Self-Healing Neural Model for Stabilization Against Failures Over Networked UAVs


Unmanned aerial vehicles (UAVs) permit formation of wide range unplanned networks. These spontanepous formations with unmanned vehicles give coverage of vast areas of applications involving mission dependent activities. Such networks can solve varied problems connected to civilian and military activities. One among the main applications of these networks is continuous surveillance. Surveillance by multiple nodes in unintentional mode is directly dependent upon the continuous data sharing, cooperative call creating and stabilized network formation. Failures in network can hinder the performance and can decrease its operability. It's troublesome to aloof network from discrete failures. So, stabilized model is needed that will offer stability to the whole network. For this, a self-healing neural model is developed that is capable of handling uncertain failures. It conjointly provides provision for recovery of nodes from failure to stabilized state.

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