Software Defined Networking in Next Generation Mobile Backhauls: A Survey
Bibliographic record
Abstract
Decoupling the control and data planes has become synonymous with Software Defined Networking (SDN). This paradigm introduces a multitude of benefits to modern networks - such include reduction of management complexity and cost, modularity, optimized utilization, and isolated innovation. The strict requirements of next generation mobile networks can be summarized by a set of Key Performance Indicators (KPIs). Peak data rates and network latency KPIs for 5G have driven the need for researchers to turn their focus to the mobile backhaul. This paper identifies the challenges faced by next generation mobile networks and investigates state-of-the-art solutions implementing SDN at the backhaul level. In addition, it presents five distinct categories of SDN-enabled solutions and discusses their effectiveness in meeting such KPIs. Mobility management, joint Radio Access Network (RAN) intelligence, multi-tenancy, caching, and traffic monitoring are areas where SDN could prove to be a powerful technology enabler in backaul networks.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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 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".