A Comprehensive Bibliographic Survey of the Standard Routing Protocols in Flying Ad Hoc Networks

Abstract

Now a days wireless ad hoc networks are used in various approaches. UAV ad hoc networks are
well organized networks compared with other ad hoc networks such as mobile and vehicular ad hoc
networks. Most of the FANET routing protocols extend from MANETs and VANETs. So that the adaptive
data relaying is very crucial for existing protocols of FANETs. The environment also changes the
transmission exposure of infrastructures. However, the machine learning reinforcement based technique
namely called as Q-learning is an adaptive technique to handle the greatly changing aspects of FANET with
conservational criticism as input, which provide adaptive routing scheme. In Q-learning, representatives
might frequently alter their accomplishment approaches rendering to the incentive of conservational
criticism to higher adapt to the energetic and unmaintainable topology. This paper proposes a Q-learning
based adaptive routing protocol to adapt the unsustainable FANET topology. The existing routing protocols
based on Q-learning uses a fixed value for parameters. In contrast, a proposed routing protocol can be
adjusted adaptively to the value of Q-learning parameters to adapt to a apotheosis changing aspects of
FANETs.