Performance analysis of two dynamic link selection algorithms in ad hoc CDMA networks
Bibliographic record
Abstract
In a mobile ad hoc network, the connection between an arbitrary source and destination node can be established using intermediate nodes. Most of the mobile nodes heavily rely on the battery power to keep themselves alive. Therefore, the battery power (or battery lifetime) and the number of relaying nodes (or delay) play a major role in mobile ad hoc networking. In this paper we discuss three existing common algorithms, MHC, MTPR, and MBCR which are used to minimize the delay, power and nodal over-utilization respectively. This paper also proposes two new algorithms namely, MWBCR and MTP-WBCR and investigates their performance in terms of power and delay. These power-aware algorithms are simulated using JAVA. The simulation results show that the proposed algorithms require more transmission power and delay than others. However, it is expected that the fairness in utilizing relaying nodes in terms of in power and delay will be improved using the new algorithms.
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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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".