Iot Based Design An Algorithm To Improve The Exhibition Framework In Wireless Sensor Networks

Abstract

In wireless sensor network (WSN) clustering of sensor nodes help in efficient routing to improve the network lifetime. Cluster head plays major role in the clustered WSN and thus needs larger energy. Therefore, it is important to select the optimal cluster head. However, previous works have given very less concentration on the clustering of mobile sensor nodes, density of the cluster and location of cluster. In our proposed work, we are implementing energy efficient and energy balanced clustering routing protocol for mobile WSN. The clustering is done using fuzzy C-mean clustering (FCM) algorithm and the clustering and cluster heads are further optimized using artificial bee colony algorithm (ABC). An ant colony optimization with forward and backward ants are utilized for the signal routing between cluster heads to the base station. Novel Admission Allotment Scheme (AAS) based intra-cluster communication to minimize overheads on the sensor nodes and packet drop. The proposed algorithm provides optimized cluster selection that offers better network lifetime, packet delivery ratio and throughput over traditional state of arts. Further, a location-aware, demand-based PMIPv6 extension for seamless mobility in the upcoming IoT networks. Utilizing location data and received signal strength (RSS), the suggested method effectively uses the network resources. The PMIPv6 protocol performs better with this solution in terms of signaling costs and network entity load. Additionally, mathematical models for signaling cost and load distribution are developed. The proposed approach is contrasted with the pre-existing PMIPv6 extension protocols based on RSS. The outcomes demonstrate that the suggested strategy improves performance and is resource-friendly for the upcoming large-scale IoT networks. newline newline newline