Mobile Edge Computing via Wireless Power Transfer Over Multiple Fading Blocks: An Optimal Stopping Approach
Bibliographic record
Abstract
To support wireless Internet of things (IoT) devices, this paper presents a new solution which combines wireless power transfer and mobile edge computing. Specifically, we consider one mobile device, which first harvests energy from radio frequency signals sent by a base station and then offloads all or part of its data to be processed to the base station. The process of energy harvesting and offloading span over multiple fading blocks. The target is to maximize the average amount of processed data in unit time. To achieve this target, we optimize the stopping rule for energy harvesting (i.e., when to stop energy harvesting and start offloading) and the number of fading blocks for data offloading. To solve the formulated problem optimally, we decompose it into two levels. In the lower level, the stopping rule for energy harvesting is optimized given a fixed number of fading blocks for offloading. The associated lower-level problem is solved optimally based on a series of special properties of the problem. In the upper level, the number of fading blocks for offloading is optimized. Efficiency of our work with fully offloading mode and partially offloading mode is shown by using simulation.
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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 | 0.000 | 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".