Enhancing Timer-Based Power Management to Support Delay-Intolerant Uplink Traffic in Infrastructure IEEE 802.11 WLANs
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
Efficient power management of the radio is a critical requirement for the battery-operated portable electronic devices incorporating wireless transceivers to have a longer runtime. The power management function of IEEE 802.11 wireless local area networks (WLANs) allows stations (STAs) to operate in the doze mode to save energy significantly. In this paper, the enhanced timer-based power management (E-TPM) scheme, which supports the applications with delay-intolerant uplink traffic (DIUT), is presented for infrastructure IEEE 802.11 WLANs. With E-TPM, the radio transceiver of the dozing STA is woken up right away when an outgoing frame is generated by the STA so that DIUT is transmitted in a timely manner. In addition, a novel model for stochastic analysis of the E-TPM is developed. Based on this model, the probabilities that an STA is active, idle, or dozing are derived, and the power consumption of the STA, the number of frames buffered at the access point (AP) for the STA operating in doze mode, and the average delay per frame are obtained. These results enable an efficient power management algorithm that optimizes the idle timer and doze duration at the STA so that the doze mode does not result in extra delay in DIUT, and the delay of downlink traffic is controlled within a given bound. Numerical results show that the proposed E-TPM is able to considerably reduce delay with limited available memory space at the AP.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 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 it