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Record W2170311083 · doi:10.1109/icc.2008.616

Call Admission Control for Mobile Agent Based Handoff in Wireless Mesh Networks

2008· article· en· W2170311083 on OpenAlexaff
Bo Rong, Yao Qian, Kejie Lu, Michel Kadoch

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicMobile Ad Hoc Networks
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsHandoverComputer networkComputer scienceWireless mesh networkRouterShared meshQuality of serviceSwitched meshCall Admission ControlBandwidth (computing)Mobility managementWireless networkAdmission controlWirelessTelecommunications

Abstract

fetched live from OpenAlex

In wireless mesh network (WMN), it is important to provide an efficient handoff scheme, due to the frequent user mobility. To address this issue, we propose a mobile agent (MA) based handoff approach, where each mesh client has a MA residing on its registered mesh router. To guarantee quality of service (QoS) and achieve differentiated priorities during the handoff, we develop a proportional threshold structured optimal effective bandwidth policy for call admission control (CAC) on the mesh router. Simulation study shows that our proposed CAC scheme can obtain satisfying tradeoff between differentiated priorities and statistical effective bandwidth in WMN handoff environment.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.969
Threshold uncertainty score0.702

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
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 head0.014
GPT teacher head0.238
Teacher spread0.224 · 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.

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

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

Citations9
Published2008
Admission routes1
Has abstractyes

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