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Record W2016565546 · doi:10.3390/photonics1010047

The Escape of Sisyphus or What “Post NG-PON2” Should Do Apart from Neverending Capacity Upgrades

2014· article· en· W2016565546 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePhotonics · 2014
Typearticle
Languageen
FieldEngineering
TopicAdvanced Photonic Communication Systems
Canadian institutionsInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceBackhaul (telecommunications)ProvisioningPassive optical networkAccess networkLimitingTelecommunicationsComputer networkWirelessWavelength-division multiplexingEngineering

Abstract

fetched live from OpenAlex

The primary design goal of (r)evolutionary NG-PON1&2 was the provisioning of an ever increasing capacity to cope with video-dominated traffic and handle the explosion of mobile data traffic by means of offloading. Recently, however, questions on the future of “post NG-PON2” have surfaced whether to shift its research focus to business and operation related aspects and move access technology into a substantially different direction than continued capacity upgrades. In fact, recent studies indicate that ultimately the major factor limiting the performance of 4G mobile networks is latency rather than capacity of the backhaul. In this paper, we review recently proposed low-latency techniques for NG-PONs that require architectural modifications at the remote node or distribution fiber level and highlight advanced network coding and real-time polling based low-latency techniques that can be implemented in software, enable NG-PONs to carry higher traffic loads and thereby extend their lifetime, and maintain the passive nature of existent optical distribution networks. Furthermore, we elaborate on emerging trends and open challenges for future post NG-PON2 research. To better understand their true potential, we put them into a wider non-technical and historical perspective leading up to a sustainable Third Industrial Revolution (TIR) economy and its underlying Energy Internet.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.555
Threshold uncertainty score0.761

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 head0.040
GPT teacher head0.255
Teacher spread0.215 · 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