Sensor-centric energy-constrained reliable query routing for wireless sensor networks

  • Authors:

  • Rajgopal Kannan;Sudipta Sarangi;S. Sitharama Iyengar

  • Affiliations:

  • Department of Computer Science, Louisiana State University, Baton Rouge LA;Department of Economics, Louisiana State University, Baton Rouge LA;Department of Computer Science, Louisiana State University, Baton Rouge LA

  • Venue:
  • Journal of Parallel and Distributed Computing
  • Year:
  • 2004

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Abstract

Standard wireless sensor network models emphasize energy efficiency and distributed decision-making by considering untethered and unattended sensors. To this we add two constraints--the possibility of sensor failure and the fact that each sensor must tradeoff its own resource consumption with overall network objectives. In this paper, we develop an analytical model of energy-constrained, reliable, data-centric information routing in sensor networks under all the above constraints. Unlike existing techniques, we use game theory to model intelligent sensors thereby making our approach sensor-centric. Sensors behave as rational players in an N-player routing game, where they tradeoff individual communication and other costs with network wide benefits. The outcome of the sensor behavior is a sequence of communication link establishments, resulting in routing paths from reporting to querying sensors. We show that the optimal routing architecture is the Nash equilibrium of the N-player routing game and that computing the optimal paths (which maximizes payoffs of the individual sensors) is NP-Hard with and without data-aggregation. We develop a game-theoretic metric called path weakness to measure the qualitative performance of different routing mechanisms. This sensor-centric concept which is based on the contribution of individual sensors to the overall routing objective is used to define the quality of routing (QoR) paths. Analytical results on computing paths of bounded weakness are derived and game-theoretic heuristics for finding approximately optimal paths are presented. Simulation results are used to compare the QoR of different routing paths derived using various energy-constrained routing algorithms.