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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Format: | Article |
Language: | English |
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Wiley
2018-07-01
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Series: | IET Networks |
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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. |
first_indexed | 2024-12-22T08:42:52Z |
format | Article |
id | doaj.art-2ad47b0b664c4a098e4d27196e196d6d |
institution | Directory Open Access Journal |
issn | 2047-4954 2047-4962 |
language | English |
last_indexed | 2024-12-22T08:42:52Z |
publishDate | 2018-07-01 |
publisher | Wiley |
record_format | Article |
series | IET Networks |
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 AT manimozhimuthukumarasamy energyefficientclusteringalgorithmforstructuredwirelesssensornetworks |