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Record W2102243509 · doi:10.1145/1454573.1454575

Evaluating video streaming over UWB wireless networks

2008· article· en· W2102243509 on OpenAlex
Rukhsana Ruby, Yangyang Liu, Jianping Pan

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
FieldEngineering
TopicUltra-Wideband Communications Technology
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Victoria
KeywordsComputer scienceWirelessComputer networkWireless networkBroadbandProvisioningLatency (audio)ReservationWireless broadbandBroadband networksVideo qualityThe InternetVideo streamingLow latency (capital markets)ThroughputTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

Video streaming is going to drive the Internet to a new height. However, how to distribute the high-quality video streams that are already delivered to the doorsteps of ordinary customers to almost all rooms in their dwellings still remains a technique challenge. There are various proposals for wired, ``no-new-wires or wireless approaches, but their performance in real environment is yet to be examined. In this paper, we evaluate the performance of high-quality video streaming over short-range wireless networks, specifically Ultra-Wide Band (UWB), for a two-tiered broadband home network. Our analysis and experiment results reveal the unique features of UWB reservation schemes and their intrinsic throughput-latency tradeoffs, which indicates the efficacy of UWB for high-speed, in-room wireless access with both quality and mobility provisioning.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.469
Threshold uncertainty score0.448

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 head0.028
GPT teacher head0.272
Teacher spread0.243 · 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

Citations12
Published2008
Admission routes2
Has abstractyes

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