Mitigating SIP Overload Using a Control-Theoretic Approach
Bibliographic record
Abstract
Retransmission mechanism helps SIP maintain its reliability, but it can also make an overload worse. Recent server collapses due to emergency-induced call volume in carrier networks indicate that the built-in overload control mechanism cannot handle overload conditions effectively. Since the retransmissions caused by the overload are redundant, we suggest mitigating the overload by controlling redundant message ratio to an acceptable level. Using control-theoretic approach, we model the interaction of an overloaded downstream server with its upstream server as a feedback control system. Then we develop an adaptive PI control algorithm to mitigate the overload at the downstream server by controlling the retransmission message rate of its upstream servers. By performing OPNET simulations on two typical overload scenarios, we demonstrate that: (1) without overload control algorithm applied, the overload at the downstream server may propagate to its upstream servers; (2) our control-theoretic solution not only mitigate the overload effectively, but also achieve a satisfactory target redundant message ratio.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".