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Record W2114605240 · doi:10.1109/ccece.2005.1557226

A hybrid approach to reliability estimation of mobile agent-based systems

2006· article· en· W2114605240 on OpenAlex
Mosaab Daoud, Qusay H. Mahmoud

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
FieldComputer Science
TopicMobile Agent-Based Network Management
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceReliability (semiconductor)Node (physics)ThroughputComponent (thermodynamics)Stochastic Petri netPetri netDistributed computingMobile agentReliability engineeringTransmission (telecommunications)EngineeringWireless

Abstract

fetched live from OpenAlex

In this paper we analytically analyze the reliability of mobile agent-based systems. We define the reliability of a mobile agent in terms of the processor execution time required to perform agent's tasks at each processing node and the transmission (communication) time needed to transfer the agent from one processing node to another via a network to complete the mission. The failure of entire components causes failure of the agent. Simulation experiments have been conducted using stochastic Petri Nets modeling. We investigate the effect of different component reliability and availability models (processors and links) on the system throughput. The results we have obtained demonstrate the impact of different reliability and availability models on the system throughput

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)0.001
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 score0.777
Threshold uncertainty score0.613

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.010
GPT teacher head0.217
Teacher spread0.207 · 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

Citations1
Published2006
Admission routes2
Has abstractyes

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