A cooperative game theoretic approach to clustering algorithms for wireless sensor networks

As one of the most widely investigated topology control mechanisms of wireless sensor networks (WSNs), the clustering algorithm provides energy efficient communications by reducing transmission overhead and enhancing transmission reliability. Through the previous forms of noncooperative games, the behavior of each sensor node (SN) is individual in WSNs; accordingly, it engenders uneven distribution of residual energy across SNs and expedites network partition. To balance energy consumption of SNs and increase network lifetime and stability, a cooperative game theoretic model of clustering algorithms is provided for assigning feasible allocations of energy cost. Moreover, from the outcome of this model, we propose and analyze a cooperative clustering approach for global optimization with the capacity of sensing data transmission and energy efficiency. The key idea is that SNs should trade off individual cost with network-wide cost. In the algorithm, we develop conditions to form coalitions considering residual energy, transmission distance and number of SNs in a cluster adapting to various WSNs. Furthermore, we present performance evaluation and comparison of the existing clustering algorithms with our approach quantitatively with respect to network lifetime, data transmission capacity and energy efficiency. Comparing with other approaches through the simulation, our scheme can surely guarantee to prolong network life-time and improve data transmission capacity up to 5.8% and 35.9%, respectively.