  The Internet of Things (IoT) is a communication scheme which allows various
objects to exchange several types of information, enabling functions such as
home automation, production management, healthcare, etc. In addition,
energy-harvesting (EH) technology is considered for IoT environment in order to
reduce the need for management and enhance maintainability. Moreover, since
environments considering outdoor elements such as pedestrians, vehicles and
drones have been on the rise recently, it is important to consider mobility
when designing an IoT network management scheme. However, calculating the
optimal relaying topology is considered as an NP-hard problem, and finishing
computation for mobility environment before the channel status changes is
important to prevent delayed calculation results. In this article, our
objective is to calculate a sub-optimal relaying topology for stationary and
mobile system within reasonable computation time. To achieve our objective, we
validate an iterative balancing time slot allocation algorithm introduced in
the previous study, and propose a guided-mutation genetic algorithm (GMGA) that
modulates the mutation rate based on the channel status for rational
exploration. Additionally, we propose a mobility-aware iterative relaying
topology algorithm, which calculates relaying topology in a mobility
environment using an inheritance of the sub-optimal relaying topology
calculations. Simulation results verify that our proposed scheme effectively
solves formulated IoT network problems compared to other conventional schemes,
and also effectively handles IoT environments including mobility in terms of
minimum rate budget and computation time.
