Energy Conservation in Sensor Network Data Ferrying: A Reinforcement Metalearning Approach

Given multiple widespread stationary data sources such as ground-based sensors, an unmanned aircraft can fly over the sensors and gather the data via a wireless link. When sensors have limited energy resources, network lifetime can be extended by reducing the power that the sensors use for communication with the aircraft. Complex vehicle and communication dynamics and imperfect knowledge of the environment make accurate system models difficult to acquire and maintain, so the authors present a reinforcement learning approach that allows the data-ferrying aircraft to optimize data collection trajectories and sensor power use in situ, obviating the need for system identification.

Provided by: Institute of Electrical & Electronic Engineers Topic: Mobility Date Added: Nov 2012 Format: PDF

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