Block chain based trusted distributed routing scheme using optimized dropout ensemble extreme learning neural network in MANET

Mobile ad hoc network (MANET) is a set of mobile nodes that communicate via wireless networks while moving from one place to another. Numerous studies have been done on increasing reliable between routing nodes, trust management, the use of cryptographic systems, and centralized routing decisions and so on. However, the majority of routing methods are challenging to execute in real-world scenarios, because it is challenging to determine the malicious behaviors of routing nodes. There is still no reliable method to prevent malicious node attacks. Due to these networks' dynamic and decentralized character, packet routing in MANET is difficult. To overcome this problem, this manuscript proposes a Dropout Ensemble Extreme Learning Neural Network (DrpEnXLNN) optimized with Metaheuristic Anopheles Search routing algorithm(MASA) based Token fostered Block chain Technology for trusted distributed optimal routing in Mobile adhoc networks. The aim of this work is to provide the most efficient method for data transmission and generates tokens for packet stream admittance with a secret key that goes to each routing mobile node. Subsequently, the trusted routing information is distributed by proposed block chain(BC) based mobile ad hoc network utilizing DrpEnXLNN optimized with MASA. The proposed technique is simulated in NS-2(Network Simulator) tool. The performance metrics, such as average delay, average latency, average energy consume, throughput of block chain token transactions are evaluated. Finally, the proposed TDRP-MASA-DrpEnXLNN-BCMANET method attains 22% and 14% less delay during 25% spiteful routing environment, 15% and 8% less delay during 50% spiteful routing environment when analyzed to the existing models.