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F5N‐based unequal clustering protocol (F5NUCP) for wireless sensor networks

Summary Wireless sensor networks (WSNs) became very popular and still remains an active research because of diverse applications. Minimizing the energy dissipation and maximizing the network lifetime is an important design issue in WSN. Clustering is the widely used energy effective technique to les...

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Published in:International journal of communication systems 2018-11, Vol.31 (17), p.n/a
Main Authors: Arjunan, Sariga, Pothula, Sujatha, Ponnurangam, Dhavachelvan
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description Summary Wireless sensor networks (WSNs) became very popular and still remains an active research because of diverse applications. Minimizing the energy dissipation and maximizing the network lifetime is an important design issue in WSN. Clustering is the widely used energy effective technique to lessen the overall energy consumption of WSN. An appropriate selection of cluster heads (CHs) and cluster size is a crucial process in clustered WSN. The CHs nearer to base station (BS) suffer from hot spot problem and die earlier than the normal lifetime. This paper contributes a five input fuzzy‐based unequal clustering protocol (F5NUCP) for selecting CHs and determining the appropriate cluster size to prevent the network from hot spot problem. Unequal clusters eliminates the hot spot problem by producing smaller clusters for the nodes located near the BS and larger clusters for the nodes located far away from the BS. F5NUCP uses a nonprobabilistic approach for selecting tentative CHs by introducing a back‐off timer where the timer value is set using the remaining energy of the node. The proposed method uses five input parameters, namely, remaining energy, distance to BS, distance to its neighboring nodes, link quality, and node degree. The output fuzzy parameters used in this research are cluster size and the probability of becoming CHs. The proposed method is implemented in MATLAB. The simulation results show that F5NUCP performs well when compared with LEACH, DEEC, TEEN, and EAUCF in terms of network lifetime and reduced energy consumption. To solve the hot spot problem, a five input fuzzy‐based unequal clustering protocol (F5NUCP) is proposed which involves a nonprobabilistic approach for selecting tentative CHs using a back‐off timer. The simulation results show that F5NUCP outperforms LEACH, DEEC, TEEN, and EAUCF in terms of network lifetime and energy consumption.
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The proposed method uses five input parameters, namely, remaining energy, distance to BS, distance to its neighboring nodes, link quality, and node degree. The output fuzzy parameters used in this research are cluster size and the probability of becoming CHs. The proposed method is implemented in MATLAB. The simulation results show that F5NUCP performs well when compared with LEACH, DEEC, TEEN, and EAUCF in terms of network lifetime and reduced energy consumption. To solve the hot spot problem, a five input fuzzy‐based unequal clustering protocol (F5NUCP) is proposed which involves a nonprobabilistic approach for selecting tentative CHs using a back‐off timer. 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Minimizing the energy dissipation and maximizing the network lifetime is an important design issue in WSN. Clustering is the widely used energy effective technique to lessen the overall energy consumption of WSN. An appropriate selection of cluster heads (CHs) and cluster size is a crucial process in clustered WSN. The CHs nearer to base station (BS) suffer from hot spot problem and die earlier than the normal lifetime. This paper contributes a five input fuzzy‐based unequal clustering protocol (F5NUCP) for selecting CHs and determining the appropriate cluster size to prevent the network from hot spot problem. Unequal clusters eliminates the hot spot problem by producing smaller clusters for the nodes located near the BS and larger clusters for the nodes located far away from the BS. F5NUCP uses a nonprobabilistic approach for selecting tentative CHs by introducing a back‐off timer where the timer value is set using the remaining energy of the node. The proposed method uses five input parameters, namely, remaining energy, distance to BS, distance to its neighboring nodes, link quality, and node degree. The output fuzzy parameters used in this research are cluster size and the probability of becoming CHs. The proposed method is implemented in MATLAB. The simulation results show that F5NUCP performs well when compared with LEACH, DEEC, TEEN, and EAUCF in terms of network lifetime and reduced energy consumption. To solve the hot spot problem, a five input fuzzy‐based unequal clustering protocol (F5NUCP) is proposed which involves a nonprobabilistic approach for selecting tentative CHs using a back‐off timer. The simulation results show that F5NUCP outperforms LEACH, DEEC, TEEN, and EAUCF in terms of network lifetime and energy consumption.</abstract><cop>Chichester</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1002/dac.3811</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0002-9752-2395</orcidid></addata></record>
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subjects Clustering
Energy consumption
Energy dissipation
energy efficiency
fuzzy logic
hot spot problem
Nodes
Parameters
Remote sensors
unequal clustering
Wireless networks
Wireless sensor networks
WSN
title F5N‐based unequal clustering protocol (F5NUCP) for wireless sensor networks
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