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Joint Content-Prefetching, Transmission Scheduling, and Rate Adaptation in Vehicular Networks.

Authors :
Berri, Sara
Zhang, Jun
Bensaou, Brahim
Labiod, Houda
Source :
IEEE Transactions on Vehicular Technology. Apr2022, Vol. 71 Issue 4, p4348-4358. 11p.
Publication Year :
2022

Abstract

Content prefetching at road side units (RSUs) in vehicular networks can improve users’ experience by reducing the average data access latency. Prefetching algorithms proposed in the literature usually rely on a fixed modulation scheme, that corresponds to the lowest possible data rate for RSU-to-vehicles transmission. As a consequence, the network bandwidth is often inefficiently used. In this article, we propose to study the problem of efficient content broadcasting in vehicular networks and express it as a joint data-prefetching and broadcast transmission scheduling optimization problem, subject to cache size constraints and transmission rate adaptation constraints. In our study we consider a highway scenario covered by several RSUs, and take into account the deadline requirement of interactive applications. We express the problem as an integer linear programming problem, and solve it using a heuristic algorithm that determines: the content prefetching schedule, the broadcast transmission schedule and the rate adaptation schedule sequentially. Simulation results show that, i) it is beneficial to use adaptive rates to broadcast data instead of relying on single-rate with unicast transmissions; ii) using vehicular trajectories and content popularity in conjunction yields better results than simply relying on content popularity for content prefetching and caching; and iii) this holds even with inaccurately predicted vehicle locations and with delay-sensitive contents. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00189545
Volume :
71
Issue :
4
Database :
Academic Search Index
Journal :
IEEE Transactions on Vehicular Technology
Publication Type :
Academic Journal
Accession number :
156718591
Full Text :
https://doi.org/10.1109/TVT.2022.3147979