A Wireless Sensor and Actor Network (WSAN) is a group of wireless devices with the ability to sense physical events (sensors) or/and to perform relatively complicated actions (actors), based on the sensed data shared by sensors. This paper presents design and implementation of a simulation system based on Deep Q-Network (DQN) for actor node mobility control in WSANs. DQN is a deep neural network structure used for estimation of Q-value of the Q-learning method. We implemented the proposed simulating system by Rust programming language. We evaluated the performance of proposed system for normal and uniform distributions of events considering three-dimensional environment. For this scenario, the simulation results show that for normal distribution of events and the best episode all actor nodes are connected.
CITATION STYLE
Oda, T., Kulla, E., Katayama, K., Ikeda, M., & Barolli, L. (2019). A deep q-network based simulation system for actor node mobility control in WSANs considering three-dimensional environment: A comparison study for normal and uniform distributions. In Advances in Intelligent Systems and Computing (Vol. 772, pp. 842–852). Springer Verlag. https://doi.org/10.1007/978-3-319-93659-8_77
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