Deep Reinforcement Learning-Based UAV Path Planning for Energy-Efficient Multitier Cooperative Computing in Wireless Sensor Networks

Table 1

Environment parameters setting.

Parameters	Value
UAV initial energy	J
UAV flying speed	m/s
UAV flying height	m
UAV CPU frequency	MHz
UAV flying power	W
UAV hovering power	W
Node initial energy	J
Node CPU frequency	MHz
Node transmission power
CPU cycles for 1-bit
Circuit energy consumption factor
Amplifier energy consumption factor	J/bit/
Computation energy consumption factor
Channel bandwidth	MHz
Channel gain at the reference distance of 1 m
Noise power spectral density	W/Hz
Probability of generating a task per unit time at node