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Record W2170944998 · doi:10.1109/pimrc.2009.5450023

An architecture with QoS support for application layer multicasting over wireless mesh networks

2009· article· en· W2170944998 on OpenAlexaff
Amr Alasaad, Sathish Gopalakrishnan, Victor C. M. Leung

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicPeer-to-Peer Network Technologies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMulticastComputer networkComputer scienceXcastProtocol Independent MulticastIP multicastSource-specific multicastOverlay multicastDistributed computingPragmatic General MulticastWireless mesh networkDistance Vector Multicast Routing ProtocolMulticast addressQuality of serviceWireless networkWirelessTelecommunications

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. The high capacity at mesh routers nodes allows applications such as real time multicast over WMNs. In light of the slow development of IP multicast and the rise of peer-to-peer communication, implementing multicast capability at the application layer is imminent. QoS support for application layer multicast over WMNs is challenging due to the architecture of the overlay networks, characteristics of the wireless medium, and end users limited bandwidth efficiency. We argue for ring-based overlay multicast scheme with support from wireless mesh routers for the multicast applications. We demonstrate, using extensive simulations, that this approach has excellent potential to improve the performance of the peer-to-peer multicast applications in a wireless setting; specifically we focus on many-to-many real time multimedia applications 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.

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)0.000
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 score0.940
Threshold uncertainty score0.624

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 science0.0010.000
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 head0.012
GPT teacher head0.266
Teacher spread0.254 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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

Citations2
Published2009
Admission routes1
Has abstractyes

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