A Reinforcement Learning-Based Dynamic Clustering of Sleep Scheduling Algorithm (RLDCSSA-CDG) for Compressive Data Gathering in Wireless Sensor Networks

A Reinforcement Learning-Based Dynamic Clustering of Sleep Scheduling Algorithm (RLDCSSA-CDG) for Compressive Data Gathering in Wireless Sensor Networks

Energy plays a major role in wireless sensor networks (WSNs), and measurements demonstrate that transmission consumes more energy than processing. Hence, organizing the transmission process and managing energy usage throughout the network are the main goals for maximizing the network’s lifetime. Thi...

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Bibliographic Details
Main Authors: Alaa N. El-Shenhabi, Ehab H. Abdelhay, Mohamed A. Mohamed, Ibrahim F. Moawad
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Technologies
Subjects:
efficient energy
sparse-CDG
sleep scheduling
clustering
reinforcement learning
duty cycling
Online Access:https://www.mdpi.com/2227-7080/13/1/25
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