Paper Info
Title
Performance Evaluation of a Deep Q-Network Based Simulation System for Actor Node Mobility Control in Wireless Sensor and Actor Networks Considering Three-Dimensional Environment.
Abstract
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 distribution 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 but one event is not covered.
Year
DOI
Venue
2017
10.1007/978-3-319-65636-6_4
ADVANCES IN INTELLIGENT NETWORKING AND COLLABORATIVE SYSTEMS, INCOS-2017
Field
DocType
Volume
Key distribution in wireless sensor networks,Normal distribution,Wireless,Simulation system,Computer science,Computer network,Rust (programming language),Artificial neural network,Mobility control,Distributed computing
Conference
8
ISSN
Citations 
PageRank 
2367-4512
1
0.35
References 
Authors
18
6
Name
Order
Citations
PageRank
Tetsuya Oda144586.37
Donald Elmazi215731.95
Miralda Cuka31812.97
Elis Kulla435151.47
Makoto Ikeda51202207.10
Leonard Barolli61179144.22