King's College London

Research portal

QUIC-EST: A QUIC-Enabled Scheduling and Transmission Scheme to Maximize VoI with Correlated Data Flows

Research output: Contribution to journalArticlepeer-review

Federico Chiariotti, Anay Ajit Deshpande, Marco Giordani, Konstantinos Antonakoglou, Toktam Mahmoodi, Andrea Zanella

Original languageEnglish
Article number9433511
Pages (from-to)30-36
Number of pages7
JournalIEEE COMMUNICATIONS MAGAZINE
Volume59
Issue number4
DOIs
PublishedApr 2021

Bibliographical note

Funding Information: This project has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie Grant agreement No. 813999 (WINDMILL). Publisher Copyright: © 1979-2012 IEEE. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

King's Authors

Abstract

Progress in communication technologies has fostered the development of advanced interactive applications that require multi-sensor data transmission with low latency and high reliability. Since these requirements are not guaranteed by current application-agnostic transport protocols, these applications mostly have to rely on customized, application-level scheduling and flow control mechanisms, which lack generality and transparency, making it difficult to jointly control the information flows of different applications. In this work, we propose a unified framework to support the transmission of correlated data flows. We assume that the applications are able to describe the correlation among their data streams and the related service requirements in terms of a value of information (VoI) matrix. Hence, we propose QUIC-EST, a transmission scheme that combines the congestion control and multi-stream features of the recently proposed QUIC transport protocol with a proper scheduling algorithm to maximize the VoI at the receiver. To illustrate the idea, we propose the analysis of two relevant use cases, namely inter-vehicular and haptic communications, and demonstrate through simulations how the proposed approach can significantly outperform current transport schemes.

View graph of relations

© 2020 King's College London | Strand | London WC2R 2LS | England | United Kingdom | Tel +44 (0)20 7836 5454