Delay performance of CSMA policies in multihop wireless networks: A new perspective
Bibliographic record
Abstract
In this paper, we study the delay performance of CSMA policies in wireless networks, where the delay is defined as the average time that a silent wireless link needs to wait until it accesses the channel for packet transmission. It is well-known that CSMA policies can incur an access delay that may be correlated over time and may grow exponentially with the network size. This discourages practical implementation of CSMA policies in even mid-sized networks. In this paper, we provide a new perspective on the delay performance of CSMA policies. We present recently developed results for two important interference models and show how CSMA policies can be used to ensure an access delay that is memoryless over time or that does not grow with the network size. The two interference models that we consider are primary interference and the ¿lattice interference graph¿. Our results suggest that CSMA policies can achieve a delay performance, as well as a delay-throughput trade-off, that makes them viable to be used in practice.
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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 | 0.003 | 0.017 |
| 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 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".