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Record W2097097299 · doi:10.1109/wcnc.2007.568

Multi-Class Resource Management in a Cellular/WLAN Integrated Network

2007· article· en· W2097097299 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Network Optimization
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer scienceComputer networkCellular networkResource management (computing)Resource allocationOverhead (engineering)Distributed computingScheme (mathematics)Local area networkWireless networkRadio resource managementWirelessTelecommunicationsOperating system

Abstract

fetched live from OpenAlex

Resource management is an important aspect for the integrated system of cellular networks and wireless local area networks (WLANs). This study proposed a resource management scheme for the cellular/WLAN integrated network to support multiple service classes, namely, the conversational, streaming, and interactive classes. Resource sharing based on virtual partitioning is employed in the cellular network to overcome the limitation of contention-based WLANs in multi-class support. Further, a dynamic load balancing policy is proposed to distribute the traffic load to the integrated cell and WLAN based on factors such as service class and system utilization. The dedicated resource allocation of the cellular network is exploited to avoid the large overhead paid for WLANs to support realtime conversational and streaming classes. The elastic interactive traffic is manipulated flexibly to minimize the bursty overflow traffic and balance the utilization of both systems. The overall performance of the integrated network is significantly improved by the proposed resource management scheme.

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)0.000
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 score0.812
Threshold uncertainty score0.607

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.007
GPT teacher head0.207
Teacher spread0.200 · 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

Quick stats

Citations21
Published2007
Admission routes1
Has abstractyes

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