Joint Management of Communication, Computing, and Storage Resources for Low Latency Vehicular Edge Computing

Result code in 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>

Result on the web

<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>

Result language

angličtina

Original language name

Joint Management of Communication, Computing, and Storage Resources for Low Latency Vehicular Edge Computing

Original language description

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.

Czech name

—

Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

20203 - Telecommunications

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

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

Publication year

2025

Confidentiality

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

Name of the periodical

IEEE Transactions on Intelligent Transportation Systems

ISSN

1524-9050

e-ISSN

1558-0016

Volume of the periodical

26

Issue of the periodical within the volume

11

Country of publishing house

US - UNITED STATES

Number of pages

16

Pages from-to

18471-18486

UT code for WoS article

001575980100001

EID of the result in the Scopus database

2-s2.0-105016866814