Computational Offloading for Autonomous Systems: Real-World Experiments and Modeling

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F25%3A00387459" target="_blank" >RIV/68407700:21230/25:00387459 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1109/VTC2025-Spring65109.2025.11174768" target="_blank" >https://doi.org/10.1109/VTC2025-Spring65109.2025.11174768</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/VTC2025-Spring65109.2025.11174768" target="_blank" >10.1109/VTC2025-Spring65109.2025.11174768</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Computational Offloading for Autonomous Systems: Real-World Experiments and Modeling

Popis výsledku v původním jazyce

We focus on computation offloading from moving devices, such as mobile robots or autonomous vehicles to MultiAccess Edge Computing (MEC) servers via mobile network. To this end, we develop and implement a prototype of small autonomous vehicle with capability to offload processing of sensor data to MEC server via mobile network. Then, we investigate an impact of communication channel on delay and energy consumed by the autonomous vehicle for two practical applications, namely road sign recognition and path planning, in the real-world environment with a real physical equipment. Via experiments, we demonstrate benefits of the computation offloading on both energy and delay. The experiments highlight the potential of MEC for the autonomous systems allowing to reduce cost and increase scalability of such autonomous systems. Furthermore, based on the real-world experiments, we derive detailed models of energy consumption and delay for both practical applications.

Název v anglickém jazyce

Computational Offloading for Autonomous Systems: Real-World Experiments and Modeling

Popis výsledku anglicky

We focus on computation offloading from moving devices, such as mobile robots or autonomous vehicles to MultiAccess Edge Computing (MEC) servers via mobile network. To this end, we develop and implement a prototype of small autonomous vehicle with capability to offload processing of sensor data to MEC server via mobile network. Then, we investigate an impact of communication channel on delay and energy consumed by the autonomous vehicle for two practical applications, namely road sign recognition and path planning, in the real-world environment with a real physical equipment. Via experiments, we demonstrate benefits of the computation offloading on both energy and delay. The experiments highlight the potential of MEC for the autonomous systems allowing to reduce cost and increase scalability of such autonomous systems. Furthermore, based on the real-world experiments, we derive detailed models of energy consumption and delay for both practical applications.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20203 - Telecommunications

Projekt

<a href="/cs/project/LUASK22064" target="_blank" >LUASK22064: Prediktivní alokace výpočetních prostředků pro autonomní řízení na hraně sítě</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

2025 IEEE 101st Vehicular Technology Conference: VTC2025-Spring

ISBN

979-8-3315-3147-8

ISSN

2577-2465

e-ISSN

2577-2465

Počet stran výsledku

7

Strana od-do

—

Název nakladatele

IEEE

Místo vydání

Piscataway

Místo konání akce

Oslo

Datum konání akce

17. 6. 2025

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

001699882900488