Queuing Discipline Parameters for BBR-n+ and BBR-v3 Network Tests

A dataset containing parameters for queuing disciplines used in the evaluation of TCP congestion control algorithms. It was created by Muhammad Ahsan and published on figshare in April 2026. The data supports research comparing the performance of BBR-v3, BBR-n+, and TCP Cubic algorithms under various network conditions.

Use Cases

• Comparing throughput gains between BBR-n+ and BBR-v3 based on receiver window limitations described in the paper.
• Analyzing latency reductions for HTTP traffic under different congestion control algorithms as mentioned in the evaluation.
• Investigating fairness issues when BBR-n+ competes against Cubic flows with eight or more concurrent streams.
• Evaluating the impact of modern AQMs like CAKE and FQ_CoDel on algorithm performance as explored in the testing.

Strengths

• Data is associated with a specific research paper evaluating BBR-v3 and a proposed BBR-n+ algorithm.
• The dataset is small (5.5 KB), making it quick to download and inspect.
• It is published under a permissive CC-BY-4.0 license for reuse.

Limitations

• The dataset is extremely small (5.5 KB), indicating very limited scope and likely containing only summary parameters.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for statistical analysis.

Provenance

Source

Muhammad Ahsan via figshare.

Collection Method

Likely generated from network simulation or experimental testbed results described in the associated research paper.

Freshness

Last updated 2026-04-24 17:51:37; freshness should be verified.