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Record W2110164062 · doi:10.1109/sensorcomm.2009.62

A Survey on Fault Tolerant Routing Techniques in Wireless Sensor Networks

2009· article· en· W2110164062 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicEnergy Efficient Wireless Sensor Networks
Canadian institutionsConcordia University
Fundersnot available
KeywordsComputer scienceRouting protocolComputer networkDynamic Source RoutingWireless Routing ProtocolMultipath routingLink-state routing protocolGeographic routingStatic routingWireless sensor networkFault tolerancePolicy-based routingDistributed computingRouting (electronic design automation)Zone Routing Protocol

Abstract

fetched live from OpenAlex

Wireless sensor networks are without a doubt one of the central issues in current research topics due to the harsh environmental conditions in which such networks can be deployed and their unique sensor network characteristics,specifically limited power supply, sensing, processing and communication capabilities. Presented with many challenges and design issues that affect the data routing, a need for a fault tolerant routing protocol becomes essential. In this paper, we summarize and highlight the key ideas of existing fault tolerant techniques of routing protocols, survey existing routing protocols proposed to support fault tolerance. Finally, we provide some future research directions in the area of fault tolerance in wireless sensor networks routing.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.770
Threshold uncertainty score1.000

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 head0.016
GPT teacher head0.248
Teacher spread0.232 · 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

Citations101
Published2009
Admission routes1
Has abstractyes

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