Advancements in Network Performance and Reliability

The field of network research is moving towards improving performance and reliability through innovative solutions. Recent developments focus on enhancing traffic engineering, congestion control, and path selection strategies. Notably, researchers are exploring the potential of multipath transport protocols and path-aware networks to optimize network stability and efficiency. Furthermore, there is a growing interest in designing practical and deployable systems that can leverage radio KPI measurements and machine learning techniques to improve network performance. The development of new analytical frameworks and simulation tools is also facilitating the evaluation and optimization of network protocols and architectures. Overall, the field is advancing towards more robust, efficient, and adaptive network systems. Noteworthy papers include: ReWeave, which presents a scalable and efficient link-level traffic engineering scheme, and BISCAY, which proposes a practical radio KPI-driven congestion control system for mobile networks.

Sources

ReWeave: Traffic Engineering with Robust Path Weaving for Localized Link Failure Recover

Modeling and Analysis of Coexistence Between MLO NSTR-based Wi-Fi 7 and Legacy Wi-Fi

A QoS Framework for Service Provision in Multi-Infrastructure-Sharing Networks

Improving Nonpreemptive Multiserver Job Scheduling with Quickswap

Impact of Passive Element Technological Limits on CMOS Low-Noise Amplifier Design

2.4-GHz Integrated CMOS Low-Noise Amplifier (English Version)

BISCAY: Practical Radio KPI Driven Congestion Control for Mobile Networks

Performance Evaluation of LoRa for IoT Applications in Non-Terrestrial Networks via ns-3

Path Dynamics in a Deployed Path-Aware Network: A Measurement Study of SCIONLab

An Axiomatic Analysis of Path Selection Strategies for Multipath Transport in Path-Aware Networks

Understanding BBRv3 Performance in AQM-Enabled WiFi Networks

The Landscape of Fairness: An Axiomatic and Predictive Framework for Network QoE Sensitivity

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