An Infrastructure as a Service for the Internet of Things
Bibliographic record
Abstract
Internet of Things (IoT) enables a plethora of applications. However provisioning these applications in a cost-efficient manner, as well as decoupling the applications from the underlying IoT devices remains a challenge that cloud computing may aid in tackling. This paper proposes an architecture for an IoT Infrastructure as a Service (IaaS) to address these issues. Like any other cloud IaaS, the proposed IaaS relies on virtualization to realize cost efficiency. The high-level Application Programming Interfaces (APIs) that enable IoT cloud consumers (e.g. IoT PaaS) to use the virtualized resources are described, as well as the lower level APIs that make possible the management of the actual pool of IoT physical resources. The subjacent functional entities (e.g. orchestrator, publisher, repository access engine, physical and virtual sensor repositories) are introduced, as well as the related interfaces. A proof of concept prototype is built and performance measurements are made. Advanticsys and Virtenio sensors are used as physical sensors.
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 | 0.000 | 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 | 0.000 |
| 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".