Memory requirements for future Internet routers with essentially-perfect QoS guarantees
Bibliographic record
Abstract
The theory of a future Internet network which achieves essentially-perfect QoS guarantees for all QoS-enabled traffic flows for all loads ≤ 100% of capacity has recently been established. A scheduling algorithm with a bounded normalized service lead/lag (NSLL) is used to schedule traffic flows within the routers. An 'Application-Specific Token-Buffer Traffic Shaper' is used at the traffic sources, to achieve a bounded NSLL on incoming bursty traffic flows. An 'Application-Specific Playback Queue' is used to perfectly regenerate the original busty traffic flows at every destination. Under these conditions, it has been established that every QoS-enabled flow: (i) is delivered with essentially-perfect end-to-end QoS guarantees, and (ii) buffers O(K) cells/packets per router, where K is the bound on the NSLL. In this paper, we reduce the router buffering requirements significantly, so that each router buffers ≤ one cell/packet per QoS-enabled traffic flow, a reduction of up to 1K-10K over existing technologies. The proposed technology can be incorporated into new routers with negligible hardware cost, and is compatible with existing IntServ, DiffServ, MPLS and RSVP-TE protocols.
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How this classification was reachedexpand
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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".