TY - GEN
T1 - A game theoretic approach for multi-hop power line communications
AU - Saad, Walid
AU - Han, Zhu
AU - Poor, H. Vincent
N1 - Funding Information:
This work is supported by NSF Grants CNS-0910461, CNS-0953377, CNS-0905556, and ECCS-1028782, and by DTRA Grant HDTRA1-07-1-0037.
PY - 2012
Y1 - 2012
N2 - 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.
AB - 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.
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U2 - 10.1007/978-3-642-30373-9_38
DO - 10.1007/978-3-642-30373-9_38
M3 - Conference contribution
AN - SCOPUS:84869594463
SN - 9783642303722
T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering
SP - 546
EP - 561
BT - Game Theory for Networks - Second International ICST Conference, GAMENETS 2011, Revised Selected Papers
T2 - 2nd International ICST Conference on Game Theory in Networks, GAMENETS 2011
Y2 - 16 April 2011 through 18 April 2011
ER -