DeepNDN: Opportunistic Data Replication and Caching in Support of Vehicular Named Data

Manzo, Gaetano; Kalogeiton, Eirini; Di Maio, Antonio; Braun, Torsten; Palattella, Maria Rita; Turcanu, Ion; Soua, Ridha; Rizzo, Gianluca (9 October 2020). DeepNDN: Opportunistic Data Replication and Caching in Support of Vehicular Named Data. In: WOWMOM 2020 : 21st IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks. Cork, Ireland. Jun 15, 2020 - Jun 20, 2020. 10.1109/WoWMoM49955.2020.00051

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Although many target applications in VANETs are information-centric, the performance of Named Data Networking (NDN) in vehicular ad-hoc networks is severely hampered by persistent network partitioning, typical of many vehicular scenarios. Existing approaches try to address this issue by relying on opportunistic communications. However, they leave open the crucial issue of how to guarantee content persistence and tight QoS levels while optimizing the resource utilization in the vehicular environment. In this work we propose DeepNDN, a communication scheme based on the joint application of NDN and of probabilistic spatial content caching, which enables content retrieval in fragmented and dynamic network topologies with tight delay constraints. We present a data-based approach to DeepNDN management, based on locally modulating content replication and delivery in order to achieve a target hit ratio in a resource-efficient manner. Our management algorithm employs a Convolutional Neural Network (CNN) architecture for effectively capturing the complex relations between spatio-temporal patterns of mobility and content requests and DeepNDN performance. Its numerical assessment in realistic, measurement-based scenarios suggest that our management approach achieves its target set goals while outperforming a set of reference schemes.

Item Type:	Conference or Workshop Item (Paper)
Division/Institute:	08 Faculty of Science > Institute of Computer Science (INF) > Communication and Distributed Systems (CDS) 08 Faculty of Science > Institute of Computer Science (INF)
UniBE Contributor:	Kalogeiton, Eirini, Braun, Torsten
Subjects:	000 Computer science, knowledge & systems 500 Science > 510 Mathematics
Language:	English
Submitter:	Dimitrios Xenakis
Date Deposited:	18 Feb 2020 11:07
Last Modified:	05 Dec 2022 15:36
Publisher DOI:	10.1109/WoWMoM49955.2020.00051
URI:	https://boris.unibe.ch/id/eprint/140334