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Record W2789883480 · doi:10.23977/cpcs.2017.21002

Research on Hierarchical Scheduling of Operational Operation of Polar Meteorological Satellite Ground System

2017· article· en· W2789883480 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueComputing Performance and Communication systems · 2017
Typearticle
Languageen
FieldComputer Science
TopicDistributed and Parallel Computing Systems
Canadian institutionsnot available
Fundersnot available
KeywordsDynamic priority schedulingComputer scienceFair-share schedulingTwo-level schedulingFixed-priority pre-emptive schedulingRate-monotonic schedulingEarliest deadline first schedulingScheduling (production processes)Round-robin schedulingFlow shop schedulingLottery schedulingReal-time computingDistributed computingEngineeringScheduleOperating systemOperations management

Abstract

fetched live from OpenAlex

Meteorological satellite ground application system business operation scheduling is the core of the entire business operation, directly related to the entire system operating efficiency. This paper designs a hierarchical satellite terrestrial system business operation scheduling method. First of all, the satellite service is classified into first-level and second-level scheduling. Then, based on the hierarchical scheduling, task scheduling and scheduled scheduling are implemented. Through hierarchical scheduling and planning and scheduling to achieve the entire system job scheduling, thereby enhancing the efficiency of task scheduling and improve the overall system operating efficiency.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.843
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0010.000
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 head0.093
GPT teacher head0.350
Teacher spread0.257 · 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