Optimizing the Lifetime of Software Defined Wireless Sensor Network via Reinforcement Learning

Optimizing the Lifetime of Software Defined Wireless Sensor Network via Reinforcement Learning

Reinforcement learning (RL) is an unsupervised learning technique used in many real-time applications. The essence of RL is a decision-making problem. In RL, the agent constantly interacts with the environment and selects the next action according to previous feedback in terms of reward. In this pap...

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Bibliographic Details
Main Authors: Muhammad Usman Younus, Muhammad Khurram Khan, Muhammad Rizwan Anjum, Sharjeel Afridi, Zulfiqar Ali Arain, Abdul Aleem Jamali
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Reinforcement learning
wireless sensor network
SDWSN
RL-based WSN
energy optimization
routing
Online Access:https://ieeexplore.ieee.org/document/9302576/

Internet

https://ieeexplore.ieee.org/document/9302576/

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