A New TCAM Architecture for IP Routing With Update Complexity Equal to O(1)
Bibliographic record
Abstract
Ternary content addressable memories (TCAMs) have a lookup complexity of O(1). They require just one memory access to find an entry. For this reason, they are widely used in core routers of the Internet to achieve high packet forwarding capacities in terms of several 100 Gb/s. However, in a TCAM, the routing table needs to be stored in a sorted order according to the prefix length of the entries. Therefore, if a new entry needs to be added or an old one needs to be deleted, some other entries should be moved around to open a place for the new entry or fill the place of the old one. Practical methods to update a routing table require locking the TCAM during the update process. Therefore, this will cause a large number of packets to be dropped. This is because in the core routers of the Internet, the packets arrive at very high rates, and the routing table updates are very frequent. In this paper, we introduce a new, yet simple TCAM architecture in which entries do not need to be sorted. This means that updating the routing table will be done with a complexity of O(1), and therefore, no packets will be dropped.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".