Abstract
Wireless sensor networks consist of thousands of sensor nodes that are battery-based and have a limited lifetime. Accordingly, performance and energy efficiency are big challenges in wireless sensor networks. In this regard, numerous techniques were studied and developed to reduce energy consumption. In this paper, a mathematical-based method has been proposed for the optimal selecting of the cluster head in wireless sensor networks. In the proposed algorithm, a node was selected as a cluster head that has the maximum energy, weight, and density, as well as the lowest total distance from the other nodes. In this respect, the problem was converted into a math function, which was solved by non-linear programming. The experiment results show that the presented algorithm is efficient, as compared with the other approaches that have, hitherto, been used to solve this problem.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
Power-efficient gathering in sensor information.
- 2.
Energy Aware Routing.
- 3.
Low Energy Adaptive Clustering Hierarchy.
- 4.
Balanced-clustering Energy Efficient.
References
Deosarkar, B.P., Yadav, N.S., Yadav, R.P.: Clusterhead selection in clustering algorithms for wireless sensor networks: a survey. In: 2008 International Conference on Computing, Communication and Networking, pp. 1–8 (2008)
Blum, C., Roli, A.: Metaheuristics in combinatorial optimization: overview and conceptual comparison. ACM Comput. Surv. CSUR 35(3), 268–308 (2003)
Amgoth, T., Jana, P.K.: Energy-aware routing algorithm for wireless sensor networks. Comput. Electr. Eng. 41, 357–367 (2015)
Li, M., Yang, B.: A survey on topology issues in wireless sensor network. In: ICWN, p. 503 (2006)
Younis, O., Fahmy, S.: HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Trans. Mob. Comput. 4, 366–379 (2004)
Lindesy, S., Raghavendra, C.: PEGASIS: power-efficient gathering in sensor information system. In: Proceedings of 2002 IEEE Aerospace Conference, pp. 1–6 (2002)
Barekatain, B., Dehghani, S., Pourzaferani, M.: An energy-aware routing protocol for wireless sensor networks based on new combination of genetic algorithm & k-means. Proc. Comput. Sci. 72, 552–560 (2015)
Pal, V., Singh, G., Yadav, R.P.: Cluster head selection optimization based on genetic algorithm to prolong lifetime of wireless sensor networks. Proc. Comput. Sci. 57, 1417–1423 (2015)
Hamidouche, R., Aliouat, Z., Gueroui, A.: Low energy-efficient clustering and routing based on genetic algorithm in WSNs. In: International Conference on Mobile, Secure, and Programmable Networking, pp. 143–156 (2018)
Kaur, S., Mahajan, R.: ACCGP: enhanced ant colony optimization, clustering and compressive sensing based energy efficient protocol (2017)
Cui, X.: Research and improvement of LEACH protocol in wireless sensor networks. In: 2007 International Symposium on Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications, pp. 251–254 (2007)
Rao, S.S.: Engineering Optimization: Theory and Practice. Wiley (2009)
Shankar, T., Shanmugavel, S., Rajesh, A.: Hybrid HSA and PSO algorithm for energy efficient cluster head selection in wireless sensor networks. Swarm Evol. Comput. 30, 1–10 (2016)
Jafarizadeh, V., Keshavarzi, A., Derikvand, T.: Efficient cluster head selection using Naïve Bayes classifier for wireless sensor networks. Wirel. Netw. 23(3), 779–785 (2017)
Lloret, J., Shu, L., Gilaberte, R.L., Chen, M.: User-oriented and service-oriented spontaneous ad hoc and sensor wireless networks. Ad Hoc Sens. Wirel. Netw. 14(1–2), 1–8 (2012)
Manjeshwar, A., Agrawal, D.P.: TEEN: a routing protocol for enhanced efficiency in wireless sensor networks. In: Null, p. 30189a (2001)
Cui, X., Liu, Z.: BCEE: a balanced-clustering, energy-efficient hierarchical routing protocol in wireless sensor networks. In: 2009 IEEE International Conference on Network Infrastructure and Digital Content, pp. 26–30 (2009)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Afshoon, M., Keshavazi, A., Darikvand, T., Bohlouli, M. (2020). Efficient Cluster Head Selection Using the Non-linear Programming Method for Wireless Sensor Networks. In: Bohlouli, M., Sadeghi Bigham, B., Narimani, Z., Vasighi, M., Ansari, E. (eds) Data Science: From Research to Application. CiDaS 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 45. Springer, Cham. https://doi.org/10.1007/978-3-030-37309-2_1
Download citation
DOI: https://doi.org/10.1007/978-3-030-37309-2_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-37308-5
Online ISBN: 978-3-030-37309-2
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)