Event Driven Architecture: An Exploratory Study on The Gap between Academia and Industry
Bibliographic record
Abstract
Due to their applicability in different domains, Internet of Things software solutions have gained significant attention in many industries. Suitable architectures are needed in order to satisfy the needs of such applications. Event-Driven Architectures (EDA) ease the exchange of data between IoT devices while making each one of them completely decoupled from the others. EDA has been described in many studies and some industrial solutions are proposed to support such architecture. However, no study has evaluated the gap between the developed theory and the proposed industrial solutions. In this exploratory study, we selected and analyzed three industrial platforms according to what is described in the literature. Our results show that there is a lack of a unified definition of the elements of an EDA in academic studies. We also found that event-based communication is implemented differently in each platform, serving different use cases, which indicates the need to establish a commonly accepted definition and design-methodology for this type of architecture.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".