Evolutionary gravitational neocognitron neural network based block chain technology for a secured dynamic optimal routing in wireless sensor networks

Abstract

ABSTRACT In this manuscript, Evolutionary Gravitational Neocognitron Neural-Network-based Block chain Technology is proposed for a Secured Dynamic Optimal Routing in Wireless Sensor Networks (BT-SDOR-WSN-EGNNN). The purpose of block chain (BC) technology is to distribute the distributed routing information management depending on secure BC token transactions. The Proof-of-Authority (PoA)-based consensus process is selected for effectual transaction in BC wireless sensor networks. The Evolutionary Gravitational Neocognitron Neural Network (EGNNN) is considered to select salient nodes denote the features of node-based validators. The Evolutionary Gravitational Neocognitron Neural Network model enhances the collection of validators by the attributes corresponding to every node. Then, Trust-Based Secure Intelligent Opportunistic Routing Protocol (TBSIOP) is employed to assist routing nodes and makes more informed routing decisions and choose the dependable routing links. The proposed approach is simulated in Network Simulator (NS-2) tool. The performance metrics, such as average latency, average energy consumption, and throughput of blockchain token transactions, is examined. From the simulation, the proposed BT-SDOR-WSN-EGNNN method attains 76.26%, 65.57%, 48.99%, 42.9% lesser delay during 25% malicious routing environment, 73.06%, 63.82%, 59.25%, 38.84% lesser delay during 50% malicious routing environment analysed to the existing BT-SDOR-WSN-DCNN, BT-SDOR-WSN-MDP, BT-SDOR-WSN-RL and BT-SDOR-WSN-WL-DCNN methods.