  Our current technological era is flooded with smart devices that provide
significant computational resources that require optimal video communications
solutions. Optimal and dynamic management of video bitrate, quality and energy
demands needs to take into account their inter-dependencies. With emerging
network generations providing higher bandwidth rates, there is also a growing
need to communicate video with the best quality subject to the availability of
resources such as computational power and available bandwidth. Similarly, for
accommodating multiple users, there is a need to minimize bitrate requirements
while sustaining video quality for reasonable encoding times.
  This thesis focuses on providing an efficient mechanism for deriving optimal
solutions for HEVC codec based on switching GOP configurations. The approach
provides a basic system for multi-objective optimization with constraints on
power, video quality, bitrate. This is accomplished by utilizing a recently
introduced framework known as Dynamically Reconfigurable Architectures for
Time-varying Image Constraints (DRASTIC) in HEVC/H.265 codec with six different
GOP configurations to support optimization modes for minimum bitrate, maximum
quality and minimum computational time (minimum energy in constant power
configuration) mode of operation. Pareto-Optimal GOP configs are used in
implementing these DRASTIC modes.
