Architecture for AI-Enabled Multimodal Semantic Communication and Distributed Computing

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F25%3A00389505" target="_blank" >RIV/68407700:21230/25:00389505 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1109/VTC2025-Spring65109.2025.11174887" target="_blank" >https://doi.org/10.1109/VTC2025-Spring65109.2025.11174887</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/VTC2025-Spring65109.2025.11174887" target="_blank" >10.1109/VTC2025-Spring65109.2025.11174887</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Architecture for AI-Enabled Multimodal Semantic Communication and Distributed Computing

Popis výsledku v původním jazyce

In this paper, we propose novel architecture supporting artificial intelligence-based multimodal semantic communication and distributed computing. The proposed architecture is built on existing concepts in adopted mobile networks, including cloud radio access network (C-RAN) and open-RAN (O-RAN). On top of current architectures, we introduce new key features including block for artificial intelligence (AI) training models for semantic encoding and decoding, semantic modules, and hierarchical edge cloud for distributed and parallel processing. Then, we formulate a delay minimization problem for processing of semantically encoded tasks by the hierarchical edge cloud. First, we derive optimal closed-form solutions for splitting the tasks between individual tiers of the hierarchical edge cloud while assuming actual communication and computing queues. Second, we propose a low-complexity algorithm selecting place, where the individual tasks are processed while adopting the optimal splitting of the tasks. Via simulations, we demonstrate that the proposed solution decreases average processing time and energy consumption due to computing by up to 50 % and 23 % when compared to the best performing state-of-the-art scheme.

Název v anglickém jazyce

Architecture for AI-Enabled Multimodal Semantic Communication and Distributed Computing

Popis výsledku anglicky

In this paper, we propose novel architecture supporting artificial intelligence-based multimodal semantic communication and distributed computing. The proposed architecture is built on existing concepts in adopted mobile networks, including cloud radio access network (C-RAN) and open-RAN (O-RAN). On top of current architectures, we introduce new key features including block for artificial intelligence (AI) training models for semantic encoding and decoding, semantic modules, and hierarchical edge cloud for distributed and parallel processing. Then, we formulate a delay minimization problem for processing of semantically encoded tasks by the hierarchical edge cloud. First, we derive optimal closed-form solutions for splitting the tasks between individual tiers of the hierarchical edge cloud while assuming actual communication and computing queues. Second, we propose a low-complexity algorithm selecting place, where the individual tasks are processed while adopting the optimal splitting of the tasks. Via simulations, we demonstrate that the proposed solution decreases average processing time and energy consumption due to computing by up to 50 % and 23 % when compared to the best performing state-of-the-art scheme.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20203 - Telecommunications

Projekt

<a href="/cs/project/TH85010001" target="_blank" >TH85010001: Multimodální sémantická komunikace a výpočty s využitím Al</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

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

1-7

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

001699882900605