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Record W1971586190 · doi:10.1016/j.procs.2013.09.008

An Optimal Energy Efficient and Minimum Delay Scheduling for Periodic WSN Applications

2013· article· en· W1971586190 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.

Bibliographic record

VenueProcedia Computer Science · 2013
Typearticle
Languageen
FieldComputer Science
TopicEnergy Efficient Wireless Sensor Networks
Canadian institutionsAcadia University
Fundersnot available
KeywordsComputer scienceScheduling (production processes)Mathematical optimizationDistributed computingComputer networkReal-time computing

Abstract

fetched live from OpenAlex

Wireless Sensor Network (WSN) enables pervasive, ubiquitous, and seamless communication with the physical world. This paper investigates an optimal cross-layer joint routing and scheduling problem for WSN with periodic data collection. The problem is formulated as an Integer Linear Program (ILP) model such that a joint scheduling and routing is developed to maximize network lifetime and minimize delay. In this paper, an ILP model with multi objective cost function is proposed. The proposed ILP model represents the operation of Energy-Efficient Distributed Schedule-Based (EEDS) protocol. The ILP model is solved for different network configurations. The optimal solutions assuming different objectives are compared.

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 categoriesMeta-epidemiology (narrow), Scholarly communication
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 score0.367
Threshold uncertainty score1.000

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 studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
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 head0.007
GPT teacher head0.226
Teacher spread0.219 · 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