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Record W2119783159 · doi:10.1109/lcomm.2009.090121

On the impact of mobility and soft vertical handoff on voice admission control in loosely coupled 3G/WLAN networks

2009· article· en· W2119783159 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.

Bibliographic record

VenueIEEE Communications Letters · 2009
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsComputer scienceComputer networkHandoverQuality of serviceCall Admission ControlCall blockingNetwork packetPacket lossWireless networkWirelessTelecommunications

Abstract

fetched live from OpenAlex

Loose coupling between 3G and WLAN ensures flexibility and openness. However, providing an ubiquitous mobile voice service in a loosely coupled 3G/WLAN network requires both packet-level and call-level quality of service (QoS) guarantees using soft vertical handoff (SVHO) and call admission control (CAC). In this paper, we evaluate the impact of both SVHO and WLAN mobility on call blocking and dropping probabilities rederived for the integrated network. For this purpose, we propose a new multi-region mobility model that accurately estimate these probabilities under a resource-efficient dynamic threshold SVHO compared to a standard static-threshold SVHO. Results show us that the resource-efficient SVHO blocks and drops much less voice calls than the static one when very low mean and high variability of multi-mode mobile station velocities are noticed. Therefore, resource-efficient SVHO implementations are highly recommended in these mobility environments.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.232
Threshold uncertainty score0.640

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0030.000
Research integrity0.0000.001
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 head0.031
GPT teacher head0.319
Teacher spread0.288 · 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