Analysis and optimization of duty-cycle in preamble-based random access networks
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Duty-cycling has been proposed as an effective mechanism for reducing the energy consumption in wireless sensor networks (WSNs). Asynchronous duty-cycle protocols where the receiver wakes up periodically to check whether there is a transmission and the sender transmits preambles to check if the receiver is awake are widely used in WSNs due to the elimination of complex control mechanisms for topology discovery and synchronization. However, the intrinsic simplicity of the asynchronous mechanism has the drawback of smaller energy saving potential that requires the optimization of the duty cycle parameters. In this paper, we propose a novel method for the optimization of the duty-cycle parameters in preamble-based random access networks based on the accurate modeling of delay, reliability and energy consumption as a function of listen time, sleep time, traffic rate and medium access control (MAC) protocol parameters. The challenges for modeling are the random access MAC and the sleep policy of the receivers, which make it impossible to determine the exact time of data packet transmissions, and thus difficult to investigate the performance indicators given by the delay, reliability and energy consumption to successfully receive packets. An analysis of these indicators is developed as a function of the relevant parameters of the network and it is used in the minimization of the energy consumption subject to delay and reliability requirements. The optimization provides significant reduction of the energy consumption compared to the previously proposed protocols in the literature.
KeywordsWireless sensor networks MAC IEEE 802.15.4 Duty cycle Optimization
Carlo Fischione acknowledges the support the Swedish Research Council, the EU STREP project HydroBioNets, and the EU NoE Hycon2. Sinem Coleri Ergen acknowledges the support of the Marie Curie Reintegration Grant IVWSN, PIRG06-GA-2009-256441.
- 1.Fischione, C., Coleri Ergen, S., Park, P., Johansson, K. H., & Sangiovanni-Vincentelli, A. (2009). Medium access control analytical modeling and optimization in unslotted IEEE 802.15.4 wireless sensor networks. In IEEE SECON.Google Scholar
- 3.IEEE 802.15.4 standard: wireless medium access control and physical layer specifications for low-rate wireless personal area networks, IEEE. (2006). http://www.ieee802.org/15/pub/TG4.html.
- 4.Routing Over Low power and Lossy networks. http://www.ietf.org/dyn/wg/charter/roll-charter.html.
- 6.Xu, Y., Heidemann, J., & Estrin, D. (2001). Geography-informed energy conservation for ad hoc routing. In ACM MobiCom.Google Scholar
- 7.Chen, B., Jamieson, K., Balakrishnan, H., & Morris, R. (2001). Span: An energy-efficient coordination algorithm for topology maintenance in ad hoc wireless networks. In ACM MobiCom.Google Scholar
- 9.Van Dam, T., & Langendoen, K. (2003). An adaptive energy-efficient MAC protocol for wireless sensor networks. In ACM conference on embedded networked sensor systems.Google Scholar
- 12.Polastre, J., Hill, J., & Culler, D. (2004). Versatile low power media access for wireless sensor networks. In ACM SenSys.Google Scholar
- 13.The TinyOS community forum. http://www.tinyos.net.
- 14.Buettner, M., Yee, G., Anderson, E., & Han, R. (2006). X-MAC: A short preamble MAC protocol for duty-cycled wireless sensor networks. In ACM SenSys.Google Scholar
- 18.Ocakoglu, O., & Ercetin, O. (2006). Energy efficient random sleep awake schedule design. IEEE Communications Letters, 10(7), 528–530.Google Scholar
- 23.Sun, Y., Gurewitz, O., & Johnson, D. B. (2008). RI-MAC: A receiver initiated asynchronous duty cycle MAC protocol for dynamic traffic loads in wireless sensor networks. In ACM SenSys.Google Scholar
- 25.Sun, Y., Gurewitz, O., Du, S., Tang, L., & Johnson, D. B. (2009). ADB: An efficient multihop broadcast protocol based on asynchronous duty-cycling in wireless sensor networks. In ACM SenSys.Google Scholar
- 28.Kim, J., Lin, X., & Shroff, N. B. (2010). Minimizing the delay and maximizing lifetime for wireless sensor networks with anycast. IEEE Transactions on Networking, 12(2), 515–528.Google Scholar
- 31.IEEE 802.15 task group 4e: wireless medium access control and physical layer specifications for low-Rate wireless personal area networks, IEEE. (2010). http://www.ieee802.org/15/pub/TG4e.html.
- 35.ISA-100.11a-2009. (2009). Wireless systems for industrial automation: Process control and related applications.Google Scholar
- 40.Wu, H., Peng, Y., Long, K., Cheng, S., & Ma, J. (2002). Performance of reliable transport protocol over IEEE 802.11 wireless LAN: Analysis and enhancement. In IEEE INFOCOM.Google Scholar
- 42.Papoulis, A. (1991). Probability, random variables, and stochastic processes. New York: Mc Graw Hill.Google Scholar
- 44.Tmote Sky Data Sheet, Moteiv. (2006). http://www.moteiv.com/products/docs/tmote-sky-datasheet.pdf.
- 45.Fischione, C., Coleri Ergen, S., Park, P., Johansson, K. H., & Sangiovanni-Vincentelli, A. (2009). Medium access control analytical modeling and optimization in unslotted IEEE 802.15.4 wireless sensor networks. Sweden: KTH. http://www.ee.kth.se, TRITA-EE 2009:005.
- 46.Bertsekas, D. P. (2004). Nonlinear programming. Belmont: Athena Scientific.Google Scholar