Efficient and secure routing protocol based on Blockchain approach for wireless sensor networks
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
Abstract Embedded systems and wireless sensor networks (WSN) are found today in increasingly critical areas of applications. They have become integrated and embedded in nearly all aspects of everyday life, including manufacturing, healthcare, education, critical infrastructure, and entertainment. The number of connected devices continues to grow, and due to the insecure nature of these devices, the amount of risk continues to grow as well. These risks, however, can be mitigated with the creation and adoption of WSN security standards developed to create an environment of safety, security, and confidence in the technology. Designing the security policy for WSNs requires asking some preliminary questions. These questions are particularly important in the case of WSNs because their use is highly decentralized. Blockchain's ability on governing decentralized networks makes it especially suitable for designing a self‐managing system on WSN devices. This article proposes a routing protocol that uses Blockchain technology to offer a shared memory between the network's nodes. The simulation results have shown that this solution could be applicable and could resolve the issues cited above.
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 | 0.000 | 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 | 0.000 | 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