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Record W3081214814 · doi:10.1109/cjece.2019.2897277

A New TCAM Architecture for IP Routing With Update Complexity Equal to O(1)

2020· article· en· W3081214814 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Journal of Electrical and Computer Engineering · 2020
Typearticle
Languageen
FieldComputer Science
TopicNetwork Packet Processing and Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsRouting tableComputer scienceComputer networkNetwork packetRouting (electronic design automation)Loose Source RoutingTable (database)Content-addressable memoryPacket forwardingThe InternetIP forwardingVirtual routing and forwardingPrefixDistributed computingRouting protocolOperating systemDatabase

Abstract

fetched live from OpenAlex

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.

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: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.490
Threshold uncertainty score0.363

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 science0.0000.000
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 head0.013
GPT teacher head0.188
Teacher spread0.175 · 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