The increasing usage of Real-Time Communication (RTC) applications for leisure and remote working calls for realistic and reproducible techniques to test them. They are used under very different network conditions: from high-speed broadband networks, to noisy wireless links. As such, it is of paramount importance to assess the impact of the network on users’ Quality of Experience (QoE), especially when it comes to the application’s mechanisms such as video quality adjustment or transmission of redundant data. In this work, we pose the basis for a system in which a target RTC application is tested in an emulated mobile environment. To this end, we leverage ERRANT, a data-driven emulator which includes 32 distinct profiles modeling mobile network performance in different conditions. As a use case, we opt for Cisco Webex, a popular RTC application. We show how variable network conditions impact the packet loss, and, in turn, trigger video quality adjustments, impairing the users’ QoE.

Realistic testing of RTC applications under mobile networks

Trevisan, Martino;
2020-01-01

Abstract

The increasing usage of Real-Time Communication (RTC) applications for leisure and remote working calls for realistic and reproducible techniques to test them. They are used under very different network conditions: from high-speed broadband networks, to noisy wireless links. As such, it is of paramount importance to assess the impact of the network on users’ Quality of Experience (QoE), especially when it comes to the application’s mechanisms such as video quality adjustment or transmission of redundant data. In this work, we pose the basis for a system in which a target RTC application is tested in an emulated mobile environment. To this end, we leverage ERRANT, a data-driven emulator which includes 32 distinct profiles modeling mobile network performance in different conditions. As a use case, we opt for Cisco Webex, a popular RTC application. We show how variable network conditions impact the packet loss, and, in turn, trigger video quality adjustments, impairing the users’ QoE.
2020
9781450379489
File in questo prodotto:
File Dimensione Formato  
3386367.3431661.pdf

Accesso chiuso

Licenza: Copyright dell'editore
Dimensione 1.14 MB
Formato Adobe PDF
1.14 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
3386367.3431661-Post_print.pdf

accesso aperto

Tipologia: Bozza finale post-referaggio (post-print)
Licenza: Digital Rights Management non definito
Dimensione 1.72 MB
Formato Adobe PDF
1.72 MB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/3025200
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact