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Record W2022963857 · doi:10.1109/bsc.2010.5472947

Reliable Fault-Tolerant Multipath routing protocol for wireless sensor networks

2010· article· en· W2022963857 on OpenAlexaff
Hind Alwan, Anjali Agarwal

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicEnergy Efficient Wireless Sensor Networks
Canadian institutionsConcordia University
Fundersnot available
KeywordsComputer scienceComputer networkMultipath routingZone Routing ProtocolRouting protocolDynamic Source RoutingWireless Routing ProtocolLink-state routing protocolDistributed computingSource routingErasure codeWireless sensor networkNetwork packetDecoding methodsTelecommunications

Abstract

fetched live from OpenAlex

Several routing protocols have been designed in the recent years to support different wireless sensor networks requirements. In this paper, we introduce a new on demand routing protocol, Reliable Fault-Tolerant Multipath (RFTM), to improve the reliability of data routing in wireless sensor networks. RFTM is a multi objective routing protocol that meets diverse application requirements by considering the changing conditions of the network. The protocol takes into account both reliability demand and link quality to determine the number of desired multiple disjoint paths between the sink and source nodes. With the advantage of data splitting method based on erasure coding the packets are encoded at source nodes and the sink node obtains the data by decoding. Moreover, the sink node can make intelligent decisions based on the node's available resources, hop count to the source and delay to lengthen the network lifetime, provides fault-tolerance and achieves the desired reliability that meets the network state and the different application requirements.

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.

How this classification was reachedexpand

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: Methods · Consensus signal: Methods
Teacher disagreement score0.426
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 integrity0.0000.001
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 head0.016
GPT teacher head0.273
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations14
Published2010
Admission routes1
Has abstractyes

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