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Record W1598470171 · doi:10.1109/wimob.2005.1512924

Rate-adaptive multicast in mobile ad-hoc networks

2006· article· en· W1598470171 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
TopicWireless Networks and Protocols
Canadian institutionsYork University
Fundersnot available
KeywordsMulticastComputer networkComputer scienceProtocol Independent MulticastSource-specific multicastReliable multicastDistance Vector Multicast Routing ProtocolThroughputXcastPragmatic General MulticastNetwork packetIP multicastDistributed computingWirelessTelecommunications

Abstract

fetched live from OpenAlex

A current trend in wireless communications is to enable wireless devices to transmit at different rates. That multirate capability has been defined in many standards such as 802.11a, 802.11b, 802.11g, and HiperLAN2. We propose a rate-adaptive multicast (RAM) protocol that is multirate-aware. During the process of path discovery, the quality of wireless links is estimated to suggest optimal transmission rates, which are then used to calculate the total transmission time incurred by the mobile nodes on a path. Among several considered paths from a source to a destination, RAM selects the path with the lowest total transmission time. Our work is the first that proposes the use of the multirate capability in multicast. The proposed RAM protocol works with any multirate standards, and does not require any modifications to the standards. Our simulation results show that RAM outperforms single-rate multicast in terms of packet delivery ratio, packet end-to-end delay, and throughput of the multicast group.

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 score0.954
Threshold uncertainty score0.461

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.011
GPT teacher head0.242
Teacher spread0.231 · 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

Citations47
Published2006
Admission routes1
Has abstractyes

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