Technique towards Multi-Objective Clustering in Heterogeneous Wireless Sensor Networks

International Journal of Electrical and Electronics Engineering
© 2023 by SSRG - IJEEE Journal
Volume 10 Issue 12
Year of Publication : 2023
Authors : Santosh V. Purkar, Jayant J. Chopade, Dnyaneshwar D. Ahire
pdf
How to Cite?

Santosh V. Purkar, Jayant J. Chopade, Dnyaneshwar D. Ahire, "Technique towards Multi-Objective Clustering in Heterogeneous Wireless Sensor Networks," SSRG International Journal of Electrical and Electronics Engineering, vol. 10,  no. 12, pp. 8-17, 2023. Crossref, https://doi.org/10.14445/23488379/IJEEE-V10I12P102

Abstract:

The primary intent and objectives of communication entities and systems have been substantially multiplied by wireless sensor systems or sensors as an end-mile extension. Nevertheless, the sensor unit’s power constraints limit their activity and lifetime. As a result, an energy-efficient approach appears to be needed to improve reliability in the form of sensor network lifetime. On the other hand, in the same direction, adding heterogeneity to a Wireless Sensor Network (WSN) and controlling communication activity extends the nodes’ lifetime. The intelligent energy-saving approach enhances network stability and lifespan without attention to node deployment or heterogeneity level. Thus, the resulting method reduces administrative expenses of inter-cluster or intra-cluster interactions, optimizes communication stress, succeeds in better load balance within the network, and ultimately boosts network stability. The Multi-Objective Protocol (MOP) for clustering heterogeneous WSN is a proposed design to do the same thing. Finally, the suggested system demonstrates superior performance across diverse deployment situations, varying levels of heterogeneity, and multiple performance criteria. The simulation results of the recommended scheme surpass well-known published design techniques by a factor of more than 1.95 times.

Keywords:

Heterogeneity, Multilevel, Node index, Received Signal Strength Indicator, Sampling.

References:

[1] W.R. Heinzelman, A. Chandrakasan, and H. Balakrishnan, “Energy-Efficient Communication Protocol for Wireless Microsensor Networks,” Proceedings of the 33rd Annual Hawaii International Conference on System Sciences, Maui, USA, vol. 2, pp. 10-19, 2000.
[CrossRef] [Google Scholar] [Publisher Link]
[2] M. Perillo, Z. Cheng, and W. Heinzelman, “On the Problem of Unbalanced Load Distribution in Wireless Sensor Networks,” IEEE Global Telecommunications Conference Workshops - GlobeCom Workshops, Dallas, TX, USA, pp. 74-79, 2004.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Ankita Srivastava, and Pramod Kumar Mishra, “Energy Efficient Clustering Using Modified Promethee-II and AHP Approach in Wireless Sensor Networks,” Multimedia Tools and Applications, vol. 82, pp. 47049-47080, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[4] Georgios Smaragdakis, Ibrahim Matta, and Azer Bestavros, “SEP: A Stable Election Protocol for Clustered Heterogeneous Wireless Sensor Network,” CAS: Computer Science: Technical Reports, pp. 1-11, 2004.
[Google Scholar] [Publisher Link]
[5] Li Qing, Qingxin Zhu, and Mingwen Wang, “Design of a Distributed Energy-Efficient Clustering Algorithm for Heterogeneous Wireless Sensor Networks,” Computer Communications, vol. 29, no. 12, pp. 2230-2237, 2006.
[CrossRef] [Google Scholar] [Publisher Link]
[6] A. Kashaf et al., “TSEP: Threshold-Sensitive Stable Election Protocol for WSNs,” 2012 10th International Conference on Frontiers of Information Technology, Islamabad, Pakistan, pp. 164-168, 2012.
[CrossRef] [Google Scholar] [Publisher Link]
[7] Carolina Del-Valle-Soto, Alma Rodríguez, and Cesar Rodolfo Ascencio-Piña, “A Survey of Energy-Efficient Clustering Routing Protocols for Wireless Sensor Networks Based on Metaheuristic Approaches,” Artificial Intelligence Review, vol. 56, pp. 9699-9770, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Sweta Kumari Barnwal, Amit Prakash, and Dilip Kumar Yadav, “Improved African Buffalo Optimization-Based Energy Efficient Clustering Wireless Sensor Networks Using Metaheuristic Routing Technique,” Wireless Personal Communications, vol. 130, pp. 1575- 1596, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[9] P. Paruthi Ilam Vazhuthi et al., “A Hybrid ANFIS Reptile Optimization Algorithm for Energy-Efficient Inter-Cluster Routing in Internet of Things-Enabled Wireless Sensor Networks,” Peer-to-Peer Networking and Applications, vol. 16, pp. 1049-1068, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Bryar A. Hassan, and Tarik A. Rashid, “A Multidisciplinary Ensemble Algorithm for Clustering Heterogeneous Datasets,” Neural Computing and Applications, vol. 33, no. 17, pp. 10987-11010, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Bryar A. Hassan, Tarik A. Rashid, and Hozan K. Hamarashid, “A Novel Cluster Detection of COVID-19 Patients and Medical Disease Conditions Using Improved Evolutionary Clustering Algorithm Star,” Computers in Biology and Medicine, vol. 138, pp. 1-16, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Zhezhuang Xu et al., “Balancing Energy Consumption with Hybrid Clustering and Routing Strategy in Wireless Sensor Networks,” Sensors, vol. 15, no. 10, pp. 26583-26605, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[13] Bryar A. Hassan, Tarik A. Rashid, and Seyedali Mirjalili, “Formal Context Reduction in Deriving Concept Hierarchies from Corpora Using Adaptive Evolutionary Clustering Algorithm Star,” Complex & Intelligent Systems, vol. 7, pp. 2383-2398, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[14] Bryar A. Hassan, Tarik A. Rashid, and Seyedali Mirjalili, “Performance Evaluation Results of Evolutionary Clustering Algorithm Star for Clustering Heterogeneous Datasets,” Data in Brief, vol. 36, pp. 1-12, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[15] Bryar A. Hassan, and Tarik A. Rashid, “Artificial Intelligence Algorithms for Natural Language Processing and the Semantic Web Ontology Learning,” arXiv, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[16] Absalom E. Ezugwu et al., “Automatic Clustering Algorithms: A Systematic Review and Bibliometric Analysis of Relevant Literature,” Neural Computing and Applications, vol. 33, pp. 6247-6306, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[17] Edy Umargono, Jatmiko Endro Suseno, and S.K. Vincensius Gunawan, “K-Means Clustering Optimization Using the Elbow Method and Early Centroid Determination Based on Mean and Median Formula,” Proceedings of the 2nd International Seminar on Science and Technology (ISSTEC 2019), Atlantis Press, pp. 121-129, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[18] Ishita Banerjee, and P. Madhumathy, “QoS Enhanced Energy Efficient Cluster-Based Routing Protocol Realized Using Stochastic Modeling to Increase Lifetime of Green Wireless Sensor Network,” Wireless Networks, vol. 29, pp. 489-507, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[19] Nevine Makram Labib et al., “Design of an Enhanced Threshold Sensitive Distributed Energy Efficient Clustering Routing Protocol for WSN-Based IoT,” vol. 110, no. 8, pp. 1373-1392, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[20] Chaoming Wang et al., “Hybrid Multi-Hop Partition-Based Clustering Routing Protocol for WSNs,” IEEE Sensors Letters, vol. 2, no. 1, pp. 1-4, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[21] Fifi Farouk, Rawya Rizk, and Fayez W. Zaki, “Multi-Level Stable and Energy-Efficient Clustering Protocol in Heterogeneous Wireless Sensor Networks,” IET Wireles Sensor Systems, vol. 4, no. 4, pp. 159-169, 2014.
[CrossRef] [Google Scholar] [Publisher Link]
[22] Dilip Kumar, Trilok C. Aseri, and R.B. Patel, “EEHC: Energy Efficient Heterogeneous Cluster Scheme for Wireless Sensor Networks,” Computer Communications, vol. 32, no. 4, pp. 662-667, 2009.
[CrossRef] [Google Scholar] [Publisher Link]
[23] Nadeem Javaid et al., “An Energy-Efficient Distributed Clustering Algorithm for Heterogeneous WSNs,” EURASIP Journal on Wireless Communications and Networking, vol. 2015, no. 151, pp. 3-11, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[24] Brahim Elbhiri et al., “Developed Distributed Energy- Efficient Clustering (DDEEC) for Heterogeneous Wireless Sensor,” 2010 5th International Symposium on I/V Communications and Mobile Network, Rabat, Morocco, pp. 1-4, 2010.
[CrossRef] [Google Scholar] [Publisher Link]