An Improved SEED Clustering Model for Wireless Sensor Networks

Year 2021, , 521 - 528, 01.06.2021

Sercan Yalçın , Ebubekir Erdem

https://doi.org/10.2339/politeknik.700947

Abstract

It is important to develop clustering methods to collect data efficiently in wireless sensor networks (WSNs). Among the clustering methods in the literature, the most popular on behalf of balanced energy depletion and increasing the life of the network is heterogeneous clustering consisting of nodes with different characteristics. In this study, Sleep-awake Energy Efficient Distributed (SEED) clustering method that is a heterogeneous clustering, has been improved. In this sense, the mechanism of the SEED has been developed on behalf of the data sending-receiving, and energy consumption. According to the proposed method, the nodes in the WSN perceive the data in specified time periods and do not transmit and receive data by staying asleep at certain times. The most important difference of the proposed algorithm from the SEED method is that the remaining energy of the nodes and the network average energy are added to the threshold value in the cluster head (CH) selection. Moreover, cluster formation and CH selection enables more effective method than SEED algorithm by providing cluster members to communicate with CHs, and then the data transmission process is also included in the method process. Thus, energy consumption is reduced and network life is elongated by choosing the optimum CHs. The proposed method has been compared with both the SEED algorithm and other heterogeneous clustering methods existing in the literature in the simulation environment. The results of the simulations show the advantages of the recommended method.

Keywords

Wireless sensor networks, energy efficiency, data gathering, heterogeneous clustering

References

• [1] Yarinezhad, R. and Hashemi, S. N.,” A routing algorithm for wireless sensor networks based on clustering and an fpt-approximation algorithm”, Journal of Systems and Software, 155: 145-161, (2019).
• [2] Oladimeji, M. O., Turkey, M. and Dudley, S., ”HACH: Heuristic Algorithm for Clustering Hierarchy protocol in wireless sensor networks”, Applied Soft Computing, 55: 452-461, (2017).
• [3] Chang, J.-Y. and Ju, P.-H.,” An energy-saving routing architecture with a uniform clustering algorithm for wireless body sensor networks” , Future Generation Computer Systems,35: 129-140,(2014).
• [4] Vancin, S. and Erdem, E., “Performance analysis of the energy efficient clustering models in wireless sensor”, 24th IEEE Int. Conf. on Elect, Circ. and Sys. (ICECS), Batumi, Georgia, 247-251, (2017).
• [5] Vancin, S. and Erdem, E., “Threshold Balanced Sampled DEEC Model for Heterogeneous Wireless Sensor Network”, Wireless Communication and Mobil Computing, 6: 1–12, (2018).
• [6] Heinzelman, W. R., Chandrakasan, A. P. and Balakrishnan, H., “Energy efficient communication protocol for wireless micro sensor networks”, in: Proc. of the 33rd Hawaii Int. Conf. on Sys. Sci.(HICSS-33), January, (2000).
• [7] Lindsey, S. and Raghavenda, C. S., “PEGASIS: Power efficient gathering in sensor information systems”, in: Proc. of the IEEE Aerospace Conf., Big Sky, Montana, 1-6, (2002).
• [8] Smaragdakis, G., Matta, I. and Bestavros, A., “SEP: A Stable Election Protocol for clustered heterogeneous wireless sensor network”, in: Sec. Int. Workshop on Sensor and Actor Network Protocols and Applications (SANPA), 97(7): 1-11, (2004).
• [9] Younis, O. and Fahmy, S.,, “HEED: A hybrid, energy efficient, distributed clustering approach for ad hoc sensor networks”, IEEE Trans. on Mob. Comp., 3(4): 660-669, (2004).
• [10] Qing, L., Zhu, Q. and Wang, M., “Design of a distributed energy-efficient clustering algorithm for heterogeneous wireless sensor network”, Computer Communications, 29: 2230- 2237, (2006).
• [11] Saini, P. and Sharma, A. K., “E-DEEC- Enhanced Distributed Energy Efficient Clustering Scheme for heterogeneous WSN”, in: 2010 1st Int. Conf. on Parallel, Dist. and Grid Comp., 914-919, (2010).
• [12] Aslam, M., Shah, T., Javaid, N., Rahim, A., Rahman, Z. and Khan, Z.A., “CEEC:centralized energy efficient clustering a new routing protocol for WSNS”, in:Proc.IEEESECON, (2012).
• [13] Kang, T. Yun, J., Lee H. et al., “A Clustering Method for Energy Efficient Routing in Wireless Sensor Networks,” in Proceedings of the International Conference on Electronics, Hardware, Wireless and Optical Communications, 133–138, Corfu Island, Greece, (2007).
• [14] Singh, J. Singh, B. P. and Shaw, S., “A new LEACH-based routing protocol for energy optimization inWireless Sensor Network,” in Proceedings of the 5th IEEE International Conference on Computer and Communication Technology, ICCCT 2014, 181–186, September 2014.
• [15] Kumar, A. and Katiyar, V.K., “Intelligent Cluster Routing: An Energy Efficient Approach for Routing in Wireless Sensor Networks”, International Journal of Computer Applications, 110(5): 18–22, (2015).
• [16] Yalçın, S. and Erdem, E., "Bacteria Interactive Cost and Balanced-Compromised Approach to Clustering and Transmission Boundary-Range Cognitive Routing in Mobile Heterogeneous Wireless Sensor Networks", Sensors 2019, 19(4): 1-30, (2019).
• [17] AT, N. and SM, D. “A New Energy Efficient Clustering-based Protocol for Heterogeneous Wireless Sensor Networks” ,Journal of Electrical & Electronic Systems, 4(3):1-7, (2015).
• [18] Ahmet, G., Zou, J., Fareed, M.M.S. and Zeeshan, M., “Sleep- awake energy efficient distributed clustering algorithm for wireless sensor networks”, Computer and Electrical Engineering, 56: 385-398, (2015).