Joint Handoff and Energy Management for a Wireless Mesh Network
Bibliographic record
Abstract
A lot of access points (APs) in wireless mesh networks (WMNs) are battery powered. In order to minimize their energy consumption, the APs can adaptively adjust their transmission power and time based on various network conditions. In this paper, the problem of minimizing the AP energy consumption is formulated as an optimization problem with the constraint to satisfy the throughput requirements of associated mobile stations (MSs). Balancing the energy consumption of the APs can be important to prolong the network lifetime, particularly in a network with high and random user mobility, which can easily result in unbalanced traffic load and energy consumption among the APs. Two distributed handoff schemes are proposed for a WMN with adaptive transmission power and rate. One scheme attempts to achieve balanced energy consumption among the APs during each scheduling interval, and the other scheme balances the AP energy consumption over a longer term. Numerical results show that both schemes achieve much longer network lifetime than the traditional distance-based handoff scheme, while the long-term based handoff scheme can achieve the objective with approximately the same number of handoffs as the distance-based handoff.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".