DefinePK

Abstract

MANET and fifth-generation mobile network (5G) are attained greater significance in next-generation because of their simplicity and efficiency in handling real problems in diverse applications. The data communication in 5G networks has improved the number of users and the information transmission rate among the nodes in network. Though, the connection among these nodes has to continually renew because of mobility, connection failure, routing overhead and low battery energy. Therefore, it utilizes more energy in searching and connecting the mobile nodes during the process of data routing. Therefore, Brown Boosted Expectation Maximization Ensemble Node Clustering (BBEMENC) Technique is planned in this paper with objective of decreasing the energy employment during the processes of reliable data sharing in MANET using 5G. In the BBEMENC Technique, more numbers of mobile nodes are taken as training samples. Furthermore, Expectation Maximization (EM) clusters are assumed weak clusters. In BBEMENC Technique, EM clusters is applied for grouping all the nodes in network as strong strength or weak node based on their residual energy, trust and bandwidth availability. Subsequently, weak clusters outcomes are united to get strong cluster results where it accurately finds strong strength and weak nodes in MANET. Finally, BBEMENC Technique choose the nearest strong strength nodes as optimal in order to efficiently route the data packets between the source and destination in 5G mobile network. From that, BBEMENC Technique gains a higher routing performance with better packet delivery ratio and latency. The simulation of BBEMENC Technique is done by considering the metrics such as energy utilization, packet delivery ratio, latency and scalability with varying numbers of input mobile nodes and data packets.