Contention‐free approaches for WiFi MAC design for VoIP services: performance analysis and comparison
Bibliographic record
Abstract
Abstract The exponential growth in the demand of voice over internet protocol (VoIP) services along with the increasing demand for mobility in VoIP services has attracted great research efforts towards provisioning of VoIP services in IEEE 802.11‐based Wireless LANs (WiFi networks). We address one of the important research problems, namely, the quality of service (QoS)‐aware efficient silence suppression in the bursty voice traffic, for provisioning VoIP services in WiFi networks. The research works in the recent literature on silence suppression in voice calls have been surveyed categorising them on how the activity arrival is notified to the access point (AP). In most of the recent schemes, notification of uplink activity arrival is done through contention based medium access mechanisms such as the distributed coordination function (DCF). Contention‐based medium access causes non‐deterministic delays, therefore such schemes are not suited to voice traffic which require strict delay bound guarantees. This paper focuses on the schemes which do not use contention based approaches for silence suppression in voice traffic. Analytical performance evaluation and comparison of such schemes is carried out. Two very important performance metrics are modelled mathematically. One is the expected polling overhead time that the schedulers in these schemes can save per voice call during one voice activity cycle as compared to that in the round‐robin polling scheduler. The other is the expected unnecessary wireless channel access delay that a typical first talk‐spurt frame experiences due to the specific design of each scheme. The numerical results of this evaluation lead us to the conclusion whether or not and to what extent each of these schemes is viable. Copyright © 2008 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".