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Md. Mahir Ashhab

dblp:426/1327 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2025
0009-0002-5321-1357ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
1 paper
Transport protocols and congestion control · 44% Content delivery and video streaming · 44% Datacenter networks · 13%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Transport protocols and congestion control › explicit congestion notification
ECN-based congestion control
0.912025
Poster: ECN-based Congestion Control for WebRTC · IMC 2025
Content delivery and video streaming › video transmission
real-time video transmission
0.912025
Poster: ECN-based Congestion Control for WebRTC · IMC 2025
Datacenter networks
low-latency networking
0.312025
Poster: ECN-based Congestion Control for WebRTC · IMC 2025

Methods — techniques the papers use, named apart from their topics

ECN feedback · 0.9
YearPublicationVenuePosition
2025 Poster: ECN-based Congestion Control for WebRTC
abstract
Real-time communication (RTC) applications require low packet delay and loss while maintaining a stable throughput. WebRTC, a widely used framework, relies on Google Congestion Control (GCC). Meanwhile, newer methods like L4S (Low Latency, Low Loss, Scalable Throughput) provide opportunities with early congestion signaling. In this work, we extend client-side WebRTC to support L4S by adding ECN-based rate control and ECN feedback handling. Our results show that L4S improves real-time performance while remaining compatible with current WebRTC infrastructure.
Md. Mahir Ashhab, Hyojoon Kim
IMC1