On the inadequacy of MANET routing to efficiently use the wireless capacity
Bibliographic record
Abstract
Wireless bandwidth is a limited and scarce shared resource in MANETs. A number of experimental and analytical studies have shown that the multi-hop nature results in nodes experience low bandwidth. Compounding this problem further are the routing protocols themselves: as they typically minimize either hop count or number of packet retransmissions, they favor routes in the centre of a MANET. This results in a reduction of spatial reuse, inefficiently using the scarce wireless bandwidth. In our work, we are interested in the "end-to-end capacity" of the network, which we define to be the sum of the throughputs for each flow. This represents the service a network provides to its users. In this paper, we determine the maximal MANET capacity through linear programming and evaluate the performance of AODV and DSR with respect to this maximum value. The result shows that these typical MANET routing protocols do not utilize the network resources efficiently, achieving less than 17% of that capacity even in the best possible case. New routing protocols are therefore required to make more efficient use of this limited resource.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".