Wireless Fountain Coding with IEEE 802.11e Block ACK for Media Streaming in Wireline-cum-WiFi Networks: A Performance Study
Bibliographic record
Abstract
We develop performance models for delay-sensitive uplink media streaming over a wireline-cum-WiFi network. Since the wireless channel is normally a bottleneck for such streaming, we modify the traditional 802.11e block acknowledgment (B-ACK) scheme to work with wireless fountain coding (WFC)-a packet-level coding scheme which codes packets in a similar manner to intrasession random network coding but delivers them in a manner similar to fountain coding. By using this modified B-ACK scheme, protocol complexity and wireless link-layer delay are potentially reduced. We analytically quantify this delay and use it to derive end-to-end packet loss/late probabilities when automatic repeat request (ARQ) and forward error correction (FEC) are jointly employed at the application-layer. We develop an integrated ns-3/EvalVid simulator to validate our models and compare them with the case when the traditional 802.11e B-ACK scheme is employed. Through simulations of video streaming, we observe that the modified B-ACK scheme does not always perform better than the traditional B-ACK scheme in terms of end-to-end packet loss/late probability and video distortion under certain conditions of the wireless channel. This observation leads us to propose a hybrid scheme that switches between the modified and traditional B-ACK strategies according to the conditions of the wireless channel and the number of packets to transmit in a block. Via simulations, we show the benefits of the hybrid scheme when compared to the traditional IEEE 802.11e B-ACK scheme under different network settings.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 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".