The design and implementation of architectural components for the integration of the IP multimedia subsystem and wireless actuator networks
Bibliographic record
Abstract
Wireless actuators are small scale devices that can act on their environment. The IP multimedia subsystem is an architecture with the goal of seamlessly delivering multimedia services. Combining actuation capabilities with the IMS will certainly enable novel value-added services in areas such as environment monitoring, emergency management and home automation. We have previously proposed an architecture for such integration. This architecture relies on two key components: an actuation control function (ACF) that serves as a higher-level actuation control entity, and a wireless actuators/IMS gateway (WAG) dealing with the interworking between actuator networks and the IMS. In this article, we focus on the design and implementation of the ACF and the WAG. Furthermore, a prototype application is implemented to show how new applications can be built using our integrated architecture. Performance has also been evaluated, and several lessons were learned in the course of this work. One lesson is that integrating the IMS with various and evolving actuators is a continuous task. Without standard APIs for the interaction with actuators produced by different vendors, the WAG needs to be constantly upgraded. Another lesson is that while the introduction of actuation as an application building block in the IMS enables fast and easy development of applications with actuation requirements, the lack of mature IMS application development toolkits remains a barrier.
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 | 0.001 | 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 | 0.000 |
| 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".