Bibliographic record
Abstract
Wireless networks are being deployed widely to provide network connectivity without requiring the web of physical wires. A collection of a small number of workstations connected using a wireless network forms a wireless local area network (WLAN) that follows the IEEE 802.11 standard. In a WLAN, the communication takes place using packets whose sizes may vary and have a significant impact on the delay incurred during transmission. In this regard, fragmentation may play a vital role in reducing the delay for efficient transmission across the network. This paper analyzes the performance of WLANs with respect to the packet fragmentation. We simulate three network scenarios having 4, 8 and 12 wireless workstations respectively. The scenarios are simulated using OPNET IT Guru Academic Edition v 9.1 while incorporating a peer-to-peer (P2P) based communication model for each scenario. We compare the performance of non-fragmented and fragmented communication in terms of network delay and throughput. Our results show that the fragmentation minimizes the delay and increases the throughput, however its impact is highly dependent on the size of the underlying network.
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 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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".