Energy constrained clustering routing method based on particle swarm optimization

Wireless sensor networks are made up of a large number of wireless sensor nodes which are exploited to sense parameters in environment such as temperature, moisture level, pressure, light intensity, vibration, and so on. In order to effectively reduce energy consumption of WSN, this paper proposes a...

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Published in:Cluster computing Vol. 22; no. Suppl 3; pp. 7629 - 7635
Main Authors: Gao, Feng, Luo, Wancheng, Ma, Xinqiang
Format: Journal Article
Language:English
Published: New York Springer US 01.05.2019
Springer Nature B.V
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ISSN:1386-7857, 1573-7543
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Abstract Wireless sensor networks are made up of a large number of wireless sensor nodes which are exploited to sense parameters in environment such as temperature, moisture level, pressure, light intensity, vibration, and so on. In order to effectively reduce energy consumption of WSN, this paper proposes a novel energy constrained clustering routing method based on particle swarm optimization. The simulation results show that proposed method can achieve better overall performance for both energy consumption and network lifetime.
AbstractList Wireless sensor networks are made up of a large number of wireless sensor nodes which are exploited to sense parameters in environment such as temperature, moisture level, pressure, light intensity, vibration, and so on. In order to effectively reduce energy consumption of WSN, this paper proposes a novel energy constrained clustering routing method based on particle swarm optimization. The simulation results show that proposed method can achieve better overall performance for both energy consumption and network lifetime.
Author Ma, Xinqiang
Luo, Wancheng
Gao, Feng
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  fullname: Ma, Xinqiang
  organization: School of Software Engineering, Chongqing University of Arts and Science
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Keywords Wireless sensor networks
Clustering routing algorithm
Energy constrained
Particle swarm optimization
Fitness
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SubjectTerms Algorithms
Clustering
Computer Communication Networks
Computer Science
Embedded systems
Energy consumption
Energy efficiency
Luminous intensity
Operating Systems
Optimization
Particle swarm optimization
Power supply
Processor Architectures
Receivers & amplifiers
Sensors
Wireless communications
Wireless sensor networks
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