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Record W2067933402 · doi:10.1109/glocom.2011.6133636

PSR: Proactive Source Routing in Mobile Ad Hoc Networks

2011· article· en· W2067933402 on OpenAlex
Zehua Wang, Cheng Li, Yuanzhu Chen

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 institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsComputer networkComputer scienceOptimized Link State Routing ProtocolDestination-Sequenced Distance Vector routingDynamic Source RoutingWireless Routing ProtocolLink-state routing protocolDistributed computingWireless ad hoc networkRouting protocolDSRFLOWAdaptive quality of service multi-hop routingAd hoc wireless distribution serviceRouting (electronic design automation)TelecommunicationsWireless

Abstract

fetched live from OpenAlex

Innovative routing in mobile ad hoc networks is crucial for unleashing the full potential of such networks. In this paper, we propose a new Proactive Source Routing (PSR) protocol that has a very small communication overhead but provides nodes with more network structure information than distance-vector based protocols. The value of the source routing protocol includes: 1) better control of path selection by the source nodes for congestion avoidance, load and energy consumption balancing, and bypassing untrusted areas, 2) alleviation of IP forwarding at intermediate nodes, and 3) support for opportunistic data forwarding. PSR complements DSR as a proactive counterpart to provide responsive data transportation services in heavily loaded networks. Our simulation results show that PSR achieves performance similar to OLSR and DSDV, but with only a small fraction of the communication overhead.

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)0.000
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: Methods · Consensus signal: none
Teacher disagreement score0.974
Threshold uncertainty score0.676

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 communication0.0000.001
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 head0.019
GPT teacher head0.222
Teacher spread0.203 · 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

Citations30
Published2011
Admission routes1
Has abstractyes

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