Name
Title | ||
|---|---|---|
Dynamic Path Determination of Mobile Beacons Employing Reinforcement Learning for Wireless Sensor Localization |
Abstract | ||
|---|---|---|
Wireless sensor networks (WSN) are extensively applied in civil and military areas. Localization is an essential prerequisite for many WSN applications, and is often based on beacons that provide geographical information in real time. Mobile Beacons (MB) can be used to replace many static beacons with paths that can be controlled in real-time. Robotic and/or flight vehicles can work as MBs. In this paper we consider the use of reinforcement learning (RL) (a significant branch of machine learning) to control MBs. Usually, RL needs an infinite series of episodes to determine an optimal policy. We propose however a method of localization employing mobile beacon whose behavior will be controlled by an adapted RL algorithm. A MB learns and makes decisions based on weighted information collected from unknown sensors. Simulation results show that the adapted RL algorithm provides sufficient information to the MB to localise unknown sensors in a lightweight but effective way. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/WAINA.2012.67 | AINA Workshops |
Keywords | Field | DocType |
localization,unknown sensor,real time geographical information,geographical information,computerised instrumentation,reinforcement learning,essential prerequisite,rl,learning (artificial intelligence),mobile beacons,wireless sensor network,rl algorithm,wsn applications,mobile beacons dynamic path determination,weighted information,dynamic path,optimal policy,sufficient information,mobile beacons employing reinforcement,robotic vehicles,dynamic path determination,wireless sensor networks,mobile beacon,flight vehicles,machine learning,sensor placement,wireless sensor localization,wsn application,simulation,estimation,infinite series,mobile communication,algorithm design and analysis,algorithm design,real time,learning artificial intelligence | Beacon,Algorithm design,Wireless,Computer science,Wireless sensor network,Mobile telephony,Distributed computing,Reinforcement learning | Conference |
ISBN | Citations | PageRank |
978-1-4673-0867-0 | 5 | 0.58 |
References | Authors | |
11 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Songsheng Li | 1 | 12 | 1.85 |
| Xiaoying Kong | 2 | 51 | 12.85 |
| D. G. Lowe | 3 | 15718 | 1413.60 |