An Efficient Clustering Protocol for Wireless Sensor Networks Based on Localized Game Theoretical Approach

Game theory has emerged as a brand new approach to model and analyse several problems of wireless sensor networks, such as routing, data collection, and topology control. Recently, a novel clustering mechanism called clustered routing for selfish sensors (CROSS) has been proposed based on game theory. The sensor nodes, which are modelled as players, join in a clustering game to campaign for cluster heads with an equilibrium probability. However, the CROSS algorithm needs the global information of how many nodes participate in the game at every round. Considering that this global way introduces much more packets exchange and energy consumption, we present a Localized game theoretical clustering algorithm (LGCA). In our protocol, each node selfishly plays a localized clustering game only with its neighbours within a communication radius R c . Moreover, exactly one node can successfully bid for a position of the cluster head in one district, thus achieving an optimal payoff. Simulation results show that our method achieves a better result compared with CROSS and LEACH in terms of network lifetime.