Impact of Route Selection Metrics on the Performance of On-Demand Mesh-based Multicast Ad hoc Routing
Bibliographic record
Abstract
The main objective of this paper is to study the stability and energy consumption issues of mesh-based multicast routing for mobile ad hoc networks (MANETs). This has been accomplished as follows: (i) The well-known mesh-based on-demand multicast routing protocol (ODMRP) is modified to choose routes based on two different route selection metrics: (a) hop count, as chosen by the Dynamic Source Routing (DSR) protocol and (b) predicted link lifetime, as chosen by the Flow-Oriented Routing Protocol (FORP). The modified ODMRP is referred to as ODMRP_DSR and ODMRP_FORP respectively; (ii) We propose an algorithm called OptMeshTrans to determine the sequence of stable multicast meshes connecting a set of sources to a set of receivers, such that the number of mesh transitions is minimal. Simulation results indicate that the multicast meshes determined using ODMRP_FORP are more stable than those of ODMRP_DSR. There is no appreciable difference between these two ODMRP implementations with respect to hop count per source-receiver path, number of edges and energy consumption per node. The meshes determined using OptMeshTrans are the most stable with relatively fewer edges and incur lower energy consumption per node when compared to the meshes determined using the other two protocols.
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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 | 0.002 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".