AppNet: Application-Aware Networking with O-RAN
The 5G network promised transformative services across various industries, yet its integration has mostly been limited to existing 4G services like IMS-based multimedia and IoT. This paper identifies two key reasons for this underutilization: first, the stringent, multi-dimensional requirements of next-generation verticals like AR/VR, mobile gaming, and robotics, and the limitations of traditional Quality of Service (QoS) approaches in meeting these needs. We argue for a shift towards Quality of Experience (QoE), which better captures user perception and instantaneous application state. To meet stringent QoE demands and optimize network utilization, we emphasize the importance of application state and context awareness within the network. As a solution, we propose AppNet, a novel framework that integrates application awareness into the networking stack via RAN Intelligent Controllers (RICs) of the Open-RAN platform, enabling dynamic QoS adjustments based on application context. This paper highlights 5G private networks as an ideal testing ground, focusing on multi-user scenarios to deliver optimal real-time interactive services at scale.
Authors
- Srinivas Shakkottai (ORCID: https://orcid.org/0000-0002-5882-6433)
- Dinesh Bharadia (ORCID: https://orcid.org/0000-0002-3518-4722)
- Ish Kumar Jain (ORCID: https://orcid.org/0000-0002-6321-3797)
- Ushasi Ghosh (ORCID: https://orcid.org/0009-0002-0289-1938)
- Sushila Seshasayee
Institutions
- Texas A&M University – San Antonio (US)
- University of California San Diego (US)
Publication Details
- Published
- 2024-12-04
- DOI
- https://doi.org/10.1145/3636534.3697427
- Citations
- 1
- Primary Topic
- Image and Video Quality Assessment
- Type
- article
- Field-Weighted Citation Impact
- 0.25