Approximation of Generalized Processor Sharing with Interleaved Stratified Timer Wheels - Extended Version
Bibliographic record
Abstract
This paper presents Interleaved Stratified Timer Wheels as a novel priority queue data structure for traffic shaping and scheduling in packet-switched networks. The data structure is used to construct an efficient packet approximation of Gen eral Processor Sharing (GPS). This scheduler is the first of its ki nd by combining all desirable properties without any residual catch. In contrast to previous work, the scheduler presented here has constant and near-optimal delay and fairness properties, and can be implemented with O(1) algorithmic complexity, and has a low absolute execution overhead. The paper presents the priority queue data structure and the basic scheduling algorithm, along with several versions with different cost-performance trade-offs. A generalized analytical model for rate-controlled rounded times- tamp schedulers is developed and used to assess the scheduling properties of the different scheduler versions. Some illustrative simulation results are presented to reaffirm those properti es. Index Terms—Communication systems, Computer network performance, Packet scheduling, Data structures, Algorithms
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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".