Skip to Main content Skip to Navigation
New interface
Conference papers

Cross-layer Loss Discrimination Algorithms for MEC in 4G networks

Abstract : Traditional loss-based Congestion Control Algorithms (CCAs) suffer from performance issues over wireless networks mostly due to their inability to distinguish wireless random losses from congestion losses. Different loss discrimination algorithms have been proposed to tackle this issue but they are not efficient for 4G networks since they do not consider the impact of various link layer mechanisms such as adaptive modulation and coding and retransmission techniques on congestion in LTE Radio Access Networks (RANs). We propose MELD (MEC-based Edge Loss Discrimination), a novel server-side loss discrimination mechanism that leverages recent advancements in Multi-access Edge Computing (MEC) services to discriminate packet losses based on real-time RAN statistics. Our approach collects the relevant radio information via MEC's Radio Network Information Service and uses it to correctly distinguish random losses from congestion losses. Our experimental study made with the QUIC transport protocol shows over 80% higher goodput when MELD is used with NewReno and 8% higher goodput when used with Cubic.
Document type :
Conference papers
Complete list of metadata
Contributor : Thierry Turletti Connect in order to contact the contributor
Submitted on : Monday, October 4, 2021 - 11:35:58 AM
Last modification on : Saturday, June 25, 2022 - 11:52:51 PM
Long-term archiving on: : Wednesday, January 5, 2022 - 6:24:49 PM


Files produced by the author(s)




Mamoutou Diarra, Walid Dabbous, Amine Ismail, Thierry Turletti. Cross-layer Loss Discrimination Algorithms for MEC in 4G networks. HPSR 2021 - IEEE International Conference on High Performance Switching and Routing, Jun 2021, Paris, France. ⟨10.1109/HPSR52026.2021.9481843⟩. ⟨hal-03363851⟩



Record views


Files downloads