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Record W1595947196 · doi:10.1109/vetecs.2006.1682764

Minimum Energy Cooperative Path Routing in Wireless Networks: An Integer Programming Formulation

2006· article· en· W1595947196 on OpenAlexaff
Fulu Li, Andrew Lippman, Kui Wu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicMobile Ad Hoc Networks
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsInteger programmingComputer scienceRouting (electronic design automation)Mathematical optimizationHeuristicPath (computing)Wireless networkStatic routingWirelessComputer networkGeographic routingRouting protocolDistributed computingMathematicsTelecommunications

Abstract

fetched live from OpenAlex

We study the problem of minimum energy cooperative path (MECP) routing in wireless networks. The joint problem of cooperative routing in wireless networks that combines route selection and the transmit diversity was recently presented in A. Khandani et al. (2003). Several heuristic algorithms were also proposed in A. Khandani et al. (2003) to approximate the minimum energy cooperative path, while it has not been possible to judge the quality of the solutions with respect to the optimal. In this paper, we present an integer programming formulation of the MECP problem towards an optimal solution for a network where the locations of the nodes are known a priori and fixed

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 score0.932
Threshold uncertainty score0.660

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 communication0.0000.001
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 head0.009
GPT teacher head0.226
Teacher spread0.218 · 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

Citations15
Published2006
Admission routes1
Has abstractyes

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