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

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.

Publication Details

Journal
e-space (Manchester Metropolitan University)
Published
2024-12-30
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
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article

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

e-space (Manchester Metropolitan University)
IoT and Edge/Fog Computing
article

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

article en

Abstract

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.

e-space (Manchester Metropolitan University)
National Research Foundation, Ministry of Trade, Industry and Energy, Korea Institute for Advancement of Technology, National Research Foundation of Korea, Ministry of Science and ICT, South Korea
Decent work and economic growth
Openalex Percentile: Top 50%
IoT and Edge/Fog Computing
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