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Issue No.02 - February (2010 vol.59)
pp: 231-242
Shamik Sengupta , John Jay College of Criminal Justice of the CUNY, New York
Mainak Chatterjee , University of Central Florida, Orlando
Kevin A. Kwiat , Air Force Office of Scientific Research, Rome
In infrastructure-less sensor networks, efficient usage of energy is very critical because of the limited energy available to the sensor nodes. Among various phenomena that consume energy, radio communication is by far the most demanding one. One of the effective ways to limit unnecessary energy loss is to control the power at which the nodes transmit signals. In this paper, we apply game theory to solve the power control problem in a CDMA-based distributed sensor network. We formulate a noncooperative game under incomplete information and study the existence of Nash equilibrium. With the help of this equilibrium, we devise a distributed algorithm for optimal power control and prove that the system is power stable only if the nodes comply with certain transmit power thresholds. We show that even in a noncooperative scenario, it is in the best interest of the nodes to comply with these thresholds. The power level at which a node should transmit, to maximize its utility, is evaluated. Moreover, we compare the utilities when the nodes are allowed to transmit with discrete and continuous power levels; the performance with discrete levels is upper bounded by the continuous case. We define a distortion metric that gives a quantitative measure of the goodness of having finite power levels and also find those levels that minimize the distortion. Numerical results demonstrate that the proposed algorithm achieves the best possible payoff/utility for the sensor nodes even by consuming less power.
Wireless sensor network, game theory, distributed power control, energy efficiency.
Shamik Sengupta, Mainak Chatterjee, Kevin A. Kwiat, "A Game Theoretic Framework for Power Control in Wireless Sensor Networks", IEEE Transactions on Computers, vol.59, no. 2, pp. 231-242, February 2010, doi:10.1109/TC.2009.82
[1] I. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, “A Survey on Sensor Networks,” IEEE Comm. Magazine, vol. 40, no. 8, pp. 102-114, Aug. 2002.
[2] A. Sampath, P.S. Kumar, and J. Holtzman, “Power Control and Resource Management for a Multimedia CDMA Wireless System,” Proc. IEEE Int'l Symp. Personal, Indoor and Mobile Radio Communications (PIMRC), vol. 1, pp. 21-25, Sept. 1995.
[3] R. Yates, “A Framework for Uplink Power Control in Cellular Radio Systems,” IEEE J. Selected Areas in Comm., vol. 13, no. 7, pp.1341-1348, Sept. 1995.
[4] S. Clearwater, Market-Based Control: A Paradigm for Distributed Resource Allocation. World Scientific, 1996.
[5] F. Kelly, A. Maulloo, and D. Tan, “Rate Control in Communications Networks: Shadow Prices, Proportional Fairness and Stability,” J. Operations Research Soc., vol. 49, pp. 237-252, 1998.
[6] P. Key and D. McAuley, “Differential QoS and Pricing in Networks: Where Flow Control Meets Game Theory,” IEE Proc. Software, vol. 146, no. 1, pp. 39-43, Feb. 1999.
[7] H. Lin, M. Chatterjee, S. Das, and K. Basu, “ARC: An Integrated Admission and Rate Control Framework for CDMA Data Networks Based on Non-Cooperative Games,” Proc. Ninth Ann. Int'l Conf. Mobile Computing and Networking, pp. 326-338, 2003.
[8] R. Maheswaran and T. Basar, “Decentralized Network Resource Allocation as a Repeated Noncooperative Market Game,” Proc. 40th IEEE Conf. Decision and Control, vol. 5, pp. 4565-4570, 2001.
[9] M. Stonebraker, R. Devine, M. Kornacker, W. Litwin, A. Pfeffer, A. Sah, and C. Staelin, “An Economic Paradigm for Query Processing and Data Migration in Mariposa” Proc. Third Int'l Conf. Parallel and Distributed Information Systems, pp. 58-67, Sept. 1994.
[10] R. Subrata, A. Zomaya, and B. Landfeldt, “Game-Theoretic Approach for Load Balancing in Computational Grids,” IEEE Trans. Parallel and Distributed Systems, vol. 19, no. 1, pp. 66-76, Jan. 2008.
[11] S. Sengupta and M. Chatterjee, “An Economic Framework for Dynamic Spectrum Access and Service Pricing,” IEEE/ACM Trans. Networking, vol. 17, no. 4, pp. 1200-1213, Aug. 2009.
[12] M. Kubisch, H. Karl, A. Wolisz, L. Zhong, and J. Rabaey, “Distributed Algorithms for Transmission Power Control in Wireless Sensor Networks,” Proc. IEEE Wireless Comm. and Networking Conf., vol. 1, pp. 558-563, 2003.
[13] D. Niyato, E. Hossain, M. Rashid, and V. Bhargava, “Wireless Sensor Networks with Energy Harvesting Technologies: A Game-Theoretic Approach to Optimal Energy Management,” IEEE Wireless Comm., vol. 14, no. 4, pp. 90-96, Aug. 2007.
[14] J. Nash, “Equilibrium Points in N-Person Games,” Proc. Nat'l Academy of Sciences, vol. 36, pp. 48-49, 1950.
[15] S. Buchegger and J. Le Boudec, “Performance Analysis of the CONFIDANT Protocol,” Proc. Third ACM Int'l Symp. Mobile Ad Hoc Networking & Computing, pp. 226-236, 2002.
[16] L. Buttyan and J.P. Hubaux, “Nuglets: A Virtual Currency to Stimulate Cooperation in Selforganized Mobile Ad-Hoc Networks,” Technical Report DSC/2001/001, Swiss Fed. Inst. of Tech nology, Jan. 2001.
[17] W. Wang, M. Chatterjee, and K. Kwiat, “Enforcing Cooperation in Ad Hoc Networks with Unreliable Channel,” Proc. Fifth IEEE Int'l Conf. Mobile Ad-Hoc and Sensor Systems (MASS), pp. 456-462, 2008.
[18] V. Srinivasan, P. Nuggehalli, C. Chiasserini, and R. Rao, “Cooperation in Wireless Ad Hoc Networks,” Proc. IEEE INFOCOM, vol. 2, pp. 808-817, Apr. 2003.
[19] Z. Xidong, C. Yueming, and Z. Heng, “A Game-Theoretic Dynamic Power Management Policy on Wireless Sensor Network” Proc. Int'l Conf. Comm. Technology, pp. 1-4, Nov. 2006.
[20] Z. Jia, M. Chundi, and H. Jianbin, “Game Theoretic Energy Balance Routing in Wireless Sensor Networks” Proc. Chinese Control Conf., pp. 420-424, July 2007.
[21] S. Olariu, Q. Xu, and A. Zomaya, “An Energy-Efficient Self-Organization Protocol for Wireless Sensor Networks” Proc. Intelligent Sensors, Sensor Networks, and Information Processing Conf., pp. 55-60, Dec. 2004.
[22] M. Maskery and V. Krishnamurthy, “Decentralized Adaptation in Sensor Networks: Analysis and Application of Regret-Based Algorithms” Proc. 46th IEEE Conf. Decision and Control, pp. 951-956, Dec. 2007.
[23] J. Chang and L. Tassiulas, “Maximum Lifetime Routing in Wireless Sensor Networks,” IEEE/ACM Trans. Networking, vol. 12, no. 4, pp. 609-619, Aug. 2004.
[24], 2009.
[25] L. Blazevic, L. Buttyan, S. Capkun, S. Giordiano, J. Hubaux, and J. Le Boudec, “Self-Organization in Mobile Ad-Hoc Networks: The Approach of Terminodes,” IEEE Comm. Magazine, vol. 39, no. 6, pp. 166-174, June 2001.
[26] J. Crowcroft, R. Gibbens, F. Kelly, and S. Ostring, “Modelling Incentives for Collaboration in Mobile Ad Hoc Networks,” Proc. Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt '03), 2003.
[27] S. Marti, T.J. Giuli, K. Lai, and M. Baker, “Mitigating Routing Misbehavior in Mobile Ad Hoc Networks,” Proc. Sixth Ann. Int'l Conf. Mobile Computing and Networking, pp. 255-265, 2000.
[28] P. Michiardi and R. Molva, “Core: A Collaborative Reputation Mechanism to Enforce Node Cooperation in Mobile Ad Hoc Networks,” Proc. Comm. and Multimedia Security Conf., 2002.
[29] E. Baccarelli, M. Biagi, and C. Pelizzoni, “A Distributed Spatial Signal-Shaping for the Competitively Optimal Throughput-Maximization of MIMO ‘Ad-Hoc’ Networks,” IEEE Trans. Vehicular Technology, vol. 55, no. 6, pp. 1862-1876, Nov. 2006.
[30] P. Michiardi and R. Molva, “A Game Theoretical Approach to Evaluate Cooperation Enforcement Mechanisms in Mobile Ad Hoc Networks,” Proc. Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt '03), 2003.
[31] F. Meshkati, H. Poor, S. Schwartz, and N. Mandayam, “An Energy-Efficient Approach to Power Control and Receiver Design in Wireless Data Networks,” IEEE Trans. Comm., vol. 53, no. 11, pp. 1885-1894, Nov. 2005.
[32] S. De, C. Qiao, D. Pados, M. Chatterjee, and S. Philip, “An Integrated Cross-Layer Study of Wireless CDMA Sensor Networks,” IEEE J. Selected Areas in Comm. (JSAC), Special Issue on Quality of Service Delivery in Variable Topology Networks, vol.22, no. 7, pp. 1271-1285, Sept. 2004.
[33] A. Garcia, Probability and Random Processes for Electrical Engineering. Addision-Wesley, 1989.
[34] D. Fundenberg and J. Tirole, Game Theory. MIT Press, 1991.
[35] J. Neumann and O. Morgenstern, Theory of Games and Economic Behavior. Princeton Univ. Press, 1944.
[36] Y. Xing and R. Chandramouli, “Distributed Discrete Power Control for Bursty Transmissions over Wireless Data Networks,” Proc. IEEE Int'l Conf. Comm. (ICC), vol. 1, pp. 139-143, 2004.
[37] “Cisco Systems Inc. Data Sheet for Aironet,” 2004.
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