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Fuzzy Logic Based Energy Efficient Protocol in Wireless Sensor Networks


Affiliations
1 Modeling, Simulation & Computing Laboratory, Material & Mineral Research Unit School of Engineering and Information Technology, Universiti Malaysia Sabah, Malaysia
2 Modeling, Simulation & Computing Laboratory, Material & Mineral Research Unit School of Engineering and Information Technology, Universiti Malaysia Sabah, Malaysia
     

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Wireless sensor networks (WSNs) have been vastly developed due to the advances in microelectromechanical systems (MEMS) using WSN to study and monitor the environments towards climates changes. In environmental monitoring, sensors are randomly deployed over the interest area to periodically sense the physical environments for a few months or even a year. Therefore, to prolong the network lifetime with limited battery capacity becomes a challenging issue. Low energy adaptive cluster hierarchical (LEACH) is the common clustering protocol that aim to reduce the energy consumption by rotating the heavy workload cluster heads (CHs). The CHs election in LEACH is based on probability model which will lead to inefficient in energy consumption due to least desired CHs location in the network. In WSNs, the CHs location can directly influence the network energy consumption and further affect the network lifetime. In this paper, factors which will affect the network lifetime will be presented and the demonstration of fuzzy logic based CH selection conducted in base station (BS) will also be carried out. To select suitable CHs that will prolong the network first node dies (FND) round and consistent throughput to the BS, energy level and distance to the BS are selected as fuzzy inputs.

Keywords

Wireless Sensor Network, Cluster Head, First Node Dies, Fuzzy Logic.
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  • Fuzzy Logic Based Energy Efficient Protocol in Wireless Sensor Networks

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Authors

Zhan Wei Siew
Modeling, Simulation & Computing Laboratory, Material & Mineral Research Unit School of Engineering and Information Technology, Universiti Malaysia Sabah, Malaysia
Chen How Wong
Modeling, Simulation & Computing Laboratory, Material & Mineral Research Unit School of Engineering and Information Technology, Universiti Malaysia Sabah, Malaysia
Aroland Kiring
Modeling, Simulation & Computing Laboratory, Material & Mineral Research Unit School of Engineering and Information Technology, Universiti Malaysia Sabah, Malaysia
Renee Ka Yin Chin
Modeling, Simulation & Computing Laboratory, Material & Mineral Research Unit School of Engineering and Information Technology, Universiti Malaysia Sabah, Malaysia
Kenneth Tze Kin Teo
Modeling, Simulation & Computing Laboratory, Material & Mineral Research Unit School of Engineering and Information Technology, Universiti Malaysia Sabah, Malaysia

Abstract


Wireless sensor networks (WSNs) have been vastly developed due to the advances in microelectromechanical systems (MEMS) using WSN to study and monitor the environments towards climates changes. In environmental monitoring, sensors are randomly deployed over the interest area to periodically sense the physical environments for a few months or even a year. Therefore, to prolong the network lifetime with limited battery capacity becomes a challenging issue. Low energy adaptive cluster hierarchical (LEACH) is the common clustering protocol that aim to reduce the energy consumption by rotating the heavy workload cluster heads (CHs). The CHs election in LEACH is based on probability model which will lead to inefficient in energy consumption due to least desired CHs location in the network. In WSNs, the CHs location can directly influence the network energy consumption and further affect the network lifetime. In this paper, factors which will affect the network lifetime will be presented and the demonstration of fuzzy logic based CH selection conducted in base station (BS) will also be carried out. To select suitable CHs that will prolong the network first node dies (FND) round and consistent throughput to the BS, energy level and distance to the BS are selected as fuzzy inputs.

Keywords


Wireless Sensor Network, Cluster Head, First Node Dies, Fuzzy Logic.