Multiple access computational offloading with computation constraints
Bibliographic record
Abstract
The shared computational resources provided by the mobile cloud computing paradigm offer the opportunity for mobile devices to reduce the energy expended, or the latency incurred, in performing significant computational tasks. To maximize their impact, cloud computing systems must jointly optimize the allocation of the computational and radio resources. We consider a scenario in which two mobile users access a finite computational resource through a single wireless access point. The resources to be allocated are the fractions of the computational resource allocated to each user, and the users' transmission powers and data rates. The key constraints are the size of the computational resource and the region of rates that can be achieved by the chosen multiple access scheme. In this paper a quasi-closed-form solution is obtained to a problem in which the computational fractions, powers and rates are optimized so as to minimize the energy required to offload tasks with specified latency constraints. In doing so, it is shown that by exploiting the fundamental capabilities of the multiple access channel, rather than just the rates of a particular multiple access scheme, the energy required to offload the tasks can be substantially reduced.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".