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Record W2080203737 · doi:10.1109/pacrim.2009.5291287

Peer-to-peer file sharing over wireless mesh networks

2009· article· en· W2080203737 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
TopicPeer-to-Peer Network Technologies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsWireless mesh networkComputer scienceComputer networkFile sharingDistributed computingWireless networkPeer-to-peerMesh networkingOverlay networkWirelessOverlayOrder One Network ProtocolWireless WANShared meshThe InternetWi-Fi arrayWorld Wide WebOperating system

Abstract

fetched live from OpenAlex

Wireless mesh networks are being widely deployed around the world as a mean to provide low-cost access to the Internet. An orthogonal evolution in computer networking has been the rise of peer-to-peer communication. Structured peer-to-peer overlay networks have been used as platform for building large-scale distributed network applications such as file sharing. It is of interest to build those distributed application over wireless mesh networks. Unfortunately, conventional structured P2P overlays are not suitable for direct deployment in a mobile and wireless environment. We argue for a dual-layer mesh network architecture with support from wireless mesh routers for peer-to-peer applications. We demonstrate using extensive simulations that this approach has excellent potential to improve the performance of peer-to-peer applications in a wireless setting; specifically we focus on file sharing but other applications can also be supported by this approach.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.779
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0040.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.015
GPT teacher head0.254
Teacher spread0.239 · 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

Citations19
Published2009
Admission routes1
Has abstractyes

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