Data Stream Query Processing on Mobile Devices
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
Nowadays, data management and processing systems exist that handle streaming data. Streaming data is data that is very large and cannot all be stored, and also may only be valid for a certain period of time. In existing stream data managements systems, data streams are transmitted to a server where the management and processing of queries take place, before the results are transmitted on an outbound stream possibly to another mobile device. However, no strategies exist that receive, manage and process stream data directly on a mobile device, without having to rely on the services of a server. This paper proposes an architecture and framework for stream data management and query processing on a mobile device. The architecture only keeps a minimal number of features. All database operations are handled with minimal data storage requirements. It also presents details on an implementation of this framework for a currency conversion application, which demonstrates the utility of our framework. This work will lead to several new directions of research in the area of stream processing on mobile devices.
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.
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 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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