Artificial agent: The fusion of artificial intelligence and a mobile agent for energy-efficient traffic control in wireless sensor networks

Abstract Applications of wireless sensor networks are blooming for attacking some limits of social development, among which energy consumption and communication latency are fatal. Effective communication traffic control and management is a potential solution, so we propose a novel traffic-control system based on deep reinforcement learning, which regards traffic control as a strategy-learning process, to minimize energy consumption. Our algorithm utilizes deep neural network for learning, inputs the state of wireless sensor network as well as outputs the optimal route path. The simulation experiments demonstrate that our algorithm is feasible to control traffic in wireless sensor network and can reduce the energy consumption.