University of Electronic Science and Technology of China

Xuebin Tan

Sheng Wang

Shizhong Xu

Jing Ren

Tongyu Song

Xiaotong Guo

Xiong Wang

Jiangong Zheng

A method for energy efficient routing in wireless sensor network based on multi-agent deep reinforcement learning, predefines a to-be-deployed wireless sensor network and creates a cooperative routing decision system including A decision networks and one sink module, A decision networks deployed on the agents a, i=1, 2, . . . , A, of the sensor nodes, the sink module deployed on the sink node n. The decision network obtains a probability vector according to its local observation and position vectors. The sink module calculates a routing for each sensor node according the probability vectors of A decision networks and sends the routings to corresponding sensor nodes. A multi-agent deep reinforcement learning algorithm is adopted to train the decision networks of A agents a, i=1, 2, . . . , A of the cooperative routing decision system, deploys the to-be-deployed wireless sensor network into an environment and updates the routing policy of the deployed wireless sensor network at each update cycle of routing.

Method for energy efficient routing in wireless sensor network based on multi-agent deep reinforcement learning

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Chengdu, China

Xuebin Tan