Software defined multihop wireless networks: Promises and challenges
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In multihop wireless networks (MWNs), wireless nodes can communicate with each other through intermediate nodes without the help of any infrastructure. Therefore, wireless nodes are responsible for organizing and configuring the network, and the management of the network is distributed between the nodes. Consequently, it is difficult to overcome the existing challenges such as node mobility and dynamic topology changes, energy constraints, etc. Software defined networking (SDN) is a promising solution, which decouples the control plane and the data plane to overcome the challenges of traditional networks. In the SDN concept, a logically centralized controller makes routing decisions based on the global view of the network and the requirements of applications, and then programs the network. Therefore, it helps to optimize resource allocation and improve the network performance. In this paper, we consider the benefits and the various aspects of applying the SDN concept in MWNs (SDMWN). We first introduce MWNs, existing challenges and the motivation for applying SDN to such networks. Then, after explaining the SDN concept, we review the related work in SDMWN. Finally, we discuss the challenges in applying SDN and future research directions in this area.
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.
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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 it