An Ultra-Low-Latency Guaranteed-Rate Internet for Cloud Services
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
An Enhanced-Internet network that provides ultra-low-latency guaranteed-rate (GR) communications for Cloud Services is proposed. The network supports two traffic classes, the Smooth and Best-Effort classes. Smooth traffic flows receive low-jitter GR service over virtual-circuit-switched (VCS) connections with negligible buffering and queueing delays, up to 100% link utilizations, deterministic end-to-end quality-of-service (QoS) guarantees, and improved energy efficiency. End-to-end delays are effectively reduced to the fiber “time of flight.” A new router scheduling problem called the Bounded Normalized-Jitter integer-programming problem is formulated. A fast polynomial-time approximate solution is presented, allowing TDM-based router schedules to be computed in microseconds. We establish that all admissible traffic demands in any packet-switched network can be simultaneously satisfied with GR-VCS connections, with minimal buffering. Each router can use two periodic TDM-based schedules to support GR-VCS connections, which are updated automatically when the router's traffic rate matrix changes. The design of a Silicon-Photonics all-optical packet switch with minimal buffering is presented. The Enhanced-Internet can: 1) reduce router buffer requirements by factors of ≥ 1000; 2) increase the Internet's aggregate capacity; 3) lower the Internet's capital and operating costs; and 4) lower greenhouse gas emissions through improved energy efficiency.
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 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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