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Record W2135551431 · doi:10.1109/mcom.2009.4785381

Network-based mobility management in the evolved 3GPP core network

2009· article· en· W2135551431 on OpenAlexaff
Irfan Ali, Alessio Casati, Kuntal Chowdhury, Katsutoshi Nishida, Eric W. Parsons, Stefan Schmid, Rahul Vaidya

Bibliographic record

VenueIEEE Communications Magazine · 2009
Typearticle
Languageen
FieldEngineering
TopicIPv6, Mobility, Handover, Networks, Security
Canadian institutionsNortel (Canada)
Fundersnot available
KeywordsComputer networkComputer scienceUMTS Terrestrial Radio Access NetworkMobility managementCore networkRadio access networkQuality of serviceDigital subscriber lineAccess networkGPRS core networkProxy Mobile IPv6Network packetWiMAXTelecommunicationsMobile IPWirelessGeneral Packet Radio ServiceMobile stationBase station

Abstract

fetched live from OpenAlex

A key aspect of the 3GPP system architecture evolution is the specification of an evolved packet core that supports multiple access networks. The EPC enables operators to deploy and operate one common packet core network for 3GPP radio accesses (E-UTRAN, UTRAN, and GERAN), as well as other wireless and wireline access networks (e.g., eHRPD, WLAN, WIMAX, and DSL/Cable), providing the operator with a common set of services and capabilities across the networks. A key requirement of the EPC is to provide seamless mobility at the IP layer as the user moves within and between accesses. This article provides an overview of the EPC specifications that use a network-based mobility mechanism based on Proxy Mobile IPv6 to enable mobility between access networks. An important facet of providing seamless mobility for a user's sessions across technologies is to ensure that quality of service is maintained as the user moves between accesses. An overview of the "off-path" QoS model to supplement PMIPv6 is also provided.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.034
GPT teacher head0.270
Teacher spread0.236 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations54
Published2009
Admission routes1
Has abstractyes

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