Binomial Logistic Regression Resource Optimized Routing in MANET

MANETs consist of the node that moves continuously in a random direction. In MANET architecture, devices can move in any direction. They have recently confined imperativeness, enlisting power and memory. The hubs of the system are versatile and the topology changes quickly. In binomial logistic regression resource optimized routing in MANET (BLR-OR), disappointment methodology includes visit hub distinguished a high directing overhead and stretched out start to finish postponement and power. The proposed method used logistic regression technique to detect optimal network path. It can be obtained depending on neighbor node using coefficient value. Regression coefficient is directed by thinking about the vitality, latency, and transmission capacity of versatile hub by utilizing the coefficient incentive to choose the mobile node with high energy, latency, and bandwidth utilization for communicating packets in MANET and enhance lifetime of the network (N-L), packet delivery ratio(P-D-R) in successful way. The presentation of BLR-OR regression procedure is estimated regarding energy consumption (E-C), end-to-end delay (E-E-D).