On Designing Self-Tuning Controllers for AQM Routers Supporting TCP Flows Based on Pole Placement
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper revisits the simple pole placement technique in the classical control theory, and exploits this technique to propose two kinds of controllers for active queue management (AQM) in Internet protocol (IP) routers: the self-tuning proportional controller based on pole placement (ST/spl I.bar/P/spl I.bar/PP) and the self-tuning proportional-plus-integral controller based on pole placement (ST/spl I.bar/PI/spl I.bar/PP). The damping ratio /spl xi/ and undamped natural frequency /spl omega//sub n/ can be appropriately chosen such that: 1) the transient response performance of the system is satisfied and 2) all the poles would lie in the left-half s-plane to guarantee the stability of the control system. The self-tuning controllers can assign proper intervals of /spl xi/ and /spl omega//sub n/ to achieve good AQM performance and thereby adapting the system to significant load changes very well. Furthermore, the ST/spl I.bar/PI/spl I.bar/PP controller can regulate the packet drop probability based on the knowledge of the instantaneous queue size, and clamp the steady value of the queue length to a specified reference value. We verify the effectiveness of these two controllers via OPNET simulation. Our simulation results show the following: 1) choosing appropriate /spl xi/ and /spl omega//sub n/ can successfully satisfy the transient response of the system and 2) when the network load changes, the ST/spl I.bar/P/spl I.bar/PP controller and the ST/spl I.bar/PI/spl I.bar/PP controller exhibit extremely short settling time.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it