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Record W2108337720 · doi:10.1109/tmc.2006.25

Power saving access points for IEEE 802-11 wireless network infrastructure

2006· article· en· W2108337720 on OpenAlexafffund
Feng Zhang, T.C. Todd, Dongmei Zhao, V. Kezys

Bibliographic record

VenueIEEE Transactions on Mobile Computing · 2006
Typearticle
Languageen
FieldComputer Science
TopicWireless Networks and Protocols
Canadian institutionsBlackberry (Canada)McMaster University
FundersIndian Council of Agricultural ResearchMcMaster University
KeywordsComputer scienceComputer networkInter-Access Point ProtocolWireless distribution systemIEEE 802.11WirelessIEEE 802.11uWireless networkIEEE 802.11b-1999IEEE 802Backward compatibilitySoftware deploymentNetwork allocation vectorWi-FiTelecommunicationsQuality of service

Abstract

fetched live from OpenAlex

In the past decade, there has been a huge proliferation of wireless local area networks (WLANs) based on the IEEE 802.11 WLAN standard. As 802.11 connectivity becomes more ubiquitous, multihop communications will be increasingly used for access point range extension and coverage enhancement. In this paper, we present a design for an IEEE 802. 11 -based power saving access point (PSAP), intended for use in multihop battery and solar/battery powered applications. These types of APs have many practical applications and can be deployed very quickly and inexpensively to provide coverage enhancement in situations such as campuses, building complexes, and fast deployment scenarios. Unlike conventional wired access points, in this type of system, power saving on the AP itself is an important objective. A key design constraint is that the proposed PSAP be backward compatible to a wide range of IEEE 802.11 functionality and existing wired access points. In this paper, we introduce the protocols required to achieve this compatibility, show the constraints imposed by this restriction, and present performance results for the proposed system.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.271
Teacher spread0.259 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations48
Published2006
Admission routes2
Has abstractyes

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