Combining SPF and Source Routing for an Efficient Probing Solution in IPv6 Topology Discovery
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
For efficient network management, knowing the full topology of the network is important. Topology discovery using source routing and routing protocols are two well known methods to discover layer 3 connectivity. Source routing has the probing space explosion phenomenon that generates a large volume of traffic. As a result, source routing based approach takes a significant amount of time for network operators to discover and troubleshoot the whole network. Although routing protocol based approach like OSPFv3 discovers the network connectivity, the full IPv6 address cannot be discovered, as the approach only discovers the prefix portion of IPv6 addresses. This thesis proposes an efficient probing space reduction algorithm by combining source routing and OSPFv3. The idea is to apply source routing based on the information obtained from OSPFv3 based discovery for IPv6. Experimental results show that the proposed algorithm reduces redundant probing significantly which is useful for network management.
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 | 0.001 | 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 | 0.000 | 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