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Record W2118412486 · doi:10.1109/p2p.2009.5284521

The impact of NAT on BitTorrent-like P2P systems

2009· article· en· W2118412486 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicPeer-to-Peer Network Technologies
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaCarnegie Mellon UniversityUniversity of Southern California
KeywordsBitTorrentNatNAT traversalComputer scienceNetwork address translationThe InternetComputer networkPeer-to-peerDistributed computingWorld Wide WebInternet Protocol

Abstract

fetched live from OpenAlex

BitTorrent nowadays is one of the most popular peer-to-peer (P2P) applications on the Internet; on the other hand, network address translation (NAT) has become pervasive in almost all networking scenarios. Despite the effort of NAT traversal, it is still very likely that P2P applications cannot receive incoming connection requests properly if they are behind NAT. Although this phenomenon has been widely observed, so far there is no quantitative study in the literature examining the impact of NAT on P2P applications. In this paper, we build analytical models to capture the performance of BitTorrent-like P2P systems with the presence of homogeneous and heterogeneous NAT peers. We further propose biased optimistic unchoke strategies in order to improve the overall system performance considerably. The analytical models have been validated by simulation results, which also reveal some interesting facts about the coexistence of NAT and public peers in P2P systems.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.637
Threshold uncertainty score0.334

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 communication0.0000.000
Open science0.0020.000
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 head0.014
GPT teacher head0.281
Teacher spread0.266 · 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

Citations27
Published2009
Admission routes2
Has abstractyes

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