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Record W2100252439 · doi:10.1109/mascot.2001.948858

Performance study of a multipath routing method for wireless mobile ad hoc networks

2002· article· en· W2100252439 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
TopicMobile Ad Hoc Networks
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsComputer scienceComputer networkMultipath routingOptimized Link State Routing ProtocolDistributed computingMobile ad hoc networkWireless ad hoc networkDestination-Sequenced Distance Vector routingDynamic Source RoutingWireless Routing ProtocolVehicular ad hoc networkRouting protocolRouting (electronic design automation)WirelessTelecommunicationsNetwork packet

Abstract

fetched live from OpenAlex

A Mobile Ad hoc NETwork (MANET) is a collection of wireless mobile computers forming a temporary network without any existing wire line infrastructure. Due to the dynamic nature of the network topology and the resource constraints, routing in MANETs is a challenging task. Multipath routing can increase end-to-end throughput and provide load balancing in wired networks. However, its advantage is not obvious in MANETs because the traffic along the multiple paths may interfere with each other . In addition, without accurate knowledge of topology, finding multiple disjoint paths is difficult. We propose an on-demand method to efficiently search for multiple node-disjoint paths and present the criteria for selecting the multiple paths. We also perform a simulation study on the proposed method. The purpose of this paper is to present the advantages as well as some difficulties of deploying multipath routing in MANETs.

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 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 score0.886
Threshold uncertainty score0.729

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 head0.025
GPT teacher head0.274
Teacher spread0.249 · 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

Citations112
Published2002
Admission routes1
Has abstractyes

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