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

Vishal Sharma*, Rajesh Kumar, Prashant Singh Rana

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)

Abstract

Unmanned aerial vehicles (UAVs) allow formation of wide range ad hoc networks. These ad hoc formations with unmanned vehicles provide coverage of vast areas of applications involving mission dependent activities. Such networks can solve various issues related to civilian and military activities. One of the main applications of these networks is continuous surveillance. Surveillance by multiple nodes in ad hoc mode is directly dependent upon the continuous data sharing, cooperative decision making and stabilized network formation. Failures in network can hinder the performance and can decrease its operability. It is difficult to aloof network from discrete failures. Therefore, stabilized model is required which can provide stability to the whole network. For this, a self-healing neural model is developed which is capable of handling uncertain failures. It also provides provision for recovery of nodes from failure to stabilized state.

Original languageEnglish
Pages (from-to)2013-2016
JournalIEEE Communications Letters
Volume19
Issue number11
DOIs
Publication statusPublished - 15 Sep 2015
Externally publishedYes

Keywords

  • Analytical models
  • Linear programming
  • Neural networks
  • Neurons
  • Stability analysis
  • Training
  • Vehicles

ASJC Scopus subject areas

  • Modelling and Simulation
  • Computer Science Applications
  • Electrical and Electronic Engineering

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