The Community for Technology Leaders
RSS Icon
Issue No.09 - September (2008 vol.7)
pp: 1057-1070
The problem of topology control is to assign per-node transmission power such that the resulting topology is energy-efficient and satisfies certain global properties such as connectivity. The conventional approach to achieve these objectives is based on the fundamental assumption that nodes are socially responsible. We examine the following question: if nodes behave in a selfish manner, how does it impact the overall connectivity and energy consumption in the resulting topologies? We pose the above problem as a non-cooperative game and use game-theoretic analysis to address it. We study Nash equilibrium properties of the topology control game and evaluate the efficiency of the induced topology when nodes employ a greedy best response algorithm. We show that even when the nodes have complete information about the network, the steady state topologies are suboptimal. We propose a modified algorithm based on a better response dynamic and show that this algorithm is guaranteed to converge to energy-efficient and connected topologies. Moreover, the node transmit power levels are more evenly distributed and the network performance is comparable to that obtained from centralized algorithms.
Network topology, Network management, Algorithm/protocol design and analysis
Ramakant S. Komali, Allen B. MacKenzie, Robert P. Gilles, "Effect of Selfish Node Behavior on Efficient Topology Design", IEEE Transactions on Mobile Computing, vol.7, no. 9, pp. 1057-1070, September 2008, doi:10.1109/TMC.2008.17
[1] C.E. Jones, K.M. Sivalingam, P. Agrawal, and J.C. Chen, “A Survey of Energy Efficient Network Protocols for Wireless Networks,” Wireless Networks, vol. 7, no. 4, pp. 343-358, Aug. 2001.
[2] P. Gupta and P.R. Kumar, “The Capacity of Wireless Networks,” IEEE Trans. Information Theory, vol. 46, pp. 388-404, Mar. 2000.
[3] P. Santi, “Topology Control in Wireless Ad Hoc and SensorNetworks,” ACM Computing Surveys, vol. 37, pp. 164-194, Mar. 2005.
[4] R. Rajaraman, “Topology Control and Routing in Ad Hoc Networks: A Survey,” SIGACT News, vol. 33, pp. 60-73, June 2002.
[5] N.S. Glance and B.A. Huberman, “Dynamics of Social Dilemmas,” Scientific Am., vol. 270, Mar. 1994.
[6] L. Li, J.Y. Halpern, P. Bahl, Y.M. Wang, and R. Wattenhofer, “A Cone-Based Distributed Topology-Control Algorithm for Wireless Multi-Hop Networks,” IEEE/ACM Trans. Networking, vol. 13, pp.147-159, Feb. 2005.
[7] V. Rodoplu and T.H. Meng, “Minimum Energy Mobile Wireless Networks,” IEEE J. Selected Areas in Comm., vol. 17, pp. 1333-1344, Aug. 1999.
[8] R. Ramanathan and R. Rosales-Hain, “Topology Control of Multihop Wireless Networks Using Transmit Power Adjustment,” Proc. IEEE INFOCOM '00, vol. 2, pp. 404-413, Mar. 2000.
[9] N. Li, J. Hou, and L. Sha, “Design and Analysis of an MST-Based Topology Control Algorithm,” Proc. IEEE INFOCOM '03, vol. 3, pp. 1702-1712, Apr. 2003.
[10] M.K.H. Yeung and Y.-K. Kwok, “A Game Theoretic Approach toPower Aware Wireless Data Access,” IEEE Trans. Mobile Computing, vol. 5, no. 8, pp. 1057-1073, Aug. 2006.
[11] R.S. Komali and A.B. MacKenzie, “Distributed Topology Control in Ad-Hoc Networks: A Game Theoretic Perspective,” Proc. ThirdIEEE Consumer Comm. and Networking Conf. (CCNC '06), vol. 1, pp.563-568, Jan. 2006.
[12] P. Santi, S. Eidenbenz, and G. Resta, “A Framework for Incentive Compatible Topology Control in Non-Cooperative Wireless Multi-Hop Networks,” Proc. Workshop Dependability Issues in Wireless Ad Hoc Networks and Sensor Networks (DIWANS), 2006.
[13] D. Monderer and L. Shapley, “Potential Games,” Games and Economic Behavior, vol. 14, pp. 124-143, 1996.
[14] D. Fudenberg and J. Tirole, Game Theory. MIT Press, 1991.
[15] J.W. Friedman and C. Mezzetti, “Learning in Games by Random Sampling,” J. Economic Theory, vol. 98, pp. 55-84, 2001.
[16] S. Narayanaswamy, V. Kawadia, R.S. Sreenivas, and P.R. Kumar, “Power Control in Ad-Hoc Networks: Theory, Architecture, Algorithm and Implementation of the COMPOW Protocol,” Proc. European Wireless 2002, Next Generation Wireless Networks: Technologies, Protocols, Services and Applications, pp. 156-162, Feb. 2002.
[17] R.W. Thomas, R.S. Komali, A.B. MacKenzie, and L. DaSilva, “Joint Power and Channel Minimization in Topology Control: A Cognitive Network Approach,” Proc. ICC CogNet Workshop, 2007.
[18] C. Bettstetter, “On the Minimum Node Degree and Connectivity of a Wireless Multihop Network,” Proc. ACM MobiHoc '02, pp.80-91, June 2002.
[19] L.A. DaSilva and V. Srivastava, “Node Participation in Ad-Hoc and Peer-to-Peer Networks: A Game-Theoretic Formulation,” Proc. Workshop Games and Emergent Behavior in Distributed Computing Environments, Sept. 2004.
[20] V. Srinivasan, P. Nuggehalli, C. Chiasserini, and R. Rao, “Cooperation in Wireless Ad Hoc Networks,” Proc. IEEE INFOCOM '03, Mar. 2003.
[21] M. Felegyhazi, J.-P. Hubaux, and L. Buttyan, “Nash Equilibria of Packet Forwarding Strategies in Wireless Ad Hoc Networks,” IEEE Trans. Mobile Computing, vol. 5, no. 5, May 2006.
[22] N. Ben Salem, L. Buttyan, J.-P. Hubaux, and M. Jakobsson, “Node Cooperation in Hybrid Ad Hoc Networks,” IEEE Trans. Mobile Computing, vol. 5, no. 4, Apr. 2006.
[23] M. Pearlman, J. Deng, B. Liang, and Z. Haas, “Elective Participation in Ad Hoc Networks Based on Energy Consumption,” Proc. IEEE Global Telecommunications Conf. (GLOBECOM), 2002.
[24] A. Clementi, P. Penna, and R. Silvestri, “Hardness Results for the Power Range Assignment Problem in Packet Radio Networks,” Proc. Third Int'l Workshop Randomization and Approximation in Computer Science (APPROX '99), vol. 1671, pp. 195-208, July 1999.
[25] R.S. Komali, R.W. Thomas, L. DaSilva, and A.B. MacKenzie, Selfishness and Knowledge in Dynamic Topology Control: A Cognitive Network Approach, Aug. 2007.
[26] V. Srivastava, J. Neel, A. MacKenzie, R. Menon, J. Hicks, L. DaSilva, J. Reed, and R. Gilles, “Using Game Theory to Analyze Wireless Ad Hoc Networks,” IEEE Comm. Surveys and Tutorials, Fourth Quarter 2005.
[27] S. Eidenbenz, V. Kumar, and S. Zust, “Equilibria in Topology Control Games for Ad Hoc Networks,” ACM/Kluwer Mobile Networks and Applications, vol. 11, no. 2, pp. 143-159, 2006.
[28] S. Yuen and B. Li, “Strategyproof Mechanisms towards EvolutionaryTopology Formation in Autonomous Networks,” ACM/Kluwer Mobile Networks and Applications, special issue on non-cooperative wireless networking and computing, Oct. 2005.
26 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool