Efficient and Secure Remote Health Management in Cloud in Vehicular Adhoc Network Environment

Abstract

Vehicle Ad Hoc Networks (VANETs) is a crucial communications framework for transferring messages between any healthcare systems. The dilemma of fixing the safest efficient route is a tedious issue in VANET. Hence the secure and most reliable way will give the appropriate solution for the routing issues in the VANET. In this paper, by using the Multi-Objective Bio-inspired Heuristic Cuckoo Search Node optimization algorithm is designed to find the efficient safest route for transferring health data within a short period. After seeing the efficient route, the node can be distinguished upon the traffic and security by using the Stochastic Discriminant Random Forest Node Classifier. Then in the selected route, the nodal distance can be calculated by applying the delay-based weighted end-to-end approach for traffic analysis. Then the authentic vehicle node can be analyzed through the Trust Aware extreme Gradient Boosting Node Classification based Secured Routing (TAXGBNC-SR) Technique. The obtained information that can be stored in the cloud. It deal with the multiple number of tasks gives to the ARM micro-controllers in order to perform the multiple tasks that gets logged in the cloud via Internet of Things technology (Iot).