MétaCan
Menu
Back to cohort
Record W2132187255 · doi:10.1145/2444776.2444779

Towards accurate accounting of cellular data for TCP retransmission

2013· article· en· W2132187255 on OpenAlexaff
Younghwan Go, Denis Foo Kune, Shinae Woo, KyoungSoo Park, Yongdae Kim

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGreen IT and Sustainability
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsRetransmissionComputer networkComputer scienceTransport layerNetwork packetPayload (computing)Reliability (semiconductor)Computer securityLayer (electronics)

Abstract

fetched live from OpenAlex

The current architecture supporting data services to mobile devices is built below the network layer (IP) and users receive the payload at the application layer. Between them is the transport layer that can cause data consumption inflation due to the retransmission mechanism that provides reliable delivery. In this paper, we examine the accounting policies of five large cellular ISPs in the U.S. and South Korea. We look at their policies regarding the transport layer reliability mechanism with TCP's retransmission and show that the current implementation of accounting policies either fails to meet the billing fairness or is vulnerable to charge evasions. Three of the ISPs surveyed charge for all IP packets regardless of retransmission, allowing attackers to inflate a victim's bill by intentionally retransmitting packets. The other two ISPs deduct the retransmitted amount from the user's bill thus allowing tunneling through TCP retransmissions. We show that a "free-riding" attack is viable with these ISPs and discuss some of the mitigation techniques.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.876
Threshold uncertainty score0.461

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 head0.025
GPT teacher head0.246
Teacher spread0.221 · 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
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

Citations18
Published2013
Admission routes1
Has abstractyes

Explore more

Same topicGreen IT and SustainabilityFrench-language works237,207