Delay-Aware Load Balancing Over Multipath Wireless Networks
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Bibliographic record
Abstract
The ability of mobile devices to be connected to more than one radio node at the same time enables mobile devices to transmit and receive traffic to and from multiple paths. This ability helps to increase the average mobile device data rate and to improve the network reliability. Load balancing among multiple paths become a key factor to avoid network congestion, nevertheless it requires efficient techniques to split traffic without adding more delay or generating too much packet reordering for delay-sensitive traffic. In this paper, we address two key issues in the context of uplink wireless mobile networks: 1) how to accurately split traffic among multiple paths and 2) how to minimize the end-to-end delay without increasing packet reordering. We propose delay-aware load balancing algorithm (DALBA), a novel strategy that splits traffic at the granularity of the packet. DALBA aims to minimize the splitting error (SE) and the end-to-end delay difference by effectively using all of the available paths. We analyze DALBA's performance through extensive simulations using H.264 video traffic. Numerical results demonstrate that DALBA outperforms previous algorithms in terms of SE, end-to-end delay and peak signal-to-noise ratio while keeping packet reordering to a suitable low value.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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