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Record W2082607696 · doi:10.1504/ijista.2007.014263

Adaptive peer-to-peer streaming over hybrid wireless networks

2007· article· en· W2082607696 on OpenAlexaff
Yifeng He, Brad Stimpson, Ivan Lee, Xijia Gu, Ling Guan

Bibliographic record

VenueInternational Journal of Intelligent Systems Technologies and Applications · 2007
Typearticle
Languageen
FieldComputer Science
TopicPeer-to-Peer Network Technologies
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsComputer networkComputer scienceHandoverWireless networkWirelessNetwork packetScheme (mathematics)Peer-to-peerThroughputLive streamingTelecommunications

Abstract

fetched live from OpenAlex

In this paper, we propose a centralised Peer-to-Peer (P2P) streaming over hybrid wireless networks to mitigate the congestion at the Access Point (AP) in Wireless Local Area Networks (WLANs). In our proposed architecture, an adaptive receiver-driven mechanism is used to coordinate the streaming from multiple senders. We also propose a peer handoff scheme and an AP handoff scheme for video streaming over hybrid wireless networks. The simulation results show that (1) centralised P2P video streaming over a hybrid wireless network can achieve a much better quality compared to traditional WLAN deployment with heavy background traffic, (2) the adaptive receiver-driven mechanism can synchronise packet delivery from multiple senders, thus increasing streaming quality, (3) the peer handoff scheme enables the receiver to maintain a high aggregate throughput from multiple serving-peers and (4) the AP handoff scheme enables the receiver to roam freely through different cells, while maintaining continuous video streaming.

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 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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.946
Threshold uncertainty score0.918

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0030.001
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 head0.016
GPT teacher head0.281
Teacher spread0.265 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations1
Published2007
Admission routes1
Has abstractyes

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