Abstract
Wireless sensor networks play a key role in monitoring remote or inhospitable physical environments. One of the most important constraints is the energy efficiency problem. Power conservation and power management must be taken into account at all levels of the sensor networks system hierarchy. Especially, DPM (Dynamic Power Management) technology, which shuts down the devices when not needed and wake them up when necessary, has been widely used in sensor networks. In this paper, we modify the sleep state policy developed by Simunic and Chdrakasan in [1] and deduce a new threshold satisfies the sleep-state transition policy. Nodes in deeper sleep states consume lower energy while asleep, but require longer delays and higher latency costs to awaken. Implementing dynamic power management with considering the battery status and probability of event generation will reduce the energy consumption and prolong the whole lifetime of the sensor networks. The sensor network consumed less energy in our simulation than that in [1].
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References
Sinha, A., Chandrakasan, A.: Dynamic Power Management in Wireless Sensor Networks. IEEE Design and Test of Computers 18(2), 62–74 (2001)
Calhoun, B.H., Daly, D.C., Verma, N., Finchelstein, D., Wentzloff, D.D., Wang, A., Cho, S.-H., Chandrakasan, A.P.: Design Considerations for Ultra-low Energy Wireless Microsensor Nodes. IEEE Transactions on Computers (June 2005)
Sohrabi, K., Gao, J., Ailawadhi, V., Pottie, G.J.: Protocols for Self-Organization of a Wireless Sensor Network. IEEE Personal Communications 7(5), 16–27 (2000)
Raghunathan, V., Schurgers, C., Park, S., Srivastava, M.B.: Energy-Aware Wireless Microsensor Networks. IEEE Signal Processing Magazine 19(2), 40–50 (2002)
Hill, J., Szewczyk, R., Woo, A., Hollar, S., Culler, D.E., Pister, K.: System Architecture Directions for Networked Sensors. Architectural Support for programming Languages and Operating Systems, pp. 93–104 (2000), Available at: http://www.tinyos.net/papers/tos.pdf
Benini, L., Micheli, G.D.: Dynamic Power Management: Design Techniques and CAD Tools. Kluwer Academic, NY (1997)
Akyildiz, I.F., Su, W., Sankarasubramaniam, Y., Cayirci, E.: A Survey on Sensor Networks. IEEE Communications Magazine 40(8), 102–114 (2002)
Chung, E.Y., Benini, L., Micheli, G.D.: Dynamic Power Management Using adaptive Learning Tree. In: International Conference on Computer-Aided Design (ICCAD), November 7-11, 1999, pp. 274–279 (1999)
Zuquim, A.L.A.P., Vieira, L.F.M., Vieira, M.A., Vieira, A.B., Carvalho, H.S., Nacif, J.A., Coelho Jr., C.N., da Silva Jr., D.C., Fernandes, A.O., Loureiro, A.A.F.: Efficient Power Management in Real-time Embedded Systems. In: IEEE International Conference on Emerging Technologies and Factory Automation-RTFA 2003, September 16-19, 2003, vol. 1, pp. 496–505 (2003)
IBM and MontaVista Software: Dynamic Power Management for Embedded System. Ver.1.1 (November 19, 2002), Available at: http://www.research.ibm.com/arl/projects/papers/DPM-V1.1.pdf
Chiasserini, C.F., Rao, R.R.: Improving energy saving in wireless systems by using dynamic power management. IEEE Transactions on wireless Communications 2(5), 1090–1100 (2003)
Brock, B., Rajamani, K.: Dynamic Power Management for Embedded System. In: IEEE International System-On-Chip (SOC) Conference, September 17-20, 2003, pp. 416–419 (2003)
Calhoun, B., Chandrakasan, A.P.: Standby Power Reduction Using Dynamic Voltage Scaling and Canary Flip-Flop Structures. IEEE Journal of Solid-State Circuits 39(9) (September 2004)
Hui, J., Ren, Z., Krogh, B.H.: Sentry-based Power Management in Wireless Sensor Networks. In: Second International Workshop on Information Processing in Sensor Networks, April 2003, pp. 458–472 (2003)
Passos, R.M., Coelho Jr., C.J.N., Loureiro, A.A.F., Mini, R.A.F.: Dynamic Power Management in Wireless Sensor Networks: An Application-Driven Approach. In: Second Annual Conference on Wireless On-demand Network Systems and Services (WONS 2005), January 2005, pp. 109–118 (2005)
Luo, R.C., Tu, L.C., Chen, O.: An Efficient Dynamic Power Management Policy on Sensor Network. In: Processing of the 19th international conference on advanced information networking and applications (AINA 2005), March 28-30, 2005, vol. 2, pp. 341–344 (2005)
Hewlett-Packard, Intel, Microsoft, Phoenix, and Toshiba, Advanced Configuration and Power Interface (ACPI): an Open Industry Specification - Revision 3.0a, Available at: http://www.acpi.info/
Henzinger, T.A.: The Theory of Hybrid Automata. In: Eleventh Annual IEEE Symposium on Logic in Computer Science (LICS), July 1996, pp. 278–292 (1996)
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Lin, C., He, Y., Xiong, N., Yang, L.T. (2006). Improved Dynamic Power Management in Wireless Sensor Networks. In: Ma, J., Jin, H., Yang, L.T., Tsai, J.JP. (eds) Ubiquitous Intelligence and Computing. UIC 2006. Lecture Notes in Computer Science, vol 4159. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11833529_46
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DOI: https://doi.org/10.1007/11833529_46
Publisher Name: Springer, Berlin, Heidelberg
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