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Record W2107855621 · doi:10.1109/dnsr.2004.1344748

Provision of QoS in wireless networks

2004· article· en· W2107855621 on OpenAlexaff
Jasjote Grewal, John DeDourek

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicNetwork Traffic and Congestion Control
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsComputer networkComputer scienceRoamingQuality of serviceWireless networkWi-Fi arrayWireless WANMobile QoSBluetoothWireless Application ProtocolHeterogeneous networkWirelessTelecommunicationsService (business)Service provider

Abstract

fetched live from OpenAlex

With the advent of different types of wireless technologies a 'vertical multi-tier' architecture is envisioned to provide the wireless user with seamless 'roaming' across different types of networks. Wireless devices will be used not only for transferring data but also for voice and multimedia applications for which QoS (quality of service) support is essential. Different wireless technologies, like Bluetooth, IEEE 802.11 standards and 1x cellular standards, can be integrated at the network layer with the help of the IETF Mobile IP standard. Although there are existing QoS mechanisms, like DiffServ and IntServ, they are not directly applicable to wireless networks. Because of the inherent issues with TCP in wireless environments, it is proposed that RTP (real time protocol) over UDP (user datagram protocol) be used for designing the QoS framework for wireless computing. Open source applications that use RTP over UDP are being used for measuring the network characteristics for multimedia flows. The paper describes the approach being taken in order to provide a QoS solution for wireless networks.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0050.004
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.005
GPT teacher head0.197
Teacher spread0.193 · 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 designTheoretical or conceptual
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

Citations8
Published2004
Admission routes1
Has abstractyes

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