NFV and SDN - based Distributed IoT Gateway for Large-Scale Disaster Management
Bibliographic record
Abstract
Large-scale disaster management applications are among the several realistic applications of the IoT. Fire detection and earthquake early warning applications are just two examples. Several IoT devices are used in such applications e.g., sensors and robots. These sensors and robots are usually heterogeneous. Moreover, in disaster scenarios, the existing communication infrastructure may become completely or partially destroyed, leaving mobile ad-hoc networks the only alternative to provide connectivity. Utilizing these applications raises new challenges such as the need for dynamic, flexible, and distributed gateways which can accommodate new applications and new IoT devices. Network Functions Virtualization (NFV) and Software Defined Networking (SDN) are emerging paradigms that can help to overcome these challenges. This paper leverages NFV and SDN to propose an architecture for on-the-fly distributed gateway provisioning in large-scale disaster management. In the proposed architecture, the gateway functions are provisioned as Virtual Network Functions (VNFs) that are chained on-the-fly in the IoT domain using SDN. A prototype is built and the performance results are presented.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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".