國立虎尾科技大學 |

Enabling Delay-Sensitive Modern Vehicular Applications by Using Resource Limited Vehicular Edge Computing Systems.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Enabling Delay-Sensitive Modern Vehicular Applications by Using Resource Limited Vehicular Edge Computing Systems./
Author:	Ku, Yu-Jen.
Description:	1 online resource (166 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 85-01, Section: B.
Contained By:	Dissertations Abstracts International85-01B.
Subject:	Electrical engineering. -
Online resource:	click for full text (PQDT)
ISBN:	9798379916411

Enabling Delay-Sensitive Modern Vehicular Applications by Using Resource Limited Vehicular Edge Computing Systems.
Ku, Yu-Jen.

Enabling Delay-Sensitive Modern Vehicular Applications by Using Resource Limited Vehicular Edge Computing Systems. - 1 online resource (166 pages)

Source: Dissertations Abstracts International, Volume: 85-01, Section: B.

Thesis (Ph.D.)--University of California, San Diego, 2023.

Includes bibliographical references

This study aims at using Road-side Unit (RSU)-assisted Vehicular Edge Computing (VEC) systems to support nowadays compute-intensive and delay-sensitive vehicular applications. Vehicles can offload these applications to the VEC server at the RSU to ease the burden on their limited onboard computing resources. Although VEC servers usually have higher computing capacity than vehicles, their computing resource, as well as the RSU's communication and energy resources, are not unlimited due to deployment constraints and operating costs. Our goal is to find the optimal resource allocation strategies for the RSU-assisted VEC systems to enable low-latency compute-intensive vehicular applications for vehicles.In the first part of the study, we consider Solar-powered RSU-assisted VEC systems, where the RSUs are solely powered by solar energy. Firstly, we aim to minimize service disruption of the offloaded vehicular applications under the intermittent solar power supply. We propose a two-phase approach that jointly optimizes solar energy usage and storage, user association, and RSU's computing and communication resource allocation for the involved RSUs and vehicles in the VEC system. Secondly, we further reduce the application's execution delay by a framework that uses computing resources from both the VEC server and the vehicle's local computing (VLC) unit for application execution through task partitioning and offloading. Furthermore, the framework is able to adjust the VEC server's platform configuration and balance between the vehicular application's execution delay and its application-level performance, according to the available computing, communication, and solar energy resources of the Solar-powered RSU.In the second part of the study, we focus on using the RSU-assisted VEC system to support an emerging advanced vehicular application, the multi-vehicle perception fusion. It is challenging to effectively allocate RSU's computing and communication resources to support the multi-vehicle perception fusion application due to its complex and uncertain task composition natures. To minimize the end-to-end delay of the above application, we present a real-time mechanism that jointly determines the optimal RSU's computing and communication resource allocation, as well as task partitioning and scheduling strategies, which are adaptive to the dynamic task composition of the application.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798379916411Subjects--Topical Terms:

596380
Electrical engineering.
Subjects--Index Terms:

Renewable energyIndex Terms--Genre/Form:

554714
Electronic books.

Enabling Delay-Sensitive Modern Vehicular Applications by Using Resource Limited Vehicular Edge Computing Systems.
LDR:03893ntm a22004217 4500 001 1143793
005 20240517104954.5
006 m o d
007 cr mn ---uuuuu
008 250605s2023 xx obm 000 0 eng d
020 $a 9798379916411
035 $a (MiAaPQ)AAI30522072
035 $a AAI30522072
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Ku, Yu-Jen. $3 1468584
245 1 0 $a Enabling Delay-Sensitive Modern Vehicular Applications by Using Resource Limited Vehicular Edge Computing Systems.
264 0 $c 2023
300 $a 1 online resource (166 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertations Abstracts International, Volume: 85-01, Section: B.
500 $a Advisor: Dey, Sujit.
502 $a Thesis (Ph.D.)--University of California, San Diego, 2023.
504 $a Includes bibliographical references
520 $a This study aims at using Road-side Unit (RSU)-assisted Vehicular Edge Computing (VEC) systems to support nowadays compute-intensive and delay-sensitive vehicular applications. Vehicles can offload these applications to the VEC server at the RSU to ease the burden on their limited onboard computing resources. Although VEC servers usually have higher computing capacity than vehicles, their computing resource, as well as the RSU's communication and energy resources, are not unlimited due to deployment constraints and operating costs. Our goal is to find the optimal resource allocation strategies for the RSU-assisted VEC systems to enable low-latency compute-intensive vehicular applications for vehicles.In the first part of the study, we consider Solar-powered RSU-assisted VEC systems, where the RSUs are solely powered by solar energy. Firstly, we aim to minimize service disruption of the offloaded vehicular applications under the intermittent solar power supply. We propose a two-phase approach that jointly optimizes solar energy usage and storage, user association, and RSU's computing and communication resource allocation for the involved RSUs and vehicles in the VEC system. Secondly, we further reduce the application's execution delay by a framework that uses computing resources from both the VEC server and the vehicle's local computing (VLC) unit for application execution through task partitioning and offloading. Furthermore, the framework is able to adjust the VEC server's platform configuration and balance between the vehicular application's execution delay and its application-level performance, according to the available computing, communication, and solar energy resources of the Solar-powered RSU.In the second part of the study, we focus on using the RSU-assisted VEC system to support an emerging advanced vehicular application, the multi-vehicle perception fusion. It is challenging to effectively allocate RSU's computing and communication resources to support the multi-vehicle perception fusion application due to its complex and uncertain task composition natures. To minimize the end-to-end delay of the above application, we present a real-time mechanism that jointly determines the optimal RSU's computing and communication resource allocation, as well as task partitioning and scheduling strategies, which are adaptive to the dynamic task composition of the application.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2024
538 $a Mode of access: World Wide Web
650 4 $a Electrical engineering. $3 596380
650 4 $a Computer science. $3 573171
650 4 $a Alternative energy. $3 1241221
650 4 $a Automotive engineering. $3 1104081
653 $a Renewable energy
653 $a Roadside units
653 $a Task dependency
653 $a Task offloading
653 $a Task partitioning
653 $a Vehicular edge computing
655 7 $a Electronic books. $2 local $3 554714
690 $a 0544
690 $a 0984
690 $a 0363
690 $a 0540
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a University of California, San Diego. $b Electrical and Computer Engineering. $3 1465765
773 0 $t Dissertations Abstracts International $g 85-01B.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30522072 $z click for full text (PQDT)