QoE-DASH: DASH QoE Performance Evaluation Tool for Edge-Cache and Recommendation

The converging ecosystem provided by Multi-access Edge Computing (MEC) has motivated novel DASH video streaming provisioning scenarios involving the joint coordination of different mechanisms for caching, communication and control. Given the complexity of designing such mechanisms, it is important t...

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Bibliographic Details
Main Authors: Esper, Joao Paulo, Claudia Bastos Loureiro Moncao, Ana, Chaves Rodrigues, Karlla B., Bonato Both, Cristiano, Correa, Sand Luz, Vieira Cardoso, Kleber
Format: Conference Proceeding
Language:English
Subjects:
Conferences
DASH
Ecosystems
Emulation
MEC
Multi-access edge computing
network emulation
Performance evaluation
Programming
QoE
Streaming media
streaming service
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Summary:The converging ecosystem provided by Multi-access Edge Computing (MEC) has motivated novel DASH video streaming provisioning scenarios involving the joint coordination of different mechanisms for caching, communication and control. Given the complexity of designing such mechanisms, it is important to provide the research community with open-source tools that support the assessment of their feasibility, specially in real-world environment. Current network emulators still require a significant programming effort to meeting this need. To fill this gap, a new DASH emulator called QoE-DASH is presented in this work. QoE-DASH builds upon goDASH to evaluate the QoE of users consuming DASH content, taking into account network properties, user preferences, and context information. To demonstrate the capabilities of QoE-DASH, we exercise different functionalities of our tool and present a case study where two joint caching and recommendation models, proposed in the literature, are evaluated and their effects on user QoE are depicted using state-of-the-art QoE metrics.
ISSN:1938-1883
DOI:10.1109/ICC45855.2022.9839234