A Conflict Analysis Framework for QoS-Aware Routing in Contention-Based Wireless Mesh Networks with Beamforming Antennas
Bibliographic record
Abstract
Utilizing smart beamforming antennas in contention-based wireless mesh networks has proven to provide a significant increase in the network capacity. Nevertheless, their effectiveness in providing additional QoS guarantees is still under-explored. In this paper, we develop a framework for analyzing conflicts on wireless links considering both the physical interference and the operation of the underlying directional MAC protocol. Based on a novel taxonomy, we classify the link conflicts into several categories and propose a novel colored conflict graph abstraction to model the network interference pattern in the presence of contention-based directional MAC protocols. Using the proposed colored conflict graph, we derive a closed form expression for the probability of successful transmission over a wireless link given that all the bandwidth requirements are satisfied. Based on our analysis, we formulate the bandwidth-guaranteed routing problem as an optimization problem. Since the problem is NP-hard, we present a heuristic algorithm for joint routing and admission control to find single-path bandwidth-guaranteed routes. Using extensive simulations, we demonstrate the accuracy of our conflict analysis and the ability of the proposed algorithm to provide QoS guarantees along with efficient channel utilization.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.000 |
| 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".