Service Coordination in the Space-Air-Ground Integrated Network
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
The space-air-ground integrated network (SAGIN) is regarded as a promising approach for providing ubiquitous Internet access anytime and anywhere. With virtualization technologies and multi-access edge computing, data transmission and data processing in SAGINs are abstracted as services. Space-air-ground service computing flexibly integrates and manages these services in SAGINs based on service-oriented architecture. However, it is significant but very challenging to provide Internet of Things service with high QoS in space-air-ground service computing due to the distributed service management, and the mobility of both infrastructures and users. Therefore, in this article, we investigate service coordination to guarantee the QoS in space-air-ground service computing. In particular, we first introduce three service coordination scenarios: fine-grained, medium-grained, and coarse-grained service coordination. Then we design a service coordination framework that contains three tiers: edge node tier, service function routing tier, and global control tier. After that, we propose a service coordination approach to reduce the service delay at low cost, which considers the selection with foresight and updates based on threshold. Experimental results show the advantages of our service coordination approach in terms of service delay and cost.
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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 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it