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Record W2119053557 · doi:10.1109/iros.2004.1389655

A two-hop energy-efficient mesh protocol for wireless sensor networks

2005· article· en· W2119053557 on OpenAlexaff
Yimin Liu, Peter Liu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicEnergy Efficient Wireless Sensor Networks
Canadian institutionsCarleton University
Fundersnot available
KeywordsComputer scienceOrder One Network ProtocolWireless mesh networkWireless sensor networkComputer networkEfficient energy useShared meshRouting protocolSwitched meshMesh networkingEnergy consumptionHazy Sighted Link State Routing ProtocolHop (telecommunications)Key distribution in wireless sensor networksDistributed computingWireless Routing ProtocolWirelessWireless networkRouting (electronic design automation)EngineeringTelecommunications

Abstract

fetched live from OpenAlex

Wireless sensor networks are finding applications in many areas such as coordinated target detection, environment monitoring and border surveillance. The strict requirement on energy efficiency is one of the most significant challenges. In this paper, we develop a novel energy-efficient routing protocol called THEEM (two-hop energy-efficient mesh) for wireless sensor networks. The THEEM protocol employs a two-hop scheme for in-mesh data transmission. A centralized mesh (cluster) formation method is adopted along with other design innovations, such as the concepts of mesh layer/column, power-aware mesh head assignment and a low-energy media access protocol, to achieve energy efficiency. Simulation results show that the THEEM protocol reduces energy consumption quite significantly compared to other similar protocols under the same condition.

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)0.000
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 score0.546
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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.272
Teacher spread0.256 · 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

Citations3
Published2005
Admission routes1
Has abstractyes

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