OEE-WCRD: Optimizing Energy Efficiency in Wireless Sensor Networks through Cluster Head Selection Using Residual Energy and Distance Metrics

Lalit Kumar Tyagi; Anoop Kumar

doi:10.4108/eetsis.4268

Authors

Lalit Kumar Tyagi Banasthali University
Anoop Kumar Banasthali University

DOI:

https://doi.org/10.4108/eetsis.4268

Keywords:

Base Station, Cluster, Residual Energy, Sensor Node, Wireless Sensor Network

Abstract

Wireless Sensor Networks (WSNs) play a pivotal role in various applications, including environmental monitoring, industrial automation, and healthcare. However, the limited energy resources of sensor nodes pose a significant challenge to the longevity and performance of WSNs. To address this challenge, this paper presents an Optimized Energy Efficient Protocol in Wireless Sensor Networks through Cluster Head Selection Using Residual Energy and Distance Metrics (OEE-WCRD). This research paper presents a novel approach to cluster head selection in WSNs by harnessing a combination of residual energy and distance metrics. The proposed method aims to significantly enhance the energy efficiency of WSNs by prioritizing nodes with ample residual energy and proximity to their neighbors as cluster heads. Through extensive simulations and evaluations, we demonstrate the effectiveness of this approach in prolonging network lifetime, optimizing data aggregation, and ultimately advancing the energy efficiency of WSNs, making it a valuable contribution to the field of WSNs protocols.

References

Narayan, Vipul, A. K. Daniel, and Pooja Chaturvedi. "E-FEERP: Enhanced Fuzzy based Energy Efficient Routing Protocol for Wireless Sensor Network." Wireless Personal Communications (2023): 1-28.

Tyagi, Lalit Kumar, et al. "Energy Efficient Routing Protocol Using Next Cluster Head Selection Process In Two-Level Hierarchy For Wireless Sensor Network." Journal of Pharmaceutical Negative Results (2022): 4772-4783.

Narayan, Vipul, and A. K. Daniel. "CHOP: Maximum coverage optimization and resolve hole healing problem using sleep and wake-up technique for WSN." ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal 11.2 (2022): 159-178.

Narayan, Vipul, and A. K. Daniel. "FBCHS: Fuzzy Based Cluster Head Selection Protocol to Enhance Network Lifetime of WSN." ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal 11.3 (2022): 285-307.

Narayan, Vipul, A. K. Daniel, and Pooja Chaturvedi. "E-FEERP: Enhanced Fuzzy based Energy Efficient Routing Protocol for Wireless Sensor Network." Wireless Personal Communications (2023): 1-28.

NARAYAN, VIPUL, A. K. Daniel, and Pooja Chaturvedi. "FGWOA: An efficient heuristic for cluster head selection in WSN using fuzzy based grey wolf optimization algorithm." (2022).

Narayan, Vipul, and A. K. Daniel. "CHHP: coverage optimization and hole healing protocol using sleep and wake-up concept for wireless sensor network." International Journal of System Assurance Engineering and Management 13.Suppl 1 (2022): 546-556.

Choudhary, Shubham, et al. "Fuzzy approach-based stable energy-efficient AODV routing protocol in mobile ad hoc networks." Software Defined Networking for Ad Hoc Networks. Cham: Springer International Publishing, 2022. 125-139.

Narayan, Vipul, and A. K. Daniel. "Energy Efficient Protocol for Lifetime Prediction of Wireless Sensor Network using Multivariate Polynomial Regression Model." (2022).

Chaturvedi, Pooja, Ajai Kumar Daniel, and Vipul Narayan. "Coverage Prediction for Target Coverage in WSN Using Machine Learning Approaches." (2021).

Narayan, Vipul, and A. K. Daniel. "IOT based sensor monitoring system for smart complex and shopping malls." International conference on mobile networks and management. Cham: Springer International Publishing, 2021.

Narayan, Vipul, and A. K. Daniel. "A novel approach for cluster head selection using trust function in WSN." Scalable Computing: Practice and Experience 22.1 (2021): 1-13.

Narayan, Vipul, and A. K. Daniel. "RBCHS: Region-based cluster head selection protocol in wireless sensor network." Proceedings of Integrated Intelligence Enable Networks and Computing: IIENC 2

Narayan, Vipul, and A. K. Daniel. "Multi-tier cluster based smart farming using wireless sensor network." 2020 5th international conference on computing, communication and security (ICCCS). IEEE, 2020.

Narayan, Vipul, A. K. Daniel, and Ashok Kumar Rai. "Energy efficient two tier cluster based protocol for wireless sensor network." 2020 international conference on electrical and electronics engineering (ICE3). IEEE, 2020.

Narayan, Vipul, and A. K. Daniel. "Design consideration and issues in wireless sensor network deployment." (2020): 101-109.

Narayan, Vipul, and A. K. Daniel. "Novel protocol for detection and optimization of overlapping coverage in wireless sensor networks." Int. J. Eng. Adv. Technol 8 (2019).

Gulati, K.; Kumar Boddu, R.S.; Kapila, D.; Bangare, S.L.; Chandnani, N.; Saravanan, G. A review paper on wireless sensor network techniques in Internet of Things (IoT). Mater. Today Proc. 2022, 51, 161–165.

Majid, M.; Habib, S.; Javed, A.R.; Rizwan, M.; Srivastava, G.; Gadekallu, T.R.; Lin, J.C.W. Applications of Wireless Sensor Networks and Internet of Things Frameworks in the Industry Revolution 4.0: A Systematic Literature Review. Sensors 2022, 22, 2087.

G. Arumugam, T. Ponnuchamy, 2015, ”EE-LEACH: development of energy-efficient LEACH Protocol for data gathering in WSN”, EURASIP Journal on Wireless Communications and Networking ,76, DOI 10.1186/s13638-015-0306-5.

Hassan Oudani, SalahddineKrit, LahoucineElmaimouni and Jalal Laassiri, 2016, ”Comparative Study and Simulation of Flat and Hierarchical Routing Protocols for Wireless Sensor Network”, International Conference In Engineering & MIS (ICEMIS), IEEE, pp. 1-9

G. Arumugam, T. Ponnuchamy, 2015, ”EE-LEACH: development of energy-efficient LEACH Protocol for data gathering in WSN”, EURASIP Journal on Wireless Communications and Networking ,76, DOI 10.1186/s13638-015-0306-5.

J. Jia, J. Chen, G. Chang, Y. Wen and J. Song, 2009, “Multi-objective optimization for coverage control in wireless sensor network with adjustable sensing radius”, Elsevier, Computers and Mathematics with Applications, Vol. 57, pp. 1767-1775.

T. Qiu, F. Xia, L. Feng, G. Wu and B. Jin, 2011, “Queueing theory based path delay analysis of wireless sensor networks”, Advances in Electrical and Computer Engineering (AECE), vol. 11, no. 2,.

Zhao, F.; Gao, N.; Zhang, K. WSNs Clustering Routing Protocol Based on Whale Optimization Algorithm and Beetle Antennae Search. Transducer Microsyst. Technol. 2022, 41, 42–45.

Sarkar, A.; Senthil Murugan, T. Cluster head selection for energy efficient and delay-less routing in wireless sensor network. Wirel. Netw. 2019, 25, 303–320.

Qiu, S.; Li, A. Application of Chaos Mutation Adaptive Sparrow Search Algorithm in Edge Data Compression. Sensors 2022, 22, 5425.

Vivekanand, C.V.; Bagan, K.B. Secure Distance Based Improved Leach Routing to Prevent Puea in Cognitive Radio Network. Wirel. Pers. Commun. 2020, 113, 1823–1837.

S. Kannadhasan and R.Nagarajan , 2018, “Performance Improvement of Slot Antenna Using Various Parameters and Band Pass Filter,” 2018 International Conference on Circuits and Systems in Digital Enterprise Technology (ICCSDET), IEEE Press, pp-128-131. 15.

Yongmin Zhang, Shibo He and Jiming Chen, 2017, “Near Optimal Data Gathering in Rechargeable Sensor Networks with a Mobile Sink”, IEEE Transactions on Mobile Computing, Volume 16, Issue 6, pp.1718-1729

4. Xue, J.; Shen, B. A novel swarm intelligence optimization approach: Sparrow search algorithm. Syst. Sci. Control Eng. 2020, 8, 22–34.

Gai, J.; Zhong, K.; Du, X.; Yan, K.; Shen, J. Detection of gear fault severity based on parameter-optimized deep belief network using sparrow search algorithm. Measurement 2021, 185, 110079.

Chu, K.C.; Horng, D.J.; Chang, K.C. Numerical Optimization of the Energy Consumption for Wireless Sensor Networks Based on an Improved Ant Colony Algorithm. IEEE Access 2019, 7, 105562–105571.

Rao, P.C.S.; Jana, P.K.; Banka, H. A particle swarm optimization based energy efficient cluster head selection algorithm for wireless sensor networks. Wirel. Netw. 2017, 23, 2005–2020.

C. Dhivya Devi and B.Santhi, 2013, “Study on Security Protocols in Wireless Sensor Networks”, International Journal of Engineering and Technology, Vol.5, No.5, pp.200-207,.

M. Revathi and Dr. B. Amutha, 2017, “A Survey on Security Protocols in Wireless Sensor Network”, International Journal of Pure and Applied Mathematics, Vol.5, No.5, pp.250-257

Narayan, V., Daniel, A.K. & Chaturvedi, P. E-FEERP: Enhanced Fuzzy Based Energy Efficient Routing Protocol for Wireless Sensor Network. Wireless Pers Commun 131, 371–398 (2023). https://doi.org/10.1007/s11277-023-10434-z

D. V. S. Babu, N. Gireesh, M. L. Ravi Chandra, and Ravilla Dilli, "Optimization of Cluster Head Selection and Enhancing Energy Efficiency in Wireless Sensor Networks Using Novel Metaheuristic Algorithms," Telecommunications and Radio Engineering, vol. 82, no. 4, pp. 1-22, March 10, 2023.

DilipKumar Jang Bahadur, L. Lakshmanan, “A novel method for optimizing energy consumption in wireless sensor network using genetic algorithm”, Microprocessors and Microsystems, Volume 96, 2023, 104749, ISSN 0141-9331, https://doi.org/10.1016/j.micpro.2022.104749.

Bharany Salil, Sharma Sandeep, Alsharabi Naif, Tag Eldin Elsayed, Ghamry Nivin A., “Energy-efficient clustering protocol for underwater wireless sensor networks using optimized glowworm swarm optimization”, Frontiers in Marine Science, 10, 2023, 10.3389/fmars.2023.1117787

Rami Reddy, M.; Ravi Chandra, M.L.; Venkatramana, P.; Dilli, R. Energy-Efficient Cluster Head Selection in Wireless Sensor Networks Using an Improved Grey Wolf Optimization Algorithm. Computers 2023, 12, 35. https://doi.org/10.3390/computers12020035

Imourane Abdoulaye, Laurent Rodriguez, Cecile Belleudy, Benoit Miramond. Energy Conservation in Wireless Sensor Networks using Embedded Artificial Neural Networks. 17ème Colloque National 2023 SOC 2 , Jun 2023, Lyon, France. , 2023.

Faiz, M., & Daniel, A. K. (2023). A hybrid WSN based two-stage model for data collection and forecasting water consumption in metropolitan areas. International Journal of Nanotechnology, 20(5-10), 851-879.

Channi, H. K., Sandhu, R., Faiz, M., & Islam, S. M. (2023, August). Multi-Criteria Decision-Making Approach for Laptop Selection: A Case Study. In 2023 3rd Asian Conference on Innovation in Technology (ASIANCON) (pp. 1-5). IEEE.

Faiz, M., Fatima, N., & Sandhu, R. (2023). A Vaccine Slot Tracker Model Using Fuzzy Logic for Providing Quality of Service. Multimodal Biometric and Machine Learning Technologies: Applications for Computer Vision, 31-52.

Sandhu, R., Singh, A., Faiz, M., Kaur, H., & Thukral, S. (2023). Enhanced Text Mining Approach for Better Ranking System of Customer Reviews. Multimodal Biometric and Machine Learning Technologies: Applications for Computer Vision, 53-69.

Sandhu, R., Bhasin, C., Faiz, M., & Islam, S. M. (2023, August). Managing E-Reviews: A Performance Enhancement Technique Using Deep Learning. In 2023 Second International Conference On Smart Technologies For Smart Nation (SmartTechCon) (pp. 662-666). IEEE.

Faiz, M., Sandhu, R., Akbar, M., Shaikh, A. A., Bhasin, C., & Fatima, N. (2023). Machine Learning Techniques in Wireless Sensor Networks: Algorithms, Strategies, and Applications. International Journal of Intelligent Systems and Applications in Engineering, 11(9s), 685-694.