Muti_Hop_Task_Routing_in_UAV_Assisted_Mobile_Edge_Computing_Networks_with_Intelligent_Reflective_Surfaces.pdf (798.79 kB)
Download fileMuti-Hop Task Routing in UAV-Assisted Mobile Edge Computing IoT Networks with Intelligent Reflective Surfaces
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posted on 2022-05-24, 21:35 authored by Yousef ShnaiwerYousef Shnaiwer, Nour Kouzayha, Mudassir Masood, Megumi Kaneko, Tareq Y. Al-NaffouriThe cooperation between Unmanned Aerial Vehicles
(UAVs) and ground Mobile Edge Computing (MEC) servers in
processing tasks is becoming one of the main research trends of
MEC networks. Despite the advantages of UAV-assisted MEC, it
is restricted by the limited battery capacity and sensitive energy
consumption of UAVs. Unlike the previous works where UAVs
are allowed to either process tasks locally or offload them to
ground MEC servers, in this paper, we propose a multi-hop
task routing solution for Internet of Things (IoT) networks
in which a UAV can also relay to another UAV with better
connection to a ground MEC server. Furthermore, the UAV can
make benefit of existing Intelligent Reflective Surfaces (IRSs) to
further improve tasks offloading and reduce energy consumption.
We show that the problem of minimizing the total energy of
UAVs is NP-hard, and we propose a graph-based heuristic
solution to solve it. Simulation results show that the proposed
graph-based solution outperforms the traditional no-relaying
scheme, especially when IRSs are deployed. Furthermore, a
Convolutional Neural Network (CNN) is devised to reduce the
delay of finding the decisions for the UAVs at the centralized
coordinator. Simulations show that the CNN achieves very close
energy consumption performance and a remarkable reduction in
execution time compared to the graph-based heuristic solution.