A joint unsupervised learning and genetic algorithm approach for topology control in energy-efficient ultra-dense wireless sensor networks

Energy efficiency is a key performance metric for ultra-dense wireless sensor networks. In this letter, an unsupervised learning approach for topology control is proposed to prolong the lifetime of ultra-dense wireless sensor networks by balancing energy consumption. By encoding sensors as genes acc...

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Bibliographic Details
Main Authors: Chang, Yuchao, Yuan, Xiaobing, Li, Baoqing, Niyato, Dusit, Al-Dhahir, Naofal
Other Authors: School of Computer Science and Engineering
Format: Journal Article
Language:English
Published: 2020
Subjects:
Online Access:https://hdl.handle.net/10356/140391