Energy‐efficient clustering algorithm for structured wireless sensor networks

Wireless communication is preferred in numerous sensing applications due to its convenience, cost‐effectiveness, and flexibility. Modern sensors are versatile to sense the environmental factors and send them wirelessly. The information collection centres prefer to collect confined clustered informat...

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Main Authors: Yuvaraj Padmanaban, Manimozhi Muthukumarasamy
Format: Article
Language:English
Published: Wiley 2018-07-01
Series:IET Networks
Subjects:
Online Access:https://doi.org/10.1049/iet-net.2017.0112
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author Yuvaraj Padmanaban
Manimozhi Muthukumarasamy
author_facet Yuvaraj Padmanaban
Manimozhi Muthukumarasamy
author_sort Yuvaraj Padmanaban
collection DOAJ
description Wireless communication is preferred in numerous sensing applications due to its convenience, cost‐effectiveness, and flexibility. Modern sensors are versatile to sense the environmental factors and send them wirelessly. The information collection centres prefer to collect confined clustered information from a group of sensors rather than collecting them from individual sensors. Good connectivity, speedy communication, and effective data gathering can be ensured in the network when a good clustering algorithm is utilized. In this paper, a simple and effective clustering algorithm called energy efficient structured clustering algorithm (EESCA) is proposed for the environmental monitoring fields. Cluster heads (CHs) are elected based on average communication distance and lingering energy. Further, a new parameter called cluster head to normal ratio (CTNR) is introduced to rotate the cluster head role among the nodes. The performance evaluation is carried out in terms of first node die (FND), simulation time, scalability, load balancing, and a new parameter called complete useful data percentage (CUDP). Simulations are conducted for three different network scenarios. Results are compared with the renowned existing algorithms low energy adaptive clustering hierarchy (LEACH) and scalable energy efficient clustering hierarchy (SEECH) and it is proved that the proposed technique is beneficial for WSNs.
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spelling doaj.art-2ad47b0b664c4a098e4d27196e196d6d2022-12-21T18:32:11ZengWileyIET Networks2047-49542047-49622018-07-017426527210.1049/iet-net.2017.0112Energy‐efficient clustering algorithm for structured wireless sensor networksYuvaraj Padmanaban0Manimozhi Muthukumarasamy1School of Electrical EngineeringVIT UniversityVelloreTamil NaduIndiaSchool of Electrical EngineeringVIT UniversityVelloreTamil NaduIndiaWireless communication is preferred in numerous sensing applications due to its convenience, cost‐effectiveness, and flexibility. Modern sensors are versatile to sense the environmental factors and send them wirelessly. The information collection centres prefer to collect confined clustered information from a group of sensors rather than collecting them from individual sensors. Good connectivity, speedy communication, and effective data gathering can be ensured in the network when a good clustering algorithm is utilized. In this paper, a simple and effective clustering algorithm called energy efficient structured clustering algorithm (EESCA) is proposed for the environmental monitoring fields. Cluster heads (CHs) are elected based on average communication distance and lingering energy. Further, a new parameter called cluster head to normal ratio (CTNR) is introduced to rotate the cluster head role among the nodes. The performance evaluation is carried out in terms of first node die (FND), simulation time, scalability, load balancing, and a new parameter called complete useful data percentage (CUDP). Simulations are conducted for three different network scenarios. Results are compared with the renowned existing algorithms low energy adaptive clustering hierarchy (LEACH) and scalable energy efficient clustering hierarchy (SEECH) and it is proved that the proposed technique is beneficial for WSNs.https://doi.org/10.1049/iet-net.2017.0112structured wireless sensor networkswireless communicationenvironmental factorsinformation collection centresconfined clustered informationconnectivity
spellingShingle Yuvaraj Padmanaban
Manimozhi Muthukumarasamy
Energy‐efficient clustering algorithm for structured wireless sensor networks
IET Networks
structured wireless sensor networks
wireless communication
environmental factors
information collection centres
confined clustered information
connectivity
title Energy‐efficient clustering algorithm for structured wireless sensor networks
title_full Energy‐efficient clustering algorithm for structured wireless sensor networks
title_fullStr Energy‐efficient clustering algorithm for structured wireless sensor networks
title_full_unstemmed Energy‐efficient clustering algorithm for structured wireless sensor networks
title_short Energy‐efficient clustering algorithm for structured wireless sensor networks
title_sort energy efficient clustering algorithm for structured wireless sensor networks
topic structured wireless sensor networks
wireless communication
environmental factors
information collection centres
confined clustered information
connectivity
url https://doi.org/10.1049/iet-net.2017.0112
work_keys_str_mv AT yuvarajpadmanaban energyefficientclusteringalgorithmforstructuredwirelesssensornetworks
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