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Record W2140102073 · doi:10.1109/icc.2011.5963029

Design of a PI Rate Controller for Mitigating SIP Overload

2011· article· en· W2140102073 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicIPv6, Mobility, Handover, Networks, Security
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRetransmissionComputer scienceComputer networkQueueing theoryServerQueuing delayController (irrigation)Upstream (networking)Real-time computingNetwork packet

Abstract

fetched live from OpenAlex

Recent collapses of SIP servers in the real carrier networks indicate that the built-in SIP overload control mechanism cannot mitigate overload effectively. In this paper, we investigate the root cause of SIP server crash by studying the impact of the retransmission on the queuing delay of the overloaded server. The transient overload may introduce the excessive queuing delay, thus triggering unnecessary retransmissions to exacerbate the overload. Therefore, we adopt a control-theoretic approach that models the overloaded downstream server and its upstream server as a feedback control system. Then we design a PI rate controller to restrict the retransmission rate based on the queuing delay. We derive the guidelines for choosing PI controller gains to ensure the system stability. Our OPNET simulation results demonstrate that our proposed control theoretic approach can mitigate the SIP overload effectively, thus preventing the SIP network collapse.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.882
Threshold uncertainty score0.642

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.032
GPT teacher head0.213
Teacher spread0.181 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it