An energy-optimized game algorithm for wireless sensor networks

Abstract

The ongoing development of wireless sensor networks has been greatly restricted because of scarce spectrum resources, limited battery power, and ineffective topologic structures. Thus, how to construct a suitable topological structure and allocate the appropriate node channels has become an urgent problem. In this study, we built a game model that took into account the influence of channel allocation and topology structure on network performance. The game model considered the nodes in wireless sensor networks to be players and took transmitting power, node channels, and node rest energy into account to establish the income function. Then, the model certified that it has Nash equilibrium. Next, we propose an energy-optimized game algorithm joint topology and channel for wireless sensor network (CETGA) in accordance with the game model. The CETGA algorithm improved each node’s income by changing the transmitting power and node channel gradually, assuming that the network retained connectivity. Then, we demonstrated that the algorithm could converge to a Pareto optimal. Finally, we used MATLAB software to verify the simulation. The results show that the topology created by CETGA is with low interference and long lifetime. In addition, the nodes’ average residual energy is more balanced and the network robustness and real time are improved.

A distributed algorithm for aggregative games of disturbed Euler-Lagrange systems

“…Liang et al 15 exploited distributed algorithms for aggregative games with coupled constraints and nonlinear aggregates. Besides, Wang et al 16 studied the energy-optimized games for wireless sensor networks. In practice, the players in the game may have their own physical dynamics such as electricity market 17 and energy resources.…”