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Record W1550834076

Capacity deficit and link loss in wlan to cellular vertical handoff

2008· dissertation· en· W1550834076 on OpenAlexaff
Seyed Vahid Azhari

Bibliographic record

VenueMacSphere (McMaster University) · 2008
Typedissertation
Languageen
FieldEngineering
TopicIPv6, Mobility, Handover, Networks, Security
Canadian institutionsMcMaster University
Fundersnot available
KeywordsHandoverComputer networkComputer scienceHandsetCellular networkBandwidth (computing)Network packetQuality of serviceBase stationNode (physics)WirelessEngineeringTelecommunications
DOInot available

Abstract

fetched live from OpenAlex

Mobile handset manufacturers have begun to include wireless LAN (WLAN) interfaces in their cellular handsets. This allows users to access WLAN networks when they are available and to revert to conventional cellular communications otherwise. In this way the handset can dynamically use the "best" available network, by switching connections between the two network interfaces. This switching is referred to as a vertical handoff (VHO). When handling real-time connections, handsets must be capable of performing a seamless vertical handoff. This occurs when the interface switching does not disrupt the quality of service requirements of the active connections. Vertical handoffs are generally time consuming, and this delay creates a difficult problem since WLAN coverage can be lost very abruptly. In this thesis, we propose and investigate several methods of mitigating this problem. A solution based on using a Vertical Handoff Support Node (VHSN) is proposed. When the WLAN link is lost, the VHSN is able to quickly redirect packets through the local cellular base-station during the time that handoff is taking place. This approach can eliminate VHO link loss. It is shown that the act of WLAN-to-cellular handoff can result in a severe bandwidth deficit problem on the WLAN. A novel bandwidth reservation and securing mechanism is proposed which overcomes this problem and performs significantly better than schemes based on modified versions of the static guard channel scheme used in cellular networks. The work is characterized by simulation and analytic models which investigate the key performance aspects of this type of system.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.755
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.009
GPT teacher head0.176
Teacher spread0.167 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations0
Published2008
Admission routes1
Has abstractyes

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