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Record W2167320146 · doi:10.1109/glocom.2007.116

EM2NET: An Energy-Saving Explicit Multicast Protocol for MANETs

2007· preprint· en· W2167320146 on OpenAlexaff
Abderrahim Benslimane, Abdelhakim Hafid

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldComputer Science
TopicMobile Ad Hoc Networks
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsProtocol Independent MulticastMulticastXcastDistance Vector Multicast Routing ProtocolSource-specific multicastComputer networkComputer sciencePragmatic General MulticastIP multicastDistributed computingReliable multicastInter-domainHeader

Abstract

fetched live from OpenAlex

In this paper, we propose a new explicit multicast protocol for MANET, called EM2NET. The objective of EM2NET is to efficiently support large number of small multicast groups in MANETs. EM2NET strikes a nice balance between the characteristics of explicit multicast protocols (e.g., Xcast and E2M) and these of tree/mesh-based multicast protocols (e.g., ODMRP and MAODV). Indeed, it combines the encoding of destinations addresses in the packet header and the maintenance of multicast state information in carefully selected nodes. Simulations show that EM2NET outperforms (a) explicit multicast protocols and (b) tree/mesh based protocols in the case of small size multicast groups.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.058
GPT teacher head0.351
Teacher spread0.293 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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

Citations4
Published2007
Admission routes1
Has abstractyes

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