Mobility-Aware Proactive Edge Caching Optimization Scheme in Information-Centric IoV Networks

Edge caching is a promising approach to alleviate the burden on the backhaul of network links. It has a significant role in the Internet of Vehicle (IoV) networks performance by providing cached data at the edge and reduce the burden of the core network caused by the number of participating vehicles...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2022-02, Vol.22 (4), p.1387
Main Authors: Musa, Salahadin Seid, Zennaro, Marco, Libsie, Mulugeta, Pietrosemoli, Ermanno
Format: Article
Language:English
Subjects:
Algorithms
Analysis
Bandwidths
Caching
Capital costs
Communication
edge caching
Efficiency
Information storage and retrieval
Internet
Internet of Vehicles
Markov analysis
Markov processes
mobility
Network latency
Numerical analysis
proactive content caching
roadside unit
Simulation methods
Traffic congestion
User satisfaction
Vehicles
vehicular caching
Wireless networks
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Summary:Edge caching is a promising approach to alleviate the burden on the backhaul of network links. It has a significant role in the Internet of Vehicle (IoV) networks performance by providing cached data at the edge and reduce the burden of the core network caused by the number of participating vehicles and data volume. However, due to the limited computing and storage capabilities of edge devices, it is hard to guarantee that all contents are cached and every requirement of the device are satisfied for all users. In this paper, we design an Information-Centric Network (ICN) with mobility-aware proactive caching scheme to provide delay-sensitive services on IoV networks. The real-time status and interaction of vehicles with other vehicles and Roadside Units (RSU) is modeled using a Markov process. Mobility aware proactive edge caching decision that maximize network performance while minimizing transmission delay is applied. Our numerical simulation results show that the proposed scheme outperforms related caching schemes in terms of latency by 20-25% in terms of latency and by 15-23% in cache hits.
ISSN:1424-8220
1424-8220
DOI:10.3390/s22041387