Bibliographic record
Abstract
It is widely accepted that Ad Hoc networks are at the leading edge of the research in the domain of wireless networking. These networks are not supported by infrastructure to connect the mobile hosts, thereby they have to be self configured, self organized and the resources have to be allocated in a distributed manner. The medium access control (MAC) layer is seen as the bottleneck for the throughput in wireless Ad hoc networks. Hence, we propose in this work a new Multichannel MAC protocol. The proposed protocol can be based on Code Division Multiple Access (CDMA) or Frequency Division Multiple Access (FDMA). A channel can be represented by one spreading code in CDMA systems or by one frequency band in FDMA case. In our analysis and simulations, we assume that the protocol is based on CDMA technique. We consider one channel for control packets and multiple channels for transmitting data information. We propose that the reservation of a data cannel is done implicitly using the common channel. We show through computer simulations that our proposition of Multichannel MAC protocol improves significantly the communication performance in wireless Ad Hoc networks, even when the introduced overhead is considered.
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 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".