CFEC: An Ultra-Low Latency Microservices-Based In-Network Computing Framework for Information-Centric IoVs

被引:1
|
作者
Din, Muhammad Salah Ud [1 ,2 ]
Rehman, Muhammad Atif Ur [3 ]
Kim, Byung-Seo [4 ]
机构
[1] Hongik Univ, Dept Elect & Comp Engn, Sejong 30016, South Korea
[2] EURECOM Sophia Antipolis, F-06410 Biot, France
[3] Manchester Metropolitan Univ, Dept Comp & Math, Manchester M15 6BX, England
[4] Hongik Univ, Dept Software & Commun Engn, Sejong 30016, South Korea
基金
新加坡国家研究基金会;
关键词
Cloud computing; Delays; Storms; Microservice architectures; IP networks; Resource management; Real-time systems; Cloud; edge; fog; Internet of Things; microservices; named data networking; vehicular networks; DATA BROADCAST MITIGATION;
D O I
10.1109/TSC.2024.3463413
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The advancement of vehicular onboard units (OBUs) has led to compute-intensive and delay-sensitive vehicular applications. Undeniably edge-assisted static roadside computing terminal (sRCT) offers immediate computations, a surge of smart vehicles and intensive computation requests during crowded hours may overload the sRCT, leading to performance degradation and intolerable delays. Therefore, to facilitate proximate computations and achieve ultra-low latency, this article envisions a Consortium of mobile vehicular Fog, Edge, and Cloud (CFEC) an ultra-low latency microservices-centric in-network computing framework for vehicular Named Data networks (VNDN). CFEC develops a fog-profiler-assisted mobile vehicular fog based on vehicles' mobility patterns and available resource characteristics to ensure reliable computation offloading and reverse-path stability in a dynamic vehicular environment. Furthermore, CFEC introduces an intermediary ZTMC controller that effectively filters out underutilized sRCTs and routes computation requests to nearby, filtered sRCTs, thus minimizing transmission time and accelerating computations even during crowded hours. Simulations results revealed that CFEC significantly reduces computational satisfaction delays by up to 32.5%, 48.5%, and 31.9%, 51.025% against varying interest and node rates, respectively while in extreme traffic conditions, CFEC achieved an impressive computation satisfaction ratio of around 85% compared with benchmark schemes.
引用
收藏
页码:3199 / 3212
页数:14
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