AHSWN Home · Issue Contents · Forthcoming Papers

TFMSC-OSCRAI:Trust Based optimized Secure Clustering Multipath Routing Protocol for Wireless Sensor Networks
Ujwala N. Ravale and Gautam M. Borkar

In Wireless Sensor Networks (WSNs), trustworthy and reliable data delivery is a difficult challenge because of its features and limitations. In this research, an optimized and secure clustering multi-path routing protocol using a type-2 fuzzy trust evaluation approach for WSNs is proposed, which addresses the need for secured data delivery and the energy as well as security trade-off. To deal with uncertainty in cluster head selection, fuzzy logic is being applied. Cluster heads an important role in managing traffic within and between clusters through the use of multi-hop communication, which increases congestion and increases the risk of performance issues. All transmission evidences are first converted into trust values using a fuzzy trust evaluation method, which successfully reduces trust uncertainty. The proposed Trust-Based Fuzzy Model for Secure Clustering (TFMSC) utilizes a K-Means algorithm to analyze the trust values acquired through fuzzy trust evaluation. Further proposed Optimized Secure Clustering and Routing using Artificial Intelligence (OSCRAI) is used for selecting optimal cluster heads and to find optimized routes for a mobile sink. The simulations demonstrate that the combination of the proposed trust-based secure clustering technique with OSCRAI effectively protects the network from malicious internal nodes. This method not only enhances the security of the network but also optimizes the route path and the selection of cluster heads (CHs). The Experimental results show packet delivery ratio is 89.96% and throughput has been improved by 10%. In addition, average energy consumption had been reduced by 13% and routing overhead reduced by 34%.

Keywords: Cluster Head, Type-2 Fuzzy Trust evaluation, K-Means, artificial intelligence