A novel dynamic reputation-based source routing protocol for mobile ad hoc networks
Bibliographic record
Abstract
A Mobile Ad hoc NETwork (MANET) is a group of self-organized wireless mobile nodes (MNs) able to communicate with each other without the need of any fixed network infrastructure nor centralized administrative support. Furthermore, the transmission range in such mobile devices is limited; thus, a packet is forwarded in a multihop path relying on the nodes in the routing path. Due to that, MANETs need the cooperation of every node in the path to achieve a successful packet delivery. However, depending on the MANET application, nodes are willing to cooperate with each other (e.g., rescuing services) since they are controlled by an authority, or might be reluctant to cooperate (e.g., data sharing [ 1 ], traffic monitoring [ 2 ], emergency assistance services [ 3 , 4 ], and multimedia data transmission [ 5 ]) trying to save their own resources. Since MANET nodes usually have limited power (i.e., battery) and scarce computational resources (CPUs), nodes might refuse to cooperate in order to save their limited resources. This misbehavior of nodes would drastically affect the routing protocol operation.
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.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".