A Game Theoretic Approach for Multi-hop Power Line Communications
In this paper, a model for multi-hop power line communication is studied in which a number of smart sensors, e.g., smart meters, seek to minimize the delay experienced during the transmission of their data to a common control center through multi-hop power line communications. This problem is modeled as a network formation game and an algorithm is proposed for modeling the dynamics of network formation. The proposed algorithm is based on a myopic best response process in which each smart sensor can autonomously choose the path that connects it to the control center through other smart sensors. Using the proposed algorithm, the smart sensors can choose their transmission path while optimizing a cost that is a function of the overall achieved transmission delay. This transmission delay captures a tradeoff between the improved channel conditions yielded by multi-hop transmission and the increase in the number of hops. It is shown that, using this network formation process, the smart sensors can self-organize into a tree structure which constitutes a Nash network. Simulation results show that the proposed algorithm presents significant gains in terms of reducing the average achieved delay per smart sensor of at least 28.7% and 60.2%, relative to the star network and a nearest neighbor algorithm, respectively.
KeywordsNetwork Formation Smart Grid Smart Sensor Star Network Game Theoretic Approach
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- 2.Hossain, E., Han, Z., Poor, H.V.: Smart Grid Communications and Networking. Cambridge University Press, Cambridge (2011)Google Scholar
- 4.Galli, S., Scaglione, A., Wang, Z.: Power line communications and the smart grid. In: Proc. International Conference on Smart Grid Communications, Gaithersburg, MD, USA (October 2010)Google Scholar
- 5.Tonello, A.M., Versolatto, F., D’Alessandro, S.: Opportunistic relaying in In-Home PLC networks. In: Proc. IEEE Global Commun. Conf., Miami, FL, USA (December 2010)Google Scholar
- 7.Galli, S.: On the channel capacity of a European-style residential power circuit. In: Proc. International Symposium on Power Line Communication and its Applications, Tokyo, Japan (March 1998)Google Scholar
- 9.Galli, S.: A simple two-tap statistical model for the power line channel. In: Proc. International Symposium on Power Line Communication and its Applications, Rio de Janeiro, Brazil (March 2010)Google Scholar
- 10.Kim, I.H., Varadarajan, B., Dabak, A.: Performance analysis and enhancements of narrowband OFDM powerline communication systems. In: Proc. International Conference on Smart Grid Communications, Gaithersburg, MD, USA (October 2010)Google Scholar
- 11.Mohagheghi, S., Stoupis, J., Wang, Z., Li, Z., Kazemzadeh, H.: Demand response architecture: Integration into the distribution management system. In: Proc. International Conference on Smart Grid Communications, Gaithersburg, MD, USA (October 2010)Google Scholar
- 12.Li, H., Zhang, W.: QoS routing in smart grid. In: Proc. IEEE Global Commun. Conf., Miami, FL, USA (December 2010)Google Scholar
- 15.Derks, J., Kuipers, J., Tennekes, M., Thuijsman, F.: Local dynamics in network formation, Maastricht University, Department of Mathematics, Maastricht, The Netherlands (December 2007), http://www.math.unimaas.nl/PERSONAL/jeand/downlds/derdyn.pdf