Providing QoS for Networked Peers in Distributed Haptic Virtual Environments
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.
Bibliographic record
Abstract
Haptic information originates from a different human sense (touch), therefore the quality of service (QoS) required to support haptic traffic is significantly different from that used to support conventional real‐time traffic such as voice or video. Each type of network impairment has different (and severe) impacts on the user′s haptic experience. There has been no specific provision of QoS parameters for haptic interaction. Previous research into distributed haptic virtual environments (DHVEs) have concentrated on synchronization of positions (haptic device or virtual objects), and are based on client‐server architectures. We present a new peer‐to‐peer DHVE architecture that further extends this to enable force interactions between two users whereby force data are sent to the remote peer in addition to positional information. The work presented involves both simulation and practical experimentation where multimodal data is transmitted over a QoS‐enabled IP network. Both forms of experiment produce consistent results which show that the use of specific QoS classes for haptic traffic will reduce network delay and jitter, leading to improvements in users′ haptic experiences with these types of applications.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it