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Record W2110625060 · doi:10.1109/ccece.2005.1556960

Differentiated back-off for ethernet

2006· article· en· W2110625060 on OpenAlexaff
Sudhakar Ganti, B. Raahemi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWireless Networks and Protocols
Canadian institutionsUniversity of OttawaUniversity of Victoria
Fundersnot available
KeywordsComputer networkComputer scienceMedia access controlAccess controlQuality of serviceWirelessOperating system

Abstract

fetched live from OpenAlex

The network devices in the IEEE 802.3 based Ethernet networks use a carrier-sense-multiple-access with collision-detection (CSMA/CD) protocol to access the shared bus. There is no priority based access control to the shared bus in this protocol. All stations (nodes) run the same algorithm to access the bus and perform an exponential back-off when contention arises. This makes it difficult to achieve quality-of-service (QoS) guarantees (relative or quantitative) among different applications. Even if priority queuing is implemented, all the stations on the network use the same back-off algorithm at the medium access control (MAC) layer and thus does not provide any priority-based access to the bus. As there is a wide deployment of Ethernet networks, any modification to the protocol should inter-operate with existing devices, as it would be very difficult to upgrade all devices. This paper proposes a modification to the back-off scheme which does not require any modifications to the existing devices, but newer devices, such as voice-over-IP (VoIP) phones and multimedia devices can make use of the modification to get a relative priority over others. Both analysis and simulation results confirm that, using differentiated back-off, high-priority traffic get quicker access to the bus (higher throughput and lower delay) than low priority traffic

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: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.820
Threshold uncertainty score0.228

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 head0.015
GPT teacher head0.243
Teacher spread0.228 · 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 designNot applicable
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

Citations0
Published2006
Admission routes1
Has abstractyes

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