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Record W2097531318 · doi:10.1109/ccnc08.2007.92

Prototypes of Opportunistic Wireless Mesh Networks Supporting Real-Time Services

2008· article· en· W2097531318 on OpenAlexaff
Liang Song, Dimitrios Hatzinakos

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicOpportunistic and Delay-Tolerant Networks
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsWireless mesh networkComputer networkComputer scienceMunicipal wireless networkOrder One Network ProtocolService setMesh networkingWireless networkBroadbandWireless broadbandWirelessSoftware deploymentWireless WANReuseBroadband networksTelecommunicationsWi-Fi arrayEngineering

Abstract

fetched live from OpenAlex

Wireless mesh networks can provide for attractive solutions to telecommunication services, where cost-effective broadband access can be realized, by means of frequency reuse and lower engineering cost in installing. A novel network architecture of opportunistic mesh networks is presented here, based upon the cognitive networking concept which opportunistically utilizes the network resources including both spectrum bandwidth and mesh station availability. The proof-of-concept prototypes are developed to show: (1) the supportance of real-time traffic over multiple wireless hops by the opportunistic resource utilization; (2) the drop-and-play networking model which can vastly save the network planning/deployment costs.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.996
Threshold uncertainty score0.897

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 head0.018
GPT teacher head0.241
Teacher spread0.222 · 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
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

Citations2
Published2008
Admission routes1
Has abstractyes

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