Modelling the Performance of High Capacity Access Networks for the Benefit of End-Users and Public Policies
May 31, 2023 Β· Declared Dead Β· π International Conference on High Performance Switching and Routing
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Antonio Capone, Maurizio Decina, Aldo Milan, Marco Petracca
arXiv ID
2305.20035
Category
cs.NI: Networking & Internet
Citations
1
Venue
International Conference on High Performance Switching and Routing
Last Checked
4 months ago
Abstract
This paper deals with the challenge of modeling the performance of planned ultrabroadband access networks while maintaining technological neutrality and accuracy in measurable quality. We highlight the importance of such modeling also for addressing public funding policies compared to models mainly based on the maximum nominal speed of the access networks, taking also into account the widespread use of measurement tools like "speed test" that have influenced the perceived quality by end-users. We present a performance modelling approach based on the extension of well-known traffic models that accurately characterizes the performance of broadband access networks. We also show how the presented model has been validated with data from two network operators and has been applied to address the recent Italian public interventions for the development of ultrabroadband access networks in market failure areas.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Networking & Internet
R.I.P.
π»
Ghosted
π
π
The Cartographer
Federated Learning in Mobile Edge Networks: A Comprehensive Survey
π
π
The Cartographer
A Survey of Indoor Localization Systems and Technologies
R.I.P.
π»
Ghosted
Survey of Important Issues in UAV Communication Networks
π
π
The Cartographer
Network Function Virtualization: State-of-the-art and Research Challenges
π
π
The Cartographer
Applications of Deep Reinforcement Learning in Communications and Networking: A Survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted