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Improving Content-Aware Video Streaming in Congested Networks with In-Network Computing

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Author(s):
Gobatto, Leonardo ; Saquetti, Mateus ; Diniz, Claudio ; Zatt, Bruno ; Cordeiro, Weverton ; Azambuja, Jose R. ; IEEE
Total Authors: 7
Document type: Journal article
Source: 2022 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS 22); v. N/A, p. 5-pg., 2022-01-01.
Abstract

Network congestion and packet loss pose an everincreasing challenge to video streaming. Despite the research efforts toward making video encoding schemes resilient to lossy network conditions, forwarding devices have not considered monitoring packet content to prioritize packets and minimize the impact of packet loss on video transmission. In this work, we advocate in favor of in-network computing employing a packet drop algorithm and an in-network hardware module to devise a solution for improving content-aware video streaming in congested network. Results show that our approach can reduce intra-predicted packet loss by over 80% at negligible resource usage and performance costs. (AU)

FAPESP's process: 20/05183-0 - SkyNet: towards smart data planes
Grantee:Luciano Paschoal Gaspary
Support Opportunities: Research Projects - Thematic Grants