Caliper: Precise and Responsive Traffic Generator
Bibliographic record
Abstract
This paper presents Caliper, a highly-accurate packet injection tool that generates precise and responsive traffic. Caliper takes live packets generated on a host computer and transmits them onto a gigabit Ethernet network with precise inter-transmission times. Existing software traffic generators rely on generic Network Interface Cards which, as we demonstrate, do not provide high-precision timing guarantees. Hence, performing valid and convincing experiments becomes difficult or impossible in the context of time-sensitive network experiments. Our evaluations show that Caliper is able to reproduce packet inter-transmission times from a given arbitrary distribution while capturing the closed-loop feedback of TCP sources. Specifically, we demonstrate that Caliper provides three orders of magnitude better precision compared to commodity NIC: with requested traffic rates up to the line rate, Caliper incurs an error of 8 ns or less in packet transmission times. Furthermore, we explore Caliper's ability to integrate with existing network simulators to project simulated traffic characteristics into a real network environment. Caliper is freely available online.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".