Web
Analytics

Cooperative Game Theory Approach for Energy-Efficient Node Clustering in Wireless Sensor Network

       Chaeriah Bin Ali Wael, Nasrullah Armi, Arumjeni Mitayani, Suyoto Suyoto, Salita Ulitia Prini, Winy Desvasari, Rico Dahlan, Ros Sariningrum

Abstract


Energy consumption is one of the critical challenges in designing wireless sensor network (WSN) since it is typically composed of resource-constrained devices. Many studies have been proposed clustering to deal with energy conservation in WSN. Due to its predominance in coordinating the behaviors of many players, game theory has been considered for improving energy efficiency in WSN. In this paper, we evaluate the performance of cooperative game theoretic clustering (CGC) algorithm which employs cooperative game theory in a form of 3-agent cost sharing game for energy-efficient clustering in WSN. Furthermore, we compared its performance to a well-known traditional clustering method, low-energy adaptive clustering hierarchy (LEACH), in terms of network lifetime and stability, and total residual energy. The simulation results show that CGC has better performance compared to LEACH due to the cooperation among cluster heads in coalition. CGC has higher alive nodes with stability improvement of first node dies (FND) by 65%, and the improvement by 52.4% for half node dies (HND). However, with the increasing of the number of nodes, the performance of LEACH is getting better compared to CGC.

  http://dx.doi.org/10.14203/jet.v20.76-81

Keywords


WSN clustering algorithm; CGC; LEACH; cooperative game theory; cost sharing game; shapley value; FND; HND

Full Text:

  PDF

References


H. Park, J.H. Eom, T.M. Chung, “Energy-efficient distance based clustering routing scheme for wireless sensor networks,” in Proc. International Conference on Computational Science and Its Applications, Aug. 2007, pp. 195-206. Crossref

V. Gupta, R. Pandey, “An improved energy aware distributed unequal clustering protocol for heterogeneous wireless sensor networks,” Engineering Science and Technology, an International Journal, vol. 19, no. 2, pp. 1050-1058, 2016. Crossref

B. Jan, H. Farman, H. Javed, B. Montrucchio, M. Khan, S. Ali, “Energy efficient hierarchical clustering approaches in wireless sensor networks: A survey,” Wireless Communications and Mobile Computing, 2017. Crossref

A. Karmaker, M.S. Alam, M.M. Hasan, A. Craig, “An energy‐efficient and balanced clustering approach for improving throughput of wireless sensor networks,” International Journal of Communication Systems, vol. 33, no. 3, e4195, 2020. Crossref

R. Sinde, F. Begum, K. Njau, S. Kaijage, “Refining network lifetime of wireless sensor network using energy-efficient clustering and DRL-based sleep scheduling,” Sensors, 20(5), p. 1540, 2020. Crossref

W. Akkari, B. Bouhdid, A. Belghith, “LEATCH: Low Energy Adaptive Tier Clustering Hierarchy,” InANT/SEIT, Jan. 2015, pp. 365-372. Crossref

W. Abidi, T. Ezzedine, “New approach for selecting cluster head based on LEACH protocol for wireless sensor networks,” in Proc. International Conference on Evaluation of Novel Approaches to Software Engineering, vol. 2, 2017, pp. 114-120 . Crossref

G.M. Tamilselvan, K. Gandhimathi, “Network coding based energy efficent LEACH protocol for WSN,” Journal of applied research and technology, vol. 17, no. 1, pp. 1-7, 2019. Crossref

Y. Yang, C. Lai, L. Wang, X. Wang, “A energy-aware clustering algorithm via game theory for wireless sensor networks,” in Proc. 12th International Conference on Control, Automation and Systems, Oct. 2012, pp. 261-266.

A. Attiah, M. Chatterjee, C.C. Zou, “A game theoretic approach for energy-efficient clustering in wireless sensor networks,” in Proc. 2017 IEEE Wireless Communications and Networking Conference (WCNC), Mar. 2017, pp. 1-6. Crossref

S. Kassan, J. Gaber, P. Lorenz, “Game theory based distributed clustering approach to maximize wireless sensors network lifetime,” Journal of Network and Computer Applications, vol. 123, pp.80-88, 2018. Crossref

H. Jing, H. Aida, “A cooperative game theoretic approach to clustering algorithms for wireless sensor networks,” in Proc. 2009 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing, Aug. 2009, pp. 140-145. Crossref

H. Jing, H. Aida, “Cooperative Clustering Algorithms for Wireless Sensor Networks,” in Smart Wireless Sensor Networks, H.D. Chinh, Y.K. Tan, Ed., Rijeka, Croatia: InTech, 2010, pp. 157-172. Crossref

Z. Beiranvand, A. Patooghy, M. Fazeli, “I-LEACH: an efficient routing algorithm to improve performance & to reduce energy consumption in wireless sensor networks,” in Proc. The 5th Conference on Information and Knowledge Technology, 2013, pp. 13-18. Crossref

C. Vimalarani, R. Subramanian, S.N. Sivanandam, “An enhanced PSO-based clustering energy optimization algorithm for wireless sensor network,” The Scientific World Journal, 2016. Crossref


Article Metrics

Metrics Loading ...

Metrics powered by PLOS ALM

Refbacks

  • There are currently no refbacks.




Copyright (c) 2020 Jurnal Elektronika dan Telekomunikasi

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.