorithm for the sensors that selects among a set of available tasks for the sensors (each assigned with a given quality of service), in order to keeping the sensors energy neutral, i.e., the energy produced during a day exceeds the energy consumed in the same time frame, while improving the overall quality of service. The algorithm solves an optimization problem by using a greedy approach that can be easily implemented on low-power sensors. The simulation results demonstrate that our approach is able to improve the quality of the overall scheduling plan of all networked sensors and that it actually maintains them energy neutral.

Keywords

Energy harvesting systems Wireless sensor networks Energy efficiency Quality of service Solar cells 

Notes

Acknowledgment

This work has been funded by the Programme for Research and Innovation of University of Castilla-La Mancha, co-financed by the European Social Fund (Resolution of 25 August 2014).

References

  1. Akkaya, K., & Younis, M. (2005). Energy and qos aware routing in wireless sensor networks. Cluster Computing, 8(2–3), 179–188.CrossRefGoogle Scholar
  2. Alippi, C., Anastasi, G., Francesco, M.D., & Roveri, M. (2010). An adaptive sampling algorithm for effective energy management in wireless sensor networks with energy-hungry sensors. IEEE Transactions on Instrumentation and Measurement, 59(2), 335–344. doi: 10.1109/TIM.2009.2023818.CrossRefGoogle Scholar
  3. Baronti, P., Pillai, P., Chook, V.W., Chessa, S., Gotta, A., & Hu, Y.F. (2007). Wireless sensor networks: a survey on the state of the art and the 802.15.4 and zigbee standards. Computer Communications, 30(7), 1655–1695. Wired/Wireless Internet Communications.CrossRefGoogle Scholar
  4. Barsocchi, P., Chessa, S., Furfari, F., & Potorti, F. (2013). Evaluating ambient assisted living solutions: the localization competition. IEEE Pervasive Computing, 12(4), 72–79. doi: 10.1109/MPRV.2013.23.CrossRefGoogle Scholar
  5. Benini, L., Bogliolo, A., & De Micheli, G. (2000). A survey of design techniques for system-level dynamic power management. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 8(3), 299–316. doi: 10.1109/92.845896.CrossRefGoogle Scholar
  6. Bergonzini, C., Brunelli, D., & Benini, L. (2009). Algorithms for harvested energy prediction in batteryless wireless sensor networks. In 3rd international workshop on advances in sensors and interfaces, 2009. IWASI 2009. doi: 10.1109/IWASI.2009.5184785 (pp. 144–149).
  7. Bogliolo, A., Delpriori, S., Lattanzi, E., & Seraghiti, A. (2011). Self-adapting maximum flow routing for autonomous wireless sensor networks. Cluster Computing, 14(1), 1–14. doi: 10.1007/s10586-009-0115-x.CrossRefGoogle Scholar
  8. Chen, J., Díaz, M., Llopis, L., Rubio, B., & Troya, J.M. (2011). A survey on quality of service support in wireless sensor and actor networks: requirements and challenges in the context of critical infrastructure protection. Journal of Network and Computer Applications, 34(4), 1225–1239. Advanced Topics in Cloud Computing.CrossRefGoogle Scholar
  9. Cooper, P. (1969). The absorption of solar radiation in solar stills. Solar Energy, 12.Google Scholar
  10. Escolar, S., Carretero, J., Marinescu, M.C., & Chessa, S. (2014). Estimating energy savings in smart street lighting by using an adaptive control system. International Journal of Distributed Sensor Networks, 2014, 17.Google Scholar
  11. Escolar, S., Chessa, S., & Carretero, J. (2012). Optimization of quality of service in wireless sensor networks powered by solar cells. In 10th ieee international symposium on parallel and distributed processing with applications (p. 8). Madrid.Google Scholar
  12. Escolar, S., Chessa, S., & Carretero, J. (2013). Energy management of networked, solar cells powered, wireless sensors. In Proceedings of the 16th ACM international conference on modeling, analysis & simulation of wireless and mobile systems, MSWiM ’13 (pp. 263–266). New York: ACM.Google Scholar
  13. Escolar, S., Chessa, S., & Carretero, J. (2014). Energy management in solar cells powered wireless sensor networks for quality of service optimization. Personal and Ubiquitous Computing, 18(2), 449–464. doi: 10.1007/s00779-013-0663-1.CrossRefGoogle Scholar
  14. Escolar, S., Chessa, S., & Carretero, J. (2014). Energy-neutral networked wireless sensors. Simulation Modelling Practice and Theory, 43, 1–15. doi: 10.1016/j.simpat.2014.01.002. http://www.sciencedirect.com/science/article/pii/S1569190X14000033.CrossRefGoogle Scholar
  15. Fafoutis, X., & Dragoni, N. (2011). Odmac: an on-demand mac protocol for energy harvesting - wireless sensor networks. In Proceedings of the 8th ACM symposium on performance evaluation of wireless ad hoc, sensor, and ubiquitous networks, PE-WASUN ’11. doi:http://doi.acm.org/10.1145/2069063.2069072 (pp. 49–56). New York: ACM.
  16. Felemban, E., Lee, C.G., & Ekici, E. (2006). Mmspeed: multipath multi-speed protocol for qos guarantee of reliability and. timeliness in wireless sensor networks. IEEE Transactions on Mobile Computing, 5(6), 738–754. doi: 10.1109/TMC.2006.79.CrossRefGoogle Scholar
  17. Hartmann, D.L. (1994). Global physical climatology, international geophysics, 1st edn. Vol. 56. Boston: Academic Press.Google Scholar
  18. Inman, R.H., Pedro, H.T., & Coimbra, C.F. (2013). Solar forecasting methods for renewable energy integration. Progress in Energy and Combustion Science, 39(6), 535–576. doi: 10.1016/j.pecs.2013.06.002. http://www.sciencedirect.com/science/article/pii/S0360128513000294.CrossRefGoogle Scholar
  19. Iyer, R., & Kleinrock, L. (2003). Qos control for sensor networks. In IEEE international conference on communications, 2003. ICC ’03. doi: 10.1109/ICC.2003.1204230, (Vol. 1 pp. 517–521).
  20. Jacobson, M.Z. (2005). Fundamentals of atmospheric modeling, 2nd edn. Cambridge University Press.Google Scholar
  21. Jiang, X., Polastre, J., & Culler, D. (2005). Perpetual environmentally powered sensor networks. In Proceedings of the 4th international symposium on information processing in sensor networks, IPSN ’05. Piscataway: IEEE Press.Google Scholar
  22. Kansal, A., Hsu, J., Zahedi, S., & Srivastava, M.B. (2007). Power management in energy harvesting sensor networks. ACM Transactions on Embedded Computing Systems, 6(4).Google Scholar
  23. Kansal, A., Potter, D., & Srivastava, M.B. (2004). Performance aware tasking for environmentally powered sensor networks. SIGMETRICS Perform Evaluation Review, 32(1), 223–234.CrossRefGoogle Scholar
  24. KL (2014). KL Solar company pvt ltd., http://www.klsolar.com/. India.
  25. Lattanzi, E., & Bogliolo, A. (2011). WSN design for unlimited lifetime, chap. Sustainable energy harvesting technologies - past, present and future. 978-953-307-438-2. InTech.Google Scholar
  26. Lattanzi, E., Regini, E., Acquaviva, A., & Bogliolo, A. (2007). Energetic sustainability of routing algorithms for energy-harvesting wireless sensor networks. Computer Communications, 30 (14–15), 2976–2986. doi: 10.1016/j.comcom.2007.05.035. http://www.sciencedirect.com/science/article/pii/S0140366407002228. Network Coverage and Routing Schemes for Wireless Sensor Networks.CrossRefGoogle Scholar
  27. Libelium (2014). Waspmote. http://www.libelium.com/downloads/documentation/waspmote_datasheet.pdf (Document version: v4.7).
  28. Lin, K., Yu, J., Hsu, J., Zahedi, S., Lee, D., Friedman, J., Kansal, A., Raghunathan, V., & Srivastava, M. (2005). Heliomote: enabling long-lived sensor networks through solar energy harvesting, (pp. 309–309). New York: ACM.Google Scholar
  29. Moser, C., Chen, J.J., & Thiele, L. (2008). An energy management framework for energy harvesting embedded systems. Journal on Emerging Technologies in Computing Systems, 6(2), 7:1–7:21.Google Scholar
  30. Moser, C., Chen, J.J., & Thiele, L. (2009). Power management in energy harvesting embedded systems with discrete service levels. International Symposium on Low Power Electronics and Design, 0, 413–418. doi:http://doi.ieeecomputersociety.org/10.1145/1594233.1594338.Google Scholar
  31. NASA (2013). Surface meteorology and solar energy (retscreen). https://eosweb.larc.nasa.gov/sse/RETScreen/.
  32. Piorno, J., Bergonzini, C., Atienza, D., & Rosing, T. (2009). Prediction and management in energy harvested wireless sensor nodes. In 1st international conference on wireless communication, vehicular technology, information theory and aerospace electronic systems technology, 2009. Wireless VITAE 2009. doi: 10.1109/WIRELESSVITAE.2009.5172412 (pp. 6–10).
  33. Polastre, J., Hill, J., & Culler, D. (2004). Versatile low power media access for wireless sensor networks. In Proceedings of the 2nd international conference on embedded networked sensor systems, SenSys ’04 (pp. 95–107). New York: ACM.Google Scholar
  34. Sohrabi, K., Gao, J., Ailawadhi, V., & Pottie, G. (2000). Protocols for self-organization of a wireless sensor network. IEEE Personal Communications, 7(5), 16–27. doi: 10.1109/98.878532.CrossRefGoogle Scholar
  35. Sudevalayam, S., & Kulkarni, P. (2011). Energy harvesting sensor nodes: survey and implications. IEEE Communications Surveys and Tutorials, 13(3), 443–461.CrossRefGoogle Scholar
  36. Vithanage, M., Fafoutis, X., Andersen, C., & Dragoni, N. (2013). Medium access control for thermal energy harvesting in advanced metering infrastructures. In EUROCON, 2013. doi: 10.1109/EUROCON.2013.6624999 (pp. 291–299): IEEE.
  37. Vullers, R., Schaijk, R., Visser, H., Penders, J., & Hoof, C. (2010). Energy harvesting for autonomous wireless sensor networks. IEEE Solid-State Circuits Magazine, 2(2), 29–38. doi: 10.1109/MSSC.2010.936667.CrossRefGoogle Scholar
  38. Xia, F. (2008). Qos challenges and opportunities in wireless sensor/actuator networks. Sensors, 8 (2), 1099–1110. doi: 10.3390/s8021099.CrossRefGoogle Scholar
  39. Yigitel, M.A., Incel, O.D., & Ersoy, C. (2011). Qos-aware MAC protocols for wireless sensor networks: a survey. Computer Networks, 55(8), 1982–2004.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Soledad Escolar
    • 1
    Email author
  • Stefano Chessa
    • 2
  • Jesús Carretero
    • 3
  1. 1.Institute of Technology and Information SystemsUniversity of Castilla-La ManchaCiudad RealSpain
  2. 2.Computer Science DepartmentUniversity of Pisa and ISTI-CNRPisaItaly
  3. 3.Computer Science DepartmentUniversity Carlos III of MadridMadridSpain

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