Performance investigation of proposed adaptive heterogeneity in WSN
Keywords:Cluster Head, Heterogeneous WSN, Load Balancing, WSN Throughput, WSN Life Time
Recently Wireless Sensor Networks (WSNs) have become the optimal solution for handling many tasks. However, there are many tasks due to their critical situations need continues and a comprehensive monitoring of the environment. Accordingly, judicious designs of such networks are necessary. In this work, an adaptive scheme for enhancing the network performance in terms of load balancing during the heterogeneous WSN life time is proposed. The proposed scheme is based on dynamically modifying the probability of Cluster Heads (CHs) election in order to balance the load during the latest rounds when the network began to lose its power and thus weakening its reliability. The network performance is investigated based on the proposed scheme materialized by many scenarios. And it has shown that, adaptively electing CHs related to the network energy will enable the network to recover its reliability and enhancing the performance in terms of throughput and living nodes.
 A Ahmad, N Javaid, ZA Khan, U Qasim, T Alghamdi, Routing scheme to maximize lifetime and throughput of wireless sensor networks. Sensors J. IEEE. (2014), 3516â€“3532.
 H. Choe, H. Choo, QoS-aware adaptive data collection in wireless sensor networks, ICUIMC '14 Proceedings of the 8th International Conference on Ubiquitous Information Management and Communication (2014).
 Z. Ye , H. Mohamadian, Adaptive Clustering Based Dynamic Routing of Wireless Sensor Networks via Generalized Ant Colony Optimization , International Conference on Future Information Engineering (2014).
 B. Sepehr, Adaptive Clustering and Data Aggregation in Wireless Sensor Networks (ACDA), M.Sc. thesis in Computer Science, University of Guelph, Canada (2013).
 S. Jabbar, , A. Minhas , M. Imran , S. Khalid and K. Saleem, Energy Efficient Strategy for Throughput Improvement in Wireless Sensor Networks, sensors 23 January (2015) ISSN 1424-8220.
 M. Mirzaie, S. Mazinani, MCFL: an energy efficient multi-clustering algorithm using fuzzy logic in wireless sensor network", Springer,Wireless Networks,springer, Volume 24, Issue 6 (2018), pp 2251â€“2266.
 M. Toloueiashtian, H. Motamen, A new clustering approach in wireless sensor networks using fuzzy system, The Journal of Supercomputing Springer, Volume 74, Issue 2 (2018), pp 717â€“737.
 A. Rajagopal, S. Somasundaram, , B. Sowmya, Performance Analysis for Efficient Cluster Head Selection in Wireless Sensor Network Using RBFO and Hybrid BFO-BSO, International Journal of Wireless Communications and Mobile Computing, Vol. 6, Issue 1(2018).
 M. Mosleh,S. Q. Mahdi,"Analyzing the Heterogeneous and Homogeneous WSN in the Term of Total Energy Consumption", Journal of Engineering and Sustainable Development, Vol. 20, No. 04 (2014).
 W. Heinzelman, A. Chandrakasan, and H. Balakrishnan, ,An Application-Specific Protocol Architecture for Wireless Microsensor Networks, IEEE transactions on wireless communications, vol. 1, no. 4(2002). https://doi.org/10.1109/TWC.2002.804190.
 L. Barai, M. Gaikwad," Performance Evaluation of LEACH Protocol for Wireless Sensor Network", International Journal of Innovative Research in Advanced Engineering (IJIRAE) ISSN: 2349-2163, Volume 1 Issue 6 (July 2014).
 G. Smaragdakis, I. Matta, A. Bestavros, SEP: A Stable Election Protocol for clustered heterogeneous wireless sensor networks, Computer Science Department Boston University, Technical Report (2004).
 F. Aderohunmu, J. Deng, M. Purvis, Enhancing Clustering in Wireless Sensor Networks with Energy Heterogeneity, 18 International Journal of Business Data Communication and Networking",vol.7,no.4 (2011) pp. 18-31.
 A. Al_Baz and E. El_Sayed, A new algorithm for cluster head selection in LEACH protocol for wireless sensor networks, International Journal of Communication System, John Wiley & Sons, Ltd., 7 August 2017.