Performance Analysis for Efficient Cluster Head Selection in Wireless Sensor Network Using RBFO and Hybrid BFO-BSO

A. Rajagopal; S. Somasundaram; B. Sowmya

doi:doi:10.11648/j.wcmc.20180601.11

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Performance Analysis for Efficient Cluster Head Selection in Wireless Sensor Network Using RBFO and Hybrid BFO-BSO

A. Rajagopal, S. Somasundaram, B. Sowmya

Published in International Journal of Wireless Communications and Mobile Computing (Volume 6, Issue 1)

Received: 18 November 2017 Accepted: 30 November 2017 Published: 26 January 2018

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Abstract

Wireless Sensor Network involves in the communication task which demands the devices to form a connected network for collecting and disseminating information through radio transmission. The main objective of the Wireless Sensor Network is to extend the network lifetime in the operational environment, to charge or to exchange the sensor node batteries is probably an impossible/unfeasible activity. The clustered network aims to select CHs that minimize transmission costs and energy. To maximize the network lifetime, optimal CH selection is important. Selections of CH are Non deterministic Polynomial (NP) hard. Recently natural swarm inspired algorithms like Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) have found their way into this domain and proved their effectiveness. In this work the BFO is adapted for cluster head selection so that multiple objectives like reduced packet delivery ratio, improved cluster formation, improved network life time and reduced end to end delay are achieved. Also a novel Hybrid algorithm using Bacterial foraging Optimization (BFO) - Bee swarm Optimization (BSO) is attempted to analysis the number of clustered formed, end to end delay, packet drop ratio and lifetime.

Published in	International Journal of Wireless Communications and Mobile Computing (Volume 6, Issue 1)
DOI	10.11648/j.wcmc.20180601.11
Page(s)	1-9
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Wireless Sensor Network, Cluster Head Selection, Bacterial Forging Optimization (BFO), Bee Swarm Optimization (BSO), Particle Swarm Optimization (PSO)

References

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[3]	Gupta, S. K., and Sinha, P. (2014), Overview of Wireless Sensor Network, A Survey, International Journal of Advanced Research in Computer and Communication Engineering, Vol. 3, No. 1, pp. 5201-5207.
[4]	O. Chipara, Z. He, G. Xing, Q. Chen, X. Wang, C. Lu, J. Stankovic, T. Abdelzaher, (2006) Real-time power-aware routing in sensor networks, quality of service, in: IWQoS 2006, 14th IEEE International, Workshop, pp. 83–92.
[5]	Mahyastuti, V. W., and Pramudita, A. A. (2013), Energy consumption evaluation of low energy adaptive clustering hierarchy routing protocol for wireless sensor network, In Communication, Networks and Satellite (COMNETSAT), IEEE International Conference, pp. 6-9.
[6]	Tripathi, M., Battula, R. B., Gaur, M. S., and Laxmi, V. (2013), Energy Efficient Clustered Routing for Wireless Sensor Network, In Mobile Ad-hoc and Sensor Networks (MSN), IEEE Ninth International Conference, pp. 330-335.
[7]	Nguyen, T. G., So-In, C., and Nguyen, N. G. (2014), Two energy-efficient cluster head selection techniques based on distance for Wireless Sensor Networks, In Computer Science and Engineering Conference (ICSEC), International, pp. 33-38.
[8]	Gambhir, S., and Fatima, N. (2014), Op-LEACH: An Optimized LEACH Method for Busty Traffic in WSNs, In Advanced Computing and Communication Technologies (ACCT), Fourth International Conference, pp. 222-229.
[9]	Sujee, R., and Kannammal, K. E. (2015), Behavior of LEACH protocol in heterogeneous and homogeneous environment, In Computer Communication and Informatics (ICCCI), International Conference, pp. 1-8.
[10]	Sharma, T., Tomar, G. S., Berry, I., Kapoor, A., and Jasuja, S. (2016), Cluster Head Election with Hexagonal Node Deployment Technique in Wireless Sensor Networks, International Journal of Future Generation Communication and Networking, Vol. 9, No. 1, pp. 247-258.
[11]	Sheta, A., and Solaiman, B. (2015), Evolving a Hybrid K-Means Clustering Algorithm for Wireless Sensor Network Using PSO and GAs. International Journal of Computer Science Issues (IJCSI), Vol. 12, No. 1, pp. 23-32.
[12]	Gajjar, S., Sarkar, M., and Dasgupta, K. (2015), FAMACRO: Fuzzy and ant colony optimization based MAC/routing cross-layer protocol for wireless sensor networks, Procedia Computer Science, Vol. 46, pp. 1014-1021.
[13]	Ahmadi, R., and Masdari, M. (2015), providing an efficient algorithm for wireless sensor network routing with hybrid particle swarm optimization and LEACH. Academie Royale Des Sciences D Outre-Mer Bulletin Des Seances, Vol. 4, No. 3, pp. 80-88.
[14]	Teimoury, E., Gholamian, M. R., Masoum, B., and Ghanavati, M. (2016), An optimized clustering algorithm based on K-means using Honey Bee Mating algorithm.
[15]	Kavitha, G., and Wahidabanu, R. (2014 March), Foraging Optimization for Cluster Head Selection, Journal of Theoretical and Applied Information Technology, Vol. 61, No. 3, pp. 571.
[16]	Rajagopal, A., Somasundaram, S., Sowmya, B. and Suguna, T. (2015), Soft computing based Cluster Head Selection in Wireless Sensor Network using Bacterial Foraging Optimization Algorithm, International Journal of Electrical, Computer, Energetic, Electronics and Communication Engineering, WASET, Vol. 9 (3), pp. 357-362.
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APA Style

A. Rajagopal, S. Somasundaram, B. Sowmya. (2018). Performance Analysis for Efficient Cluster Head Selection in Wireless Sensor Network Using RBFO and Hybrid BFO-BSO. International Journal of Wireless Communications and Mobile Computing, 6(1), 1-9. https://doi.org/10.11648/j.wcmc.20180601.11

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ACS Style

A. Rajagopal; S. Somasundaram; B. Sowmya. Performance Analysis for Efficient Cluster Head Selection in Wireless Sensor Network Using RBFO and Hybrid BFO-BSO. Int. J. Wirel. Commun. Mobile Comput. 2018, 6(1), 1-9. doi: 10.11648/j.wcmc.20180601.11

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AMA Style

A. Rajagopal, S. Somasundaram, B. Sowmya. Performance Analysis for Efficient Cluster Head Selection in Wireless Sensor Network Using RBFO and Hybrid BFO-BSO. Int J Wirel Commun Mobile Comput. 2018;6(1):1-9. doi: 10.11648/j.wcmc.20180601.11

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@article{10.11648/j.wcmc.20180601.11,
  author = {A. Rajagopal and S. Somasundaram and B. Sowmya},
  title = {Performance Analysis for Efficient Cluster Head Selection in Wireless Sensor Network Using RBFO and Hybrid BFO-BSO},
  journal = {International Journal of Wireless Communications and Mobile Computing},
  volume = {6},
  number = {1},
  pages = {1-9},
  doi = {10.11648/j.wcmc.20180601.11},
  url = {https://doi.org/10.11648/j.wcmc.20180601.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.wcmc.20180601.11},
  abstract = {Wireless Sensor Network involves in the communication task which demands the devices to form a connected network for collecting and disseminating information through radio transmission. The main objective of the Wireless Sensor Network is to extend the network lifetime in the operational environment, to charge or to exchange the sensor node batteries is probably an impossible/unfeasible activity. The clustered network aims to select CHs that minimize transmission costs and energy. To maximize the network lifetime, optimal CH selection is important. Selections of CH are Non deterministic Polynomial (NP) hard. Recently natural swarm inspired algorithms like Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) have found their way into this domain and proved their effectiveness. In this work the BFO is adapted for cluster head selection so that multiple objectives like reduced packet delivery ratio, improved cluster formation, improved network life time and reduced end to end delay are achieved. Also a novel Hybrid algorithm using Bacterial foraging Optimization (BFO) - Bee swarm Optimization (BSO) is attempted to analysis the number of clustered formed, end to end delay, packet drop ratio and lifetime.},
 year = {2018}
}

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TY  - JOUR
T1  - Performance Analysis for Efficient Cluster Head Selection in Wireless Sensor Network Using RBFO and Hybrid BFO-BSO
AU  - A. Rajagopal
AU  - S. Somasundaram
AU  - B. Sowmya
Y1  - 2018/01/26
PY  - 2018
N1  - https://doi.org/10.11648/j.wcmc.20180601.11
DO  - 10.11648/j.wcmc.20180601.11
T2  - International Journal of Wireless Communications and Mobile Computing
JF  - International Journal of Wireless Communications and Mobile Computing
JO  - International Journal of Wireless Communications and Mobile Computing
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PB  - Science Publishing Group
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UR  - https://doi.org/10.11648/j.wcmc.20180601.11
AB  - Wireless Sensor Network involves in the communication task which demands the devices to form a connected network for collecting and disseminating information through radio transmission. The main objective of the Wireless Sensor Network is to extend the network lifetime in the operational environment, to charge or to exchange the sensor node batteries is probably an impossible/unfeasible activity. The clustered network aims to select CHs that minimize transmission costs and energy. To maximize the network lifetime, optimal CH selection is important. Selections of CH are Non deterministic Polynomial (NP) hard. Recently natural swarm inspired algorithms like Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) have found their way into this domain and proved their effectiveness. In this work the BFO is adapted for cluster head selection so that multiple objectives like reduced packet delivery ratio, improved cluster formation, improved network life time and reduced end to end delay are achieved. Also a novel Hybrid algorithm using Bacterial foraging Optimization (BFO) - Bee swarm Optimization (BSO) is attempted to analysis the number of clustered formed, end to end delay, packet drop ratio and lifetime.
VL  - 6
IS  - 1
ER  -

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Author Information

A. Rajagopal

Department of Electronics & Instrumentation Engineering, Annamalai University, Chidambaram, India
S. Somasundaram

Department of Electronics & Instrumentation Engineering, Annamalai University, Chidambaram, India
B. Sowmya

Department of Electronics & Communication Engineering, Alpha College of Engineering, Chennai, India

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Plain Text BibTeX RIS

APA Style

A. Rajagopal, S. Somasundaram, B. Sowmya. (2018). Performance Analysis for Efficient Cluster Head Selection in Wireless Sensor Network Using RBFO and Hybrid BFO-BSO. International Journal of Wireless Communications and Mobile Computing, 6(1), 1-9. https://doi.org/10.11648/j.wcmc.20180601.11

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ACS Style

A. Rajagopal; S. Somasundaram; B. Sowmya. Performance Analysis for Efficient Cluster Head Selection in Wireless Sensor Network Using RBFO and Hybrid BFO-BSO. Int. J. Wirel. Commun. Mobile Comput. 2018, 6(1), 1-9. doi: 10.11648/j.wcmc.20180601.11

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AMA Style

A. Rajagopal, S. Somasundaram, B. Sowmya. Performance Analysis for Efficient Cluster Head Selection in Wireless Sensor Network Using RBFO and Hybrid BFO-BSO. Int J Wirel Commun Mobile Comput. 2018;6(1):1-9. doi: 10.11648/j.wcmc.20180601.11

Copy | Download

@article{10.11648/j.wcmc.20180601.11,
  author = {A. Rajagopal and S. Somasundaram and B. Sowmya},
  title = {Performance Analysis for Efficient Cluster Head Selection in Wireless Sensor Network Using RBFO and Hybrid BFO-BSO},
  journal = {International Journal of Wireless Communications and Mobile Computing},
  volume = {6},
  number = {1},
  pages = {1-9},
  doi = {10.11648/j.wcmc.20180601.11},
  url = {https://doi.org/10.11648/j.wcmc.20180601.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.wcmc.20180601.11},
  abstract = {Wireless Sensor Network involves in the communication task which demands the devices to form a connected network for collecting and disseminating information through radio transmission. The main objective of the Wireless Sensor Network is to extend the network lifetime in the operational environment, to charge or to exchange the sensor node batteries is probably an impossible/unfeasible activity. The clustered network aims to select CHs that minimize transmission costs and energy. To maximize the network lifetime, optimal CH selection is important. Selections of CH are Non deterministic Polynomial (NP) hard. Recently natural swarm inspired algorithms like Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) have found their way into this domain and proved their effectiveness. In this work the BFO is adapted for cluster head selection so that multiple objectives like reduced packet delivery ratio, improved cluster formation, improved network life time and reduced end to end delay are achieved. Also a novel Hybrid algorithm using Bacterial foraging Optimization (BFO) - Bee swarm Optimization (BSO) is attempted to analysis the number of clustered formed, end to end delay, packet drop ratio and lifetime.},
 year = {2018}
}

Copy | Download

TY  - JOUR
T1  - Performance Analysis for Efficient Cluster Head Selection in Wireless Sensor Network Using RBFO and Hybrid BFO-BSO
AU  - A. Rajagopal
AU  - S. Somasundaram
AU  - B. Sowmya
Y1  - 2018/01/26
PY  - 2018
N1  - https://doi.org/10.11648/j.wcmc.20180601.11
DO  - 10.11648/j.wcmc.20180601.11
T2  - International Journal of Wireless Communications and Mobile Computing
JF  - International Journal of Wireless Communications and Mobile Computing
JO  - International Journal of Wireless Communications and Mobile Computing
SP  - 1
EP  - 9
PB  - Science Publishing Group
SN  - 2330-1015
UR  - https://doi.org/10.11648/j.wcmc.20180601.11
AB  - Wireless Sensor Network involves in the communication task which demands the devices to form a connected network for collecting and disseminating information through radio transmission. The main objective of the Wireless Sensor Network is to extend the network lifetime in the operational environment, to charge or to exchange the sensor node batteries is probably an impossible/unfeasible activity. The clustered network aims to select CHs that minimize transmission costs and energy. To maximize the network lifetime, optimal CH selection is important. Selections of CH are Non deterministic Polynomial (NP) hard. Recently natural swarm inspired algorithms like Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) have found their way into this domain and proved their effectiveness. In this work the BFO is adapted for cluster head selection so that multiple objectives like reduced packet delivery ratio, improved cluster formation, improved network life time and reduced end to end delay are achieved. Also a novel Hybrid algorithm using Bacterial foraging Optimization (BFO) - Bee swarm Optimization (BSO) is attempted to analysis the number of clustered formed, end to end delay, packet drop ratio and lifetime.
VL  - 6
IS  - 1
ER  -

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