Trust based Fuzzy Cluster Head Selection in Wireless Sensor Networks

Document Type : Persian Original Article

Authors

1 Faculty of Computer Engineering and Information Technology, Sadjad University , Mashhad, Iran.

2 Faculty of Electrical and Computer Engineering, Semnan University, Semnan, Iran.

Abstract

Wireless sensor networks consist of a large number of sensor nodes scattered over a limited geographical area. The main challenge of these networks is energy consumption. Clustering is a well-known way to save energy and extend network's lifetime. Many studies iteratively change the cluster formation to increase the network's lifetime; however, this issue imposes high energy consumption on clusters. Also, some clustering methods select individual cluster heads for near clusters, which leads to more energy consumption. Another major issue is selecting untrusted and unreliable nodes as headers because it leads to unreliable interactions between nodes and reduces the security of the network. The proposed method aims to provide an efficient clustering method that, in addition to having the benefits of energy consumption management, can provide a secure path for interaction and communication between nodes by identifying malicious nodes and not selecting them as headers. For this purpose, each node's chance is calculated using the fuzzy approach, and nodes that have the highest chances are considered cluster heads. The efficiency of the proposed method is compared with state-of-the-art methods. Also, the process of cluster formation is done by fuzzy logic and by defining the objective function consisting of residual energy, distance to the base station, and the average intra-cluster distance. The statistical analysis indicates that the proposed method on average provides better results than other competitors and the results demonstrate how this method at least improves life time and residual energy by 59.83% and 14.75%, respectively.

Keywords

References

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Journal of Soft Computing and Information Technology
Volume 10, Issue 4 - Serial Number 34
Winter
January 2022
Pages 15-28

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