Portable and Performant Userspace SCTP Stack
Bibliographic record
Abstract
One of only two new transport protocols introduced in the last 30 years is the Stream Control Transmission Protocol (SCTP). SCTP enables capabilities like additional throughput and fault tolerance for multihomed hosts. An SCTP implementation is included with the Linux kernel and another implementation called sctplib functions successfully in userspace on several platforms but unfortunately neither of these implementations have all of the latest features nor do they perform as well as the FreeBSD kernel implementation of SCTP. We were motivated to produce a portable implementation of the FreeBSD kernel SCTP stack that operates in userspace of any system because of both our desires to obtain a higher performance SCTP stack for Linux as well as to exploit recent developments in hardware virtualization and transport protocol onloading. Unlike any other userspace transport implementation for TCP or SCTP, our userspace SCTP stack simultaneously achieves similar throughput and latency as the Linux kernel TCP stack, without compromising on any of the transport's features as well as maintaining true portability across multiple operating systems and devices. We create a callback API and implement a threshold to control its usage; our userspace SCTP stack with these optimizations obtains higher throughput than the Linux kernel implementation of SCTP. We describe our userspace SCTP stack's design and demonstrate how it gives similar throughput and latency on Linux as the kernel TCP implementation, with the benefits of the new features of SCTP.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".