ABSTRACT In WSNs, energy conservation is the primary goal, while throughput and delay are less important. This re-sults in a tradeoff between performance (e.g., throughput, delay, jitter, and packet-loss-rate) and energy con-sumption. In this paper, the problem of energy-efficient MAC protocols in WSNs is modeled as a game-theoretic constraint optimization with multiple objectives. After introducing incompletely cooperative game theory, based on the estimated game state (e.g., the number of competing nodes), each node independ-ently implements the optimal equilibrium strategy under the given constraints (e.g., the used energy and QoS requirements). Moreover, a simplified game-theoretic constraint optimization scheme (G-ConOpt) is pre-sented in this paper, which is easy to be implemented in current WSNs. Simulation results show that G-ConOpt can increase system performance while still maintaining reasonable energy consumption.
Cite this paper
nullL. ZHAO, L. GUO, C. Li]] and H. ZHANG, "An Energy-Efficient MAC Protocol for WSNs: Game-Theoretic Constraint Optimization with Multiple Objectives," Wireless Sensor Network, Vol. 1 No. 4, 2009, pp. 358-364. doi: 10.4236/wsn.2009.14044.
 I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, et al., “Wireless sensor networks: a survey,” Computer Networks, Vol. 38, No. 4, pp. 393–422, March 2002.
W. Ye, J. Heidemann, and D. Estrin, “An energy-efficient MAC protocol for wireless sensor networks,” INFOCOM, New York, Vol. 3, pp. 1567–1576, June 2002.
T. Dam and K. Langendoen, “An adaptive energy- efficient MAC protocol for wireless sensor networks,”
ACM SenSys, Los Angeles CA, November 2003.
J. Polastre, J. Hill, and D. Celler, “Versatile low power media access for wireless sensor networks,” ACM SenSys, USA, pp. 95–107, November 2004.
A. El-Hoiydi and J. D. Decotignie, “WiseMAC: An ultra low power MAC protocol for the downlink of infrastructure wireless sensor networks,” ISCC, Egypt. pp. 244–251, June 2004.
P. Lin, C. Qiao, and X. Wang, “Medium access control with dynamic duty cycle for sensor networks,” WCNC, Atlanta, Georgia, March 2004.
T. van Dam, K. Langendoen, “A adaptive energy-efficient MAC protocol for wireless sensor networks,” ACM SenSys, USA, pp 171–180, November 2003.
P. D. Straffin, “Game theory and strategy,” The Mathematical Association of America, 1993.
A. Agah, S. K. Das, and K. A. Basu, “Game theory based approach for security in wireless sensor networks,” IPCCC, USA, pp. 259–263, April 2004.
R. Kannan, S. Sarangi, and S. S. Lyengar, “Sensor-centric energy-constrained reliable query routing for wireless sensor networks,” Journal of Parallel and Distributed Computing, Vol. 64, No. 7, pp. 839–852, July 2004.
S. Sengupta and M. Chatterjee, “Distributed power control in sensor networks: A game theoretic approach,” IWDC, India, pp. 508–519, December 2004.
X. Zhang, Y. Cai, and H. Zhang, “A game-theoretic dynamic power management policy on wireless sensor network,” ICCT, China, pp. 1–4, November 2006.
L. Zhao, L. Guo, K. Yang, and H. Zhang, “An Energy- efficient MAC Protocol for WSNs: Game-theoretic constraint optimization,” IEEE International Conference on Communication Systems, China, pp. 114–118, November 2008.
L. Zhao, L. Guo, J. Zhang, and H. Zhang, “A Game- theoretic MAC protocol for wireless sensor network,” Journal of IET Communications, Vol. 3, No. 8, pp. 1274–1283, August 2008.
M. S. Garey and D. S. Johnson, “Computers and Intractability: Guide to the theory of NP-completeness,” W. H. Freeman, New York, 1979.
T. Vercauteren, A. L. Toledo, and X. Wang, “Batch and sequential bayesian estimators of the number of active terminals in an IEEE 802.11 network,” IEEE Trans. on Signal Processing, Vol. 55, No. 2, pp. 437–450, January 2007.
G. Bianchi and I. Tinnirello, “Kalman filter estimation of the number of competing terminals in an IEEE 802.11 network,” IEEE INFOCOM, Vol. 2, San Francisco, pp. 844–852, March 2003.
G. Bianchi, “Performance Analysis of the IEEE 802.11 distributed coordination function,” IEEE JSAC, Vol. 18, No. 3, pp. 535–547, March 2000.