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Deep RL-based Ellipsoidal Path Planning for MEC enabled UAVs to Minimize Data Transmission Latency and Energy Consumption of Mobile Devices

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Abstract
Due to the flexible deployment and movement capability, unmanned aerial vehicles (UAVs) are being utilized as flying mobile edge computing (MEC) platforms, offering real-time computational resources and low-latency data processing for a wide range of applications. The aim of this article is to explore a multi-UAV-assisted MEC system where multiple UAVs move using ellipsoidal trajectory to provide MEC services to resource-constrained mobile devices in temporary hotspot areas such as festival areas that have delay-sensitive applications with varying task offloading requests. Depending on the position, size, shape, and orientation of the ellipsoidal trajectories, the coverage area, energy consumption of mobile devices, and task transmission latency changes. Moreover, the varying user densities and task offloading request rates make the problem more challenging. Thus, we formulate an optimization problem that finds the center position, major radius, minor radius, and rotation angle of the ellipsoidal trajectory of UAV-assisted MEC servers with the objective of minimizing transmission latency and energy consumption of mobile devices while taking into account the required data transmission rate, task transmission time, energy consumption and several system-related constraints. Then, we have transformed this optimization problem into a Markov decision process and propose a deep Q-learning-based ellipsoidal trajectory optimization (DETO) algorithm to resolve it. The results from our simulations demonstrate that our approach outperforms other baselines, particularly in terms of reducing latency and the energy required for mobile devices to transmit data.
Author(s)
사디아 라베야
Issued Date
2024
Awarded Date
2024-02
Type
Dissertation
URI
https://oak.ulsan.ac.kr/handle/2021.oak/13076
http://ulsan.dcollection.net/common/orgView/200000728967
Alternative Author(s)
SADIA RABEYA
Affiliation
울산대학교
Department
일반대학원 전기전자컴퓨터공학과
Advisor
Seokhoon Yoon
Degree
Master
Publisher
울산대학교 일반대학원 전기전자컴퓨터공학과
Language
eng
Rights
울산대학교 논문은 저작권에 의해 보호받습니다.
Appears in Collections:
Computer Engineering & Information Technology > 1. Theses(Master)
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