An Interactive Context-aware Power Management Technique for Optimizing Sensor Network Lifetime

Jinseok Yang, Sameer Tilak, Tajana S. Rosing


A key problem in sensor networks equipped with renewable energy sources is deciding how to allocate energy to various tasks (sensing, communication etc.) over time so that the deployed network continues to gather high-quality data. The state-of-the-art energy allocation algorithm takes into account current battery level and harvesting energy and fairly allocates as much energy as possible along the time dimension. In this paper we show that by not considering application-context this approach leads to very high and uniform sampling rates. However, sampling the environment at fixed predefined intervals is neither possible (need to accommodate system failures) nor desirable (sampling rate might not capture an important event with desired fidelity). To that end, in this paper we propose a novel interactive power management technique that adapts sampling rate as a function of both application-level context (e.g., user request) and system-level context (e.g harvesting energy availability). We vary several key parameters including application request patterns, geographic locations, time slot length, battery end point voltage and evaluate the performance of our approach in terms of energy efficiency and accuracy. Our simulations use sensor data and system specifications (battery and solar panel specs, sensing and communication costs) from a real sensor network deployment. Our results show that the proposed approach saves significant amounts of energy by avoiding oversampling when application does not need it while using this saved energy to support sampling at high rates to capture events with necessary fidelity when needed. The computational complexity of our approach is lower (O(n)) than the state-of-the-art noninteractive energy allocation algorithm (O(n2)).


  1. Dcm005 batter specification. https://www. info/specs/ dcm0055.%pdf.
  2. (2013). Creon, the coral reef environmental observatory network.
  3. (2015). Gleon, the global lake ecological observatory network.
  4. (2015). Instapark solar panel. solar-power-panels.
  5. Cerpa, A., Elson, J., Estrin, D., Girod, L., Hamilton, M., and Zhao, J. (2001). Habitat monitoring: Application driver for wireless communications technology. volume 31, pages 20-41, New York, NY, USA. ACM.
  6. Chang, M. and Bonnet, P. (2010). Meeting ecologists' requirements with adaptive data acquisition. In Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems, SenSys, pages 141-154, New York, NY, USA. ACM.
  7. Chen, J., Cao, X., Cheng, P., Xiao, Y., and Sun, Y. (2010). Distributed collaborative control for industrial automation with wireless sensor and actuator networks. volume 57, pages 4219-4230.
  8. Doerffel, D. and Sharkh, S. A. (2006). A critical review of using the peukert equation for determining the remaining capacity of lead-acid and lithium-ion batteries. volume 155, pages 395 - 400.
  9. Gorlatova, M., Wallwater, A., and Zussman, G. (2011). Networking low-power energy harvesting devices: Measurements and algorithms. In INFOCOM, Proceedings IEEE, pages 1602-1610.
  10. Haque, M., Matsumoto, N., and Yoshida, N. (2009). Context-aware multilayer hierarchical protocol for wireless sensor network. In Sensor Technologies and Applications, SENSORCOMM. Third International Conference on, pages 277-283.
  11. Hui, J. W. and Culler, D. (2004). The dynamic behavior of a data dissemination protocol for network programming at scale. In Proceedings of the 2nd International Conference on Embedded Networked Sensor Systems, SenSys, pages 81-94, New York, NY, USA. ACM.
  12. Kansal, A., Hsu, J., Zahedi, S., and Srivastava, M. B. (2007). Power management in energy harvesting sensor networks. volume 6, New York, NY, USA. ACM.
  13. Koo, B., Won, J., Park, S., and Eom, H. (2009). Paar: A routing protocol for context-aware services in wireless sensor-actuator networks. In Internet, AH-ICI. First Asian Himalayas International Conference on, pages 1-7.
  14. Levis, P. and Culler, D. (2004). The firecracker protocol. In Proceedings of the 11th Workshop on ACM SIGOPS European Workshop, EW 11, New York, NY, USA. ACM.
  15. Mainwaring, A., Culler, D., Polastre, J., Szewczyk, R., and Anderson, J. (2002). Wireless sensor networks for habitat monitoring. In Proceedings of the 1st ACM International Workshop on Wireless Sensor Networks and Applications, WSNA, pages 88-97, New York, NY, USA. ACM.
  16. Naik, V., Arora, A., Sinha, P., and Zhang, H. (2007). Sprinkler: A reliable and energy efficient data dissemination service for extreme scale wireless networks of embedded devices. volume 6, pages 777-789.
  17. Piorno, J., Bergonzini, C., Atienza, D., and Rosing, T. (2009). Prediction and management in energy harvested wireless sensor nodes. In Wireless Communication, Vehicular Technology, Information Theory and Aerospace Electronic Systems Technology, Wireless VITA. 1st International Conference on, pages 6- 10.
  18. Tutuncuoglu, K. and Yener, A. (2012). Optimum transmission policies for battery limited energy harvesting nodes. volume 11, pages 1180-1189.
  19. Wood, A., Stankovic, J., Virone, G., Selavo, L., He, Z., Cao, Q., Doan, T., Wu, Y., Fang, L., and Stoleru, R. (2008). Context-aware wireless sensor networks for assisted living and residential monitoring. volume 22, pages 26-33.
  20. Zhou, H.-Y. and Hou, K.-M. (2007). Civic: An powerand context-aware routing protocol for wireless sensor networks. In Wireless Communications, Networking and Mobile Computing, 2007. WiCom 2007. International Conference on, pages 2771-2774.

Paper Citation

in Harvard Style

Yang J., Tilak S. and Rosing T. (2016). An Interactive Context-aware Power Management Technique for Optimizing Sensor Network Lifetime . In Proceedings of the 5th International Confererence on Sensor Networks - Volume 1: SENSORNETS, ISBN 978-989-758-169-4, pages 69-76. DOI: 10.5220/0005728600690076

in Bibtex Style

author={Jinseok Yang and Sameer Tilak and Tajana S. Rosing},
title={An Interactive Context-aware Power Management Technique for Optimizing Sensor Network Lifetime},
booktitle={Proceedings of the 5th International Confererence on Sensor Networks - Volume 1: SENSORNETS,},

in EndNote Style

JO - Proceedings of the 5th International Confererence on Sensor Networks - Volume 1: SENSORNETS,
TI - An Interactive Context-aware Power Management Technique for Optimizing Sensor Network Lifetime
SN - 978-989-758-169-4
AU - Yang J.
AU - Tilak S.
AU - Rosing T.
PY - 2016
SP - 69
EP - 76
DO - 10.5220/0005728600690076