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Record W2602655753 · doi:10.1109/vtcfall.2016.7880960

Disaster Management and Response for Modern Cellular Networks Using Flow-Based Multi-Hop Device-to-Device Communications

2016· article· en· W2602655753 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced MIMO Systems Optimization
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceComputer networkWirelessBase stationRouting (electronic design automation)ThroughputCellular networkRouting protocolWireless broadbandAnt colony optimization algorithmsWireless networkTelecommunications

Abstract

fetched live from OpenAlex

Modern wireless broadband networks are crucial for different mission-critical applications and public safety agencies. Various natural disasters and physical attacks would result in the malfunction or failure of wireless and cellular infrastructures. This subsequently affects the correct functioning of the dependent mission- critical applications. Thus, disaster management and response is of great importance. In this paper, we focus on disaster response using D2D communications to extend the coverage of base stations, and on controller-assisted routing to maximize the total end-to-end throughput for all of the current flows from the area without network coverage using the ant colony optimization. The proposed routing scheme outperforms the schemes based on the shortest path routing in terms of the total throughput as well as fairness in allocating the rates to the flows.

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 score0.513
Threshold uncertainty score0.502

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 science0.0000.000
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 head0.038
GPT teacher head0.273
Teacher spread0.235 · 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

Citations22
Published2016
Admission routes2
Has abstractyes

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