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Joint Optimization of Communication and Storage Latencies for Vehicular Edge Computing

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F24%3A00373670" target="_blank" >RIV/68407700:21230/24:00373670 - isvavai.cz</a>

  • Výsledek na webu

    <a href="https://doi.org/10.1109/TITS.2023.3336704" target="_blank" >https://doi.org/10.1109/TITS.2023.3336704</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/TITS.2023.3336704" target="_blank" >10.1109/TITS.2023.3336704</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Joint Optimization of Communication and Storage Latencies for Vehicular Edge Computing

  • Popis výsledku v původním jazyce

    The latency associated with accessing data stored on edge computing servers for vehicles encompasses both the communication between a vehicle and a server as well as a latency of a data storage system. To enable low-latency vehicular services, an efficient resource management should consider the communication as well as the storage I/O cache resource allocation along with a data access pattern and a priority of individual vehicular services. Therefore, we focus on a joint optimization of communication and storage I/O cache resource allocation for access to data of vehicular services hosted by the edge computing servers. The proposed framework determines the data placement for the services and allocates communication and storage I/O cache resources to each service. The objective is to minimize the overall latency experienced by vehicular services for access to data. The edge computing platforms share storage and communication resources among various vehicular services, each having distinct priorities and data access rates or patterns. Hence, to reflect different priorities of services in resource allocation, our objective metric takes into account the service priority, data access frequency, and latency. We propose a feasible solution using dual relaxation considering both communication and storage latencies. The proposed solution reduces the average latency of vehicular services by up to 1.8x compared to the state-of-the-art resource allocation method for vehicular edge computing. Even more notable improvement is observed for high priority vehicular services, where the proposal leads to 2.5x lower latency compared to the state-of-the-art storage I/O cache architecture for virtualized cloud services.

  • Název v anglickém jazyce

    Joint Optimization of Communication and Storage Latencies for Vehicular Edge Computing

  • Popis výsledku anglicky

    The latency associated with accessing data stored on edge computing servers for vehicles encompasses both the communication between a vehicle and a server as well as a latency of a data storage system. To enable low-latency vehicular services, an efficient resource management should consider the communication as well as the storage I/O cache resource allocation along with a data access pattern and a priority of individual vehicular services. Therefore, we focus on a joint optimization of communication and storage I/O cache resource allocation for access to data of vehicular services hosted by the edge computing servers. The proposed framework determines the data placement for the services and allocates communication and storage I/O cache resources to each service. The objective is to minimize the overall latency experienced by vehicular services for access to data. The edge computing platforms share storage and communication resources among various vehicular services, each having distinct priorities and data access rates or patterns. Hence, to reflect different priorities of services in resource allocation, our objective metric takes into account the service priority, data access frequency, and latency. We propose a feasible solution using dual relaxation considering both communication and storage latencies. The proposed solution reduces the average latency of vehicular services by up to 1.8x compared to the state-of-the-art resource allocation method for vehicular edge computing. Even more notable improvement is observed for high priority vehicular services, where the proposal leads to 2.5x lower latency compared to the state-of-the-art storage I/O cache architecture for virtualized cloud services.

Klasifikace

  • Druh

    J<sub>imp</sub> - Článek v periodiku v databázi Web of Science

  • CEP obor

  • OECD FORD obor

    20202 - Communication engineering and systems

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

    2024

  • 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

    25

  • Číslo periodika v rámci svazku

    6

  • Stát vydavatele periodika

    US - Spojené státy americké

  • Počet stran výsledku

    15

  • Strana od-do

    5435-5449

  • Kód UT WoS článku

    001126128800001

  • EID výsledku v databázi Scopus

    2-s2.0-85180328488