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Record W1492109941 · doi:10.1109/icc.2015.7249173

Bandwidth allocation and pricing for SDN-enabled home networks

2015· article· en· W1492109941 on OpenAlexaff
Homa Eghbali, Vincent W. S. Wong

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSoftware-Defined Networks and 5G
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsStackelberg competitionComputer scienceSoftware-defined networkingComputer networkQuality of serviceService providerThe InternetBandwidth (computing)Stochastic gameBandwidth allocationDynamic pricingQuality of experienceService (business)Business

Abstract

fetched live from OpenAlex

In this paper, we propose to combine the emerging software defined networking (SDN) paradigm with the existing residential broadband infrastructure to enable home users to have dynamic control over their traffic flows. The SDN centralized control technology enables household devices to have virtualized services with quality of service (QoS) guarantee. SDN-enabled open application programming interfaces (APIs) allow Internet service providers (ISPs) to perform bandwidth slicing in home networks and implement time-dependent hybrid pricing. Given the requests from household devices for virtualized and non-virtualized services, we formulate a Stackelberg game to characterize the pricing strategy of ISP as well as bandwidth allocation strategy in home networks. In the Stackelberg game, the leader is the ISP and the followers are the home networks. We determine the optimal strategies which provide maximal payoff for the ISP. Numerical results show that our proposed SDN-enabled home network technology with the hybrid pricing scheme provides a better performance than a usage-based pricing scheme tailored for best-effort home networks.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.911
Threshold uncertainty score0.300

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 head0.024
GPT teacher head0.235
Teacher spread0.211 · 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 designSimulation or modeling
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

Citations19
Published2015
Admission routes1
Has abstractyes

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