Hierarchical Proactive Caching for Vehicular Ad Hoc Networks

Gad, Mohamed E.; Hosny, Sameh; Mokhtar, Bassem; El-Sherif, Amr A.

doi:10.1109/niles.2019.8909331

Cited by 4 publications

(3 citation statements)

References 7 publications

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“…Moreover, the gains are amplified by the reduction in server load and cache redundancy is achieved. Some research works address the mobility-aware proactive caching in IoV, [16][17][18][19][20]. In the paper [16], authors consider vehicular caching where vehicles are also caching devices and propose a vehicular caching scheme in content-centric networks, developing an optimization model which minimizes the network's energy consumption.…”

Section: Related Workmentioning

confidence: 99%

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

Musa

Zennaro

Libsie

et al. 2022

Sensors

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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.

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Section: Related Workmentioning

confidence: 99%

“…Authors in [ 19 ] propose a hierarchical proactive caching scheme that considers vehicle and RSU caching. They formulate the optimization problem to minimize the vehicle communication’s latency.…”

Section: Background and Related Workmentioning

confidence: 99%

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

Musa

Zennaro

Libsie

et al. 2022

Sensors

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“…The effect of vehicle velocity has also been evaluated. Gad et al [10] designed a hierarchical proactive caching by utilising the storages at vehicles and RSUs to minimise the vehicle communication latency. Zhang et al [11] proposed a proactive caching scheme for autonomous vehicles by adopting a non-negative matrix factorization technique to estimate the preference of users.…”

Section: Related Workmentioning

confidence: 99%

Proactive Content Caching for Internet-of-Vehicles based on Peer-to-Peer Federated Learning

Min

et al. 2020

2020 IEEE 26th International Conference on Parallel and Distributed Systems (ICPADS)

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To cope with the increasing content requests from emerging vehicular applications, caching contents at edge nodes is imperative to reduce service latency and network traffic on the Internet-of-Vehicles (IoV). However, the inherent characteristics of IoV, including the high mobility of vehicles and restricted storage capability of edge nodes, cause many difficulties in the design of caching schemes. Driven by the recent advancements in machine learning, learning-based proactive caching schemes are able to accurately predict content popularity and improve cache efficiency, but they need gather and analyse users' content retrieval history and personal data, leading to privacy concerns. To address the above challenge, we propose a new proactive caching scheme based on peer-to-peer federated deep learning, where the global prediction model is trained from data scattered at vehicles to mitigate the privacy risks. In our proposed scheme, a vehicle acts as a parameter server to aggregate the updated global model from peers, instead of an edge node. A dual-weighted aggregation scheme is designed to achieve high global model accuracy. Moreover, to enhance the caching performance, a Collaborative Filtering based Variational AutoEncoder model is developed to predict the content popularity. The experimental results demonstrate that our proposed caching scheme largely outperforms typical baselines, such as Greedy and Most Recently Used caching.

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Comparative Study of Vehicular Proactive Caching Between Cellular and VLC Networks

Gad

Ismail

Hosny

et al. 2020

2020 15th International Conference on Computer Engineering and Systems (ICCES)

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Hierarchical Proactive Caching for Vehicular Ad Hoc Networks

Cited by 4 publications

References 7 publications

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

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

Proactive Content Caching for Internet-of-Vehicles based on Peer-to-Peer Federated Learning

Comparative Study of Vehicular Proactive Caching Between Cellular and VLC Networks

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