Joint Management of Communication, Computing, and Storage Resources for Low Latency Vehicular Edge Computing
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F25%3A00389271" target="_blank" >RIV/68407700:21230/25:00389271 - isvavai.cz</a>
Výsledek na webu
<a href="https://doi.org/10.1109/TITS.2025.3601353" target="_blank" >https://doi.org/10.1109/TITS.2025.3601353</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/TITS.2025.3601353" target="_blank" >10.1109/TITS.2025.3601353</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Joint Management of Communication, Computing, and Storage Resources for Low Latency Vehicular Edge Computing
Popis výsledku v původním jazyce
Low-latency Vehicular Edge Computing (VEC) applications require an efficient VEC resource allocation considering all components contributing to application latency, i.e., computation, communication, and storage. While the optimization of communication and computation resources is broadly addressed in literature, storage, a significant source of latency in the computing stack, is often ignored in existing works. Thus, in this paper, we optimize the communication and computation resources together with the storage resources to minimize the latency of VEC applications. The problem of jointly minimizing communication, computation, and storage latency under practical constraints is NP-hard. Hence, we employ dual decomposition and Lagrangian relaxation to achieve a computationally viable solution for the joint communication, computing, and storage resource allocation to VEC applications. To this end, we define a dual problem of the assignment of VEC applications to base stations. This problem corresponds to the perfect matching problem in a weighted bipartite graph and optimally solvable by algorithms with polynomial computation complexity. Then, as the solution to the dual problem may violate some constraints of the main resource allocation problem, we find a feasible solution to the main resource allocation problem using Lagrangian relaxation. We show that the joint optimization of all three aspects, i.e., communication, computation, and storage, reduces the overall offloading latency up to 60% compared to state-of-the-art works.
Název v anglickém jazyce
Joint Management of Communication, Computing, and Storage Resources for Low Latency Vehicular Edge Computing
Popis výsledku anglicky
Low-latency Vehicular Edge Computing (VEC) applications require an efficient VEC resource allocation considering all components contributing to application latency, i.e., computation, communication, and storage. While the optimization of communication and computation resources is broadly addressed in literature, storage, a significant source of latency in the computing stack, is often ignored in existing works. Thus, in this paper, we optimize the communication and computation resources together with the storage resources to minimize the latency of VEC applications. The problem of jointly minimizing communication, computation, and storage latency under practical constraints is NP-hard. Hence, we employ dual decomposition and Lagrangian relaxation to achieve a computationally viable solution for the joint communication, computing, and storage resource allocation to VEC applications. To this end, we define a dual problem of the assignment of VEC applications to base stations. This problem corresponds to the perfect matching problem in a weighted bipartite graph and optimally solvable by algorithms with polynomial computation complexity. Then, as the solution to the dual problem may violate some constraints of the main resource allocation problem, we find a feasible solution to the main resource allocation problem using Lagrangian relaxation. We show that the joint optimization of all three aspects, i.e., communication, computation, and storage, reduces the overall offloading latency up to 60% compared to state-of-the-art works.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
20203 - Telecommunications
Návaznosti výsledku
Projekt
Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Ostatní
Rok uplatnění
2025
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
IEEE Transactions on Intelligent Transportation Systems
ISSN
1524-9050
e-ISSN
1558-0016
Svazek periodika
26
Číslo periodika v rámci svazku
11
Stát vydavatele periodika
US - Spojené státy americké
Počet stran výsledku
16
Strana od-do
18471-18486
Kód UT WoS článku
001575980100001
EID výsledku v databázi Scopus
2-s2.0-105016866814