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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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Rich: Region-based Intelligent Cluster-Head Selection and Node Deployment Strategy in Concentric-based WSNs

FAN, C.-S. See more information about FAN, C.-S. on SCOPUS See more information about FAN, C.-S. on IEEExplore See more information about FAN, C.-S. on Web of Science
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Download PDF pdficon (765 KB) | Citation | Downloads: 1,210 | Views: 488

Author keywords
clustering methods, energy consumption, wireless sensor networks, energy efficiency, routing protocols

References keywords
sensor(25), networks(23), deployment(8), lifetime(4), information(4), energy(4), communications(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2013-11-30
Volume 13, Issue 4, Year 2013, On page(s): 3 - 8
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2013.04001
Web of Science Accession Number: 000331461300001
SCOPUS ID: 84890143555

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In a random deployment, sensor nodes are scattered randomly in the sensing field. Hence, the coverage can not be guaranteed. In contrast, the coverage of uniformly deployment is in general larger than the random deployment. However, uniformly deployment strategy may cause unbalanced traffic pattern in wireless sensor networks (WSNs). In this situation, larger load may be imposed to CHs (cluster heads) around the sink. Therefore, CHs close to the sink use up their energy earlier than those farther away from the sink. To overcome this problem, we propose a novel node deployment strategy in the concentric model, namely, Region-based Intelligent Cluster-Head selection and node deployment strategy (called Rich). The coverage, energy consumption and data routing issues are well investigated and taken into consideration in the proposed Rich scheme. The simulation results show that the proposed Rich alleviates the unbalanced traffic pattern significantly, prolongs network lifetime and achieves satisfactory coverage ratio.

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Cited-By CrossRef

[1] CDS-Fuzzy Opportunistic Routing Protocol for Wireless Sensor Networks, Golden Julie, E., Tamilselvi, S., Wireless Personal Communications, ISSN 0929-6212, Issue 2, Volume 90, 2016.
Digital Object Identifier: 10.1007/s11277-016-3250-8

[2] Energy Aware Clustering Scheme in Wireless Sensor Network Using Neuro-Fuzzy Approach, Harold Robinson, Y., Golden Julie, E., Balaji, S., Ayyasamy, A., Wireless Personal Communications, ISSN 0929-6212, Issue 2, Volume 95, 2017.
Digital Object Identifier: 10.1007/s11277-016-3793-8

[3] Development of Fuzzy based Energy Efficient Cluster Routing Protocol to Increase the Lifetime of Wireless Sensor Networks, Balaji, S., Golden Julie, E., Harold Robinson, Y., Mobile Networks and Applications, ISSN 1383-469X, Issue 2, Volume 24, 2019.
Digital Object Identifier: 10.1007/s11036-017-0913-y

[4] Hybrid model for security‐aware cluster head selection in wireless sensor networks, Shankar, Achyut, Jaisankar, Natarajan, Khan, Mohammad S., Patan, Rizwan, Balamurugan, Balusamy, IET Wireless Sensor Systems, ISSN 2043-6386, Issue 2, Volume 9, 2019.
Digital Object Identifier: 10.1049/iet-wss.2018.5008

[5] Dynamic Cluster Head Selection Method for Wireless Sensor Network, Jia, Dongyao, Zhu, Huaihua, Zou, Shengxiong, Hu, Po, IEEE Sensors Journal, ISSN 1530-437X, Issue 8, Volume 16, 2016.
Digital Object Identifier: 10.1109/JSEN.2015.2512322

[6] Energy efficient cluster head formation in wireless sensor network, Priyadarshi, Rahul, Soni, Surender Kumar, Nath, Vijay, Microsystem Technologies, ISSN 0946-7076, Issue 12, Volume 24, 2018.
Digital Object Identifier: 10.1007/s00542-018-3873-7

[7] Dynamicity of the scout bee phase for an Artificial Bee Colony for optimized cluster head and network parameters for energy efficient sensor routing, Shankar, Achyut, Jaisankar, N, SIMULATION, ISSN 0037-5497, Issue 9, Volume 94, 2018.
Digital Object Identifier: 10.1177/0037549717742953

[8] An enhanced architecture for route discovery and load balancing in WSN, Kaur, Mandeep, Gupta, Amit, Sohi, Balwinder Singh, The Journal of Supercomputing, ISSN 0920-8542, 2021.
Digital Object Identifier: 10.1007/s11227-021-03777-6

[9] MAC Protocol for Data Gathering in Wireless Sensor Networks with the Aid of Unmanned Aerial Vehicles, VLADUTA, A.-V., PURA, M. L., BICA, I., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 2, Volume 16, 2016.
Digital Object Identifier: 10.4316/AECE.2016.02007
[CrossRef] [Full text]

[10] A node to node security for sensor nodes implanted in cross cover multi-layer architecture using Mc-Nie algorithm, Batta, Kumar Babu, Gurrala, Venkateswara Rao, Yarlagadda, Vishnu Srinivasa Murthy, Evolutionary Intelligence, ISSN 1864-5909, 2020.
Digital Object Identifier: 10.1007/s12065-020-00478-6

[11] Markov Modulated Bernoulli Prediction Process‐based Cluster Head Selection Mechanism for improving resilience in wireless sensor networks, Arulmurugan, A., Amuthan, A., International Journal of Communication Systems, ISSN 1074-5351, Issue 8, Volume 34, 2021.
Digital Object Identifier: 10.1002/dac.4771

[12] Cluster head selection for energy efficient and delay-less routing in wireless sensor network, Sarkar, Amit, Senthil Murugan, T., Wireless Networks, ISSN 1022-0038, Issue 1, Volume 25, 2019.
Digital Object Identifier: 10.1007/s11276-017-1558-2

[13] An energy efficient and adaptive clustering for wireless sensor network (CH-leach) using leach protocol, Abushiba, Walid, Johnson, Princy, Alharthi, Saad, Wright, Colin, 2017 13th International Computer Engineering Conference (ICENCO), ISBN 978-1-5386-4266-5, 2017.
Digital Object Identifier: 10.1109/ICENCO.2017.8289762

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