Enhanced Augmented Reality Applications in Vehicle-to-Edge Networks

Pengyuan Zhou, Wenxiao Zhang, Tristan Braud, Pan Hui, Jussi Kangasharju

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Abstract

Vehicular communication applications, be it for driver-assisting augmented reality systems or fully driverless vehicles, require an efficient communication architecture for timely information delivery. Centralized, cloud-based infrastructures present latencies too high to satisfy the requirements of emergency information processing and transmission. In this paper, we present EARVE, a novel Vehicle-to-Edge infrastructure, with computational units co-located with the base stations and aggregation points. Embedding computation at the edge of the network allows to reduce the overall latency compared to vehicle-to-cloud and significantly trim the complexity of vehicle-to-vehicle communication. We present the design of EARVE and its deployment on edge servers. We implement EARVE through a bandwidth-hungry, latency constrained real-life application. We show that EARVE reduces the latency by up to 20% and the bandwidth at the server by 98% compared to cloud solutions at city scale.

Original languageEnglish
Title of host publicationPROCEEDINGS OF THE 2019 22ND CONFERENCE ON INNOVATION IN CLOUDS, INTERNET AND NETWORKS AND WORKSHOPS (ICIN)
EditorsA Galis, F Guillemin, R Noldus, S Secci, F Idzikowski, MF Sayit
Number of pages8
Place of PublicationNew York
PublisherIEEE
Publication date2019
Pages167-174
ISBN (Electronic)978-1-5386-8336-1
DOIs
Publication statusPublished - 2019
MoE publication typeA4 Article in conference proceedings
EventConference on Innovation in Clouds, Internet and Networks - Paris, France
Duration: 18 Feb 201921 Feb 2019
Conference number: 22

Publication series

NameConference on Innovations in Clouds Internet and Networks
PublisherIEEE
ISSN (Electronic)2472-8144

Fields of Science

  • 113 Computer and information sciences

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