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Table 1 Notations

From: A reinforcement learning-based sleep scheduling algorithm for compressive data gathering in wireless sensor networks

Notations

Description

SN

The set of all sensor nodes

sni

Sensor node i

Nbri

The set of all neighbors of node i

sniw

Neighbors of node i

X

A sensing data vector

K

The sparsity of X

N

The number of nodes

M

The required number of CS measurements

t

The number of sampled nodes in each measurement

S

The state vector

sk

The agent’s state at a time step k

A

The action set

ak

The selected action at a time step k

R

The reward function

Rk+1

The reward for action ak

E0

Initial energy of nodes

ER

Residual energy of nodes