Proceedings of the 2nd ACM international workshop on Performance evaluation of wireless ad hoc, sensor, and ubiquitous 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
Wireless ad hoc, sensor, along with ubiquitous networks have recently witnessed a dramatic growth, and this trend is likely to continue for the foreseeable future. However, as such networks become more widespread and complex, performance modeling and evaluation will play a crucial part in their design process to ensure their successful deployment and exploitation in practice.In this context, the Second International Workshop on Performance Evaluation of Wireless Ad Hoc, Sensor, and Ubiquitous Networks (PE-WASUN) aims at bringing together scientists, engineers, and practitioners to share and exchange their experience, discuss challenges, and report state-of-the-art and in-progress research on all aspects of wireless ad hoc, sensor, and ubiquitous networks, with a specific emphasis on their performance evaluation and analysis. The workshop is held in conjunction with the 8th ACM/IEEE International Symposium on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM), and takes place in Montreal, one of the most dynamic towns in the world.The general interest in the topics of the workshop is testified by the number of submissions received: 99 papers form major research groups worldwide. After a careful review process, 33 papers were accepted for regular presentations at the workshop, which represents a 31% acceptance rate. Moreover, following recommendations from the TPC members, 8 papers were accepted as short presentations and 12 as posters. We believe that the range of topics in these papers provide an interesting and complete view of the state-of-the-art in the field of performance evaluation of wireless ad hoc, sensor, and ubiquitous networks.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| 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