CORE: a coding-aware opportunistic routing mechanism for wireless mesh networks [Accepted from Open Call
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
Opportunistic routing is a new routing paradigm that takes advantage of the broadcast characteristic of a wireless channel for data delivery in a wireless mesh network. Network coding has recently emerged as a new coding paradigm that can significantly improve the throughput performance of a WMN. In this article we explore the combination of opportunistic routing and network coding for improving the performance of a WMN. We first review existing opportunistic routing and coding-aware routing protocols, respectively, classify these protocols based on different criteria, and discuss their merits and drawbacks. We then propose a coding-aware opportunistic routing mechanism that combines hop-by-hop opportunistic forwarding and localized inter-flow network coding for improving the throughput performance of a WMN. Through opportunistic forwarding, CORE allows the next-hop node with the most coding gain to continue the packet forwarding. Through localized network coding, CORE attempts to maximize the number of packets that can be carried in a single transmission. Simulation results show that CORE can significantly improve the throughput performance of a WMN as compared with existing protocols.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.014 | 0.004 |
| 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