An Intelligent Hybrid Cuckoo Search Genetic Algorithm based Imposter Node Aware Node Failure Detection Approach in MANETS
Node failure detection is the most difficult task in the mobile wireless network environment with high mobility. High rate of node failure would reduce the performance level of network which should be concentrated high to ensure the node failure detection rate. In this research work, these problems are concentrated and introduced the new techniques which can efficiently detect and prevent the node failures happening on the environment. In this research method, node failure can be avoided considerably by supplying required resources instead re-establishing another route path. This is ensured by clustering the mobile nodes based on node importance level as like done in our previous work and resources among the cluster members are shared with each other to ensure the enough resource availability. The cluster head is responsible for handling the cluster members and control the data sharing between cluster members. In this work optimal cluster head selection is performed by introducing the Hybrid Cuckoo Search Genetic algorithm (HCSGA). In this research work, Imposter Node aware Node Failure Detection Method (IN-NFDM) is introduced to avoid the false information about the node failure from the imposter nodes which might act as genuine neighbour nodes. Also, the proposed work is compared with location aware node failure detection method which consists of Hybrid Particle Swarm Optimization Fire Fly Algorithm (HPSOFFA) for cluster head selection.
Author's Name: K.B. Manikandan and Dr.N. Sasirekha
Volume: Volume 15
Issues: Issue 3
Keywords: Mobile Wireless Sensor Network (MWSN), Failure Node, Cluster Head (CH), Cuckoo Search (CS), Genetic Algorithm (GA), Imposter Node (IN), Particle Swarm Optimization (PSO), Fire Fly Algorithm (FFA).