Jason Hsu
Aman Kansal
ABSTRACT
Harvesting energy from the environment is feasible in many applications to ameliorate the energy limitations in sensor networks. In this paper, we present an adaptive duty cycling algorithm that allows energy harvesting sensor nodes to autonomously adjust their duty cycle according to the energy availability in the environment. The algorithm has three objectives, namely (a) achieving energy neutral operation, i.e., energy consumption should not be more than the energy provided by the environment, (b) maximizing the system performance based on an application utility model subject to the above energy-neutrality constraint, and (c) adapting to the dynamics of the energy source at run-time. We present a model that enables harvesting sensor nodes to predict future energy opportunities based on historical data. We also derive an upper bound on the maximum achievable performance assuming perfect knowledge about the future behavior of the energy source. Our methods are evaluated using data gathered from a prototype solar energy harvesting platform and we show that our algorithm can utilize up to 58% more environmental energy compared to the case when harvesting-aware power management is not used.
- R Ramanathan, and R Hain, "Toplogy Control of Multihop Wireless Networks Using Transmit Power Adjustment" in Proc. Infocom. Vol 2. 26-30 pp. 404--413. March 2000Google Scholar
- T.A. Pering, T.D. Burd, and R. W. Brodersen, " The simulation and evaluation of dynamic voltage scaling algorithms", in Proc. ACM ISLPED, pp. 76--81, 1998 Google ScholarDigital Library
- L. Benini and G. De Micheli, Dynamic Power Management: Design Techniques and CAD Tools. Kluwer Academic Publishers, Norwell, MA, 1997. Google ScholarDigital Library
- John Kymisis, Clyde Kendall, Joseph Paradiso, and Neil Gershenfeld. Parasitic power harvesting in shoes. In ISWC, pages 132--139. IEEE Computer Society press, October 1998. Google ScholarDigital Library
- Nathan S. Shenck and Joseph A. Paradiso. Energy scavenging with shoe-mounted piezoelectrics. IEEE Micro, 21(3):30--42, May-June 2001. Google ScholarDigital Library
- T Starner. Human-powered wearable computing. IBM Systems Journal, 35(3-4), 1996. Google ScholarDigital Library
- Mohammed Rahimi, Hardik Shah, Gaurav S. Sukhatme, John Heidemann, and D. Estrin. Studying the feasibility of energy harvesting in a mobile sensor network. In ICRA, 2003.Google ScholarCross Ref
- Chris Melhuish. The ecobot project. www.ias.uwe.ac.uk/energy autonomy/EcoBot web page.html.Google Scholar
- Jan M.Rabaey, M. Josie Ammer, Julio L. da Silva Jr., Danny Patel, and Shad Roundy. Picoradio supports ad hoc ultra-low power wireless networking. IEEE Computer, pages 42--48, July 2000. Google ScholarDigital Library
- Joseph A. Paradiso and Mark Feldmeier. A compact, wireless, self-powered pushbutton controller. In ACM Ubicomp, pages 299--304, Atlanta, GA, USA, September 2001. Springer-Verlag Berlin Heidelberg. Google ScholarDigital Library
- SE Wright, DS Scott, JB Haddow, andMA Rosen. The upper limit to solar energy conversion. volume 1, pages 384 -- 392, July 2000.Google Scholar
- Darpa energy harvesting projects. http://www.darpa.mil/dso/trans/energy/projects.html.Google Scholar
- Werner Weber. Ambient intelligence: industrial research on a visionary concept. In Proceedings of the 2003 international symposium on Low power electronics and design, pages 247--251. ACM Press, 2003. Google ScholarDigital Library
- V Raghunathan, A Kansal, J Hsu, J Friedman, and MB Srivastava, "Design Considerations for Solar Energy Harvesting Wireless Embedded Systems," (IPSN/SPOTS), April 2005. Google ScholarDigital Library
- Xiaofan Jiang, Joseph Polastre, David Culler, Perpetual Environmentally Powered Sensor Networks, (IPSN/SPOTS), April 25-27, 2005. Google ScholarDigital Library
- Chulsung Park, Pai H. Chou, and Masanobu Shinozuka, "DuraNode: Wireless Networked Sensor for Structural Health Monitoring," to appear in Proceedings of the 4th IEEE International Conference on Sensors, Irvine, CA, Oct. 31 - Nov. 1, 2005.Google Scholar
- Aman Kansal and Mani B. Srivastava. An environmental energy harvesting framework for sensor networks. In International symposium on Low power electronicsand design, pages 481--486. ACM Press, 2003. Google ScholarDigital Library
- Thiemo Voigt, Hartmut Ritter, and Jochen Schiller. Utilizing solar power in wireless sensor networks. In LCN, 2003. Google ScholarDigital Library
- A. Kansal, J. Hsu, S. Zahedi, and M. B. Srivastava. Power management in energy harvesting sensor networks. Technical Report TR-UCLA-NESL-200603-02, Networked and Embedded Systems Laboratory, UCLA, March 2006.Google Scholar
Index Terms
- Adaptive duty cycling for energy harvesting systems
Recommendations
Energy-Harvesting Wireless Sensor Networks (EH-WSNs): A Review
Wireless Sensor Networks (WSNs) are crucial in supporting continuous environmental monitoring, where sensor nodes are deployed and must remain operational to collect and transfer data from the environment to a base-station. However, sensor nodes have ...
Design and power management of energy harvesting embedded systems
ISLPED '06: Proceedings of the 2006 international symposium on Low power electronics and designHarvesting energy from the environment is a desirable and increasingly important capability in several emerging applications of embedded systems such as sensor networks, biomedical implants, etc. While energy harvesting has the potential to enable near-...
Adaptive Duty Cycle Control for Optimal Stochastic Energy Harvesting
Energy harvesting in wireless sensors is expected to improve the environmental footprint of sensors by reducing the polluting need of using and replacing batteries through autarkic operation. Recent advances in energy harvesting technology lead towards ...
Comments