MétaCan
Menu
Back to cohort
Record W2159152015 · doi:10.1287/ijoc.1110.0463

A Branch-and-Cut Approach for the Minimum-Energy Broadcasting Problem in Wireless Networks

2011· article· en· W2159152015 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

VenueINFORMS journal on computing · 2011
Typearticle
Languageen
FieldComputer Science
TopicMobile Ad Hoc Networks
Canadian institutionsUniversity of Windsor
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsBroadcasting (networking)Node (physics)Wireless sensor networkComputer scienceTree (set theory)WirelessEnergy consumptionWireless networkBranch and cutMathematical optimizationEnergy (signal processing)Exponential functionComputer networkMathematicsAlgorithmInteger programmingTelecommunications

Abstract

fetched live from OpenAlex

This paper studies the minimum-energy broadcasting problem (MEBP) in wireless sensor networks. The aim of the MEBP is to determine the power assignment of each node in a wireless sensor network such that a specified source node can broadcast messages to each of the other nodes and the total energy consumption is minimized. We first present a new formulation involving an exponential number of constraints for the broadcasting requirement. We then prove that under a mild condition, these constraints for the broadcasting requirement are facet defining. Directly using the proposed formulation, we further present a new branch-and-cut (B&C) solution approach to optimally solve the MEBP. We propose three ways to identify violated cuts at each node in the enumeration tree. Finally, we test the proposed B&C approach on 1,000 randomly generated instances with different properties and compare it with other alternative methods in the literature. Computational results demonstrate the effectiveness and efficiency of our approach using the proposed formulation for instances with up to 100 nodes.

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)0.002
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: Methods · Consensus signal: none
Teacher disagreement score0.907
Threshold uncertainty score0.684

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.027
GPT teacher head0.230
Teacher spread0.203 · 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