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Record W2028270449 · doi:10.1145/2612669.2612679

(Near) optimal resource-competitive broadcast with jamming

2014· article· en· W2028270449 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
TopicSecurity in Wireless Sensor Networks
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsJammingComputer scienceResource (disambiguation)TelecommunicationsComputer network

Abstract

fetched live from OpenAlex

We consider the problem of broadcasting a message from a sender to n ≥ 1 receivers in a time-slotted, single-hop, wireless network with a single communication channel. Sending and listening dominate the energy usage of small wireless devices and this is abstracted as a unit cost per time slot. A jamming adversary exists who can disrupt the channel at unit cost per time slot, and aims to prevent the transmission of the message. Let T be the number of slots jammed by the adversary. Our goal is to design algorithms whose cost is resource-competitive, that is, whose per-device cost is a function, preferably o(T), of the adversary's cost. Devices must work with limited knowledge. The values n, T, and the adversary's jamming strategy are unknown.

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 score0.771
Threshold uncertainty score0.585

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 science0.0010.000
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 head0.006
GPT teacher head0.194
Teacher spread0.189 · 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

Citations22
Published2014
Admission routes1
Has abstractyes

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