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Record W2600811548

M2ANET Simulation in 3D in NS2

2014· article· en· W2600811548 on OpenAlexaff
Nasir Mahmood, John DeDourek, Przemyslaw Pocheć

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicMobile Ad Hoc Networks
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsComputer science
DOInot available

Abstract

fetched live from OpenAlex

Abstract — In this paper, the enhancements to the ns2 source code adding a capability for modeling Mobile Ad Hoc Network (MANETs) and Mobile Medium Ad Hoc Network (M2ANETs) in three dimensions are described. ns2 is an open-source event-driven simulator designed specifically for research in computer communication networks. It allows modeling MANETs in two dimensions which imposes limits on investigating the MANET performance in the real world. Experiments were conducted using the modified ns2 simulator to determine the performance of M2ANETs in 3D, at different node densities and with different movement patterns. The results show that mobile nodes using 802.11 links and running DSR routing protocol can successfully operate as a mobile medium (M2ANET) in a 3D cube with dimensions less than 1500x1500x1500 meters. Simulation experiments also show that deploying of a 3D M2ANET in a multi-story building is not negatively affected by limiting the mobile node movement to horizontal planes corresponding to different floors in the building. Keywords-mobile network; simulation; NS2; 3D; MANET;

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)0.002
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.241
Teacher spread0.231 · 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

Citations5
Published2014
Admission routes1
Has abstractyes

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