Networking with aerial vehicles has evolved considerably over a period of time. Its applications range across a wide spectrum covering areas of military and civilian activities. Connectivity between aerial vehicles in ad hoc mode allows formation of multiple control units in the sky which have an ability to handle complex tasks. One of the major applications of these aerial vehicles is to coordinate simultaneously with another ad hoc network operating on the ground. This formation is termed as cooperative ad hoc networking. These networks operate on multiple data-sharing in form of cognitive maps. Thus, an efficient traffic management strategy is required to form a robust network. In this paper, an ambient network framework for coordination between ground and flying ad hoc network is presented. A fault-tolerant and robust connectivity strategy is proposed using neural, fuzzy and genetic modules. quaternion Kalman filter and its variant \(\alpha -\beta -\gamma \) filter is used to form the neural and decision system for guided aerial network. Effectiveness of the proposed traffic management framework for aerial vehicles is presented using mathematical simulations.
['Vishal Sharma', 'Rajesh Kumar']
G-FANET: an ambient network formation between ground and flying ad hoc networks