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Record W2992966382 · doi:10.1109/have.2019.8921300

Can We Deploy Tactile Internet Applications over Wi-Fi, 3G and WiMAX: a Comparative Study based on Riverbed Modeler

2019· article· en· W2992966382 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.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicNetwork Time Synchronization Technologies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsComputer scienceWiMAXComputer networkJitterThe InternetQuality of serviceHaptic technologyNetwork packetPacket lossReliability (semiconductor)Internet accessMultimediaTelecommunicationsWirelessSimulationWorld Wide Web

Abstract

fetched live from OpenAlex

After the birth of mobile networks and the Internet of things (IoT), the focus of the new generation of mobile communications is moving towards appending haptic information to traditional audiovisual multimedia. This will extremely demand an ultra-low latency with high availability, reliability and secure networks, which is referred to as the Tactile Internet. In the frame of preparing the adequate infrastructure for haptic communications, that play a major role in Tactile Internet, this article estimates several key performance indicators (KPIs) such as jitter, end-2-end delay, throughput and packet loss through simulations of different networks backbones (Wi-Fi, 3G and WiMAX) using Riverbed modeler. These KPIs help us evaluate the network's performance, taking into consideration the distance from users to the access point, the different types of applications as well as their minimum Quality of Service (QoS).

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.853
Threshold uncertainty score0.618

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 head0.016
GPT teacher head0.253
Teacher spread0.238 · 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