Efficient broadcasting in tactical networks: Forwarding vs. network coding
Bibliographic record
Abstract
Broadcasting (communicating information from one to all or many to all nodes in a network) is an important communication primitive. It is used as a building block in many MANET routing protocols, for example. In addition, broadcasting is a key primitive in tactical networks to support to deliver applications of all-informed voice, group push-to-talk, situational information sharing etc. Supporting one-to-all or all-to-all communication patterns in multihop wireless networks efficiently is therefore important. In this paper, we compare efficient broadcasting protocols based on packet forwarding and based on network-coding. Using a number of network scenarios, we derive lower bounds for the required number of packet retransmissions at the MAC layer to support broadcast with and without applying network coding techniques. We compare these lower bounds with each other, as well as with protocols proposed for each approach. More specifically, we use SMF and PDP as sample forwarding-based broadcast protocols, and a multisource random linear network coding protocol as a representative network coding approach. The results show that network coding has advantages over pure packet forwarding. However, none of the existing solutions comes close to approaching their respective lower bounds, leaving much room for new and improved protocols.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".