A Trusted Distributed Routing Scheme for Wireless Sensor Networks Using Block Chain and Jelly Fish Search Optimizer Based Deep Generative Adversarial Neural Network (Deep-GANN) Technique

• Published in: Wireless personal communications 2022-09, Vol.126 (2), p.1101-1128
• Main Authors: Raja, L., Periasamy, P. S.
• Format: Article
• Language: English
• Subjects: Algorithms; Blockchain; Communications Engineering; Computer Communication Networks; Computer simulation; Cryptography; Data collection; Efficiency; Engineering; Networks; Neural networks; Nodes; Packets (communication); Routing (telecommunications); Signal,Image and Speech Processing; Wireless networks; Wireless sensor networks
• ISSN: 0929-6212; 1572-834X
• DOI: 10.1007/s11277-022-09784-x

Wireless sensor network (WSN) is used to collect and monitor the data from various environments, such as temperature, pressure, humidity and speed. After that, the collected data is transferred to the base station using sink nodes. While transferring this information, the nodes are attacked by malicious attacks that lead to black hole problem, which can also affects the efficiency, packet delivery ratio and throughput in the network. The previous works does not provide the sufficient result to overcome the above problem. Therefore, in this manuscript, a trusted distributed routing scheme for WSN Using Block chain and Jelly Fish Search Optimizer algorithm (JSOA) based Deep Generative Adversarial Neural Network (DGANN) method is proposed to overcome the above problem. Here, the Block chain routing protocol is used to detect, store and transfer the packets from source to destination in trusted distribution or efficient manner. The network is used to improve the security and efficiency of the DGANN method. The weight parameters of the DGANN are optimized by JSOA. The objective function is to maximize the efficiency of the network by minimizing the black hole problem and to increase the packet delivery ratio and the throughput by reducing the delay and attackers. The simulation process is carried out in MATLAB. From the simulation, the proposed approach attains better performance of higher average packet delivery ratio 25.13%, higher network lifetime 34.56%, higher throughput 27.6%, higher energy efficiency 37.44%, lower delay 18.6%, lower drop 13.56%, lower packet overhead 23.6% when compared with the existing approaches, like multidimensional scaling-map (MDS-MAP), trust aware routing protocol through multiple attributes (TRPM), dynamic rate aware classified key distributional secure routing (DRCKDS) algorithm for routing on WSNs respectively.