Multiobjective Multiple Mobile Sink Scheduling via Evolutionary Fuzzy Rough Neural Network for Wireless Sensor Networks

The sensor nodes in wireless sensor networks have the deficiency of limited energy, and the multihop transmission of information will lead to a premature paralysis of nodes near the sink. The use of the mobile sink can balance the energy consumption and greatly prolong the lifetime. Therefore, this...

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Veröffentlicht in:	IEEE transactions on fuzzy systems Jg. 30; H. 11; S. 4630 - 4641
Hauptverfasser:	Zhao, Jianwei, Cao, Bin, Liu, Xin, Yang, Peng, Singh, Amit Kumar, Lv, Zhihan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.11.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Artificial neural networks Energy consumption Energy utilization Evolutionary algorithms Fuzzy inference Fuzzy logic Fuzzy neural networks Fuzzy rough neural network Fuzzy rough neural network (FRNN) Fuzzy sets Gene expression Genetic algorithms Multi-Objective Evolutionary Algorithm multi-objective evolutionary algorithm (MOEA) multiobjective evolutionary algorithm Multiobjective evolutionary algorithms Multiobjective optimization multiple mobile sink scheduling Multiple mobile sinks Multiple objective analysis network lifetime neural evolution Neural evolutions Neural networks Nodes Optimisations Optimization Paralysis Rough neural networks Rough sets Scheduling Sensor nodes Sensors Task complexity Task scheduling Wireless communication Wireless communications Wireless networks Wireless sensor networks
ISSN:	1063-6706, 1941-0034, 1941-0034
Online-Zugang:	Volltext
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