Using SLA Context to Ensure Quality of Service for Composite Services
Bibliographic record
Abstract
As service-orientation is establishing itself as the dominant design and integration paradigm for large heterogeneous and open systems, the lines between wired and wireless consumers and providers begin to blur. Due to the availability of toolkits and standards it is now fairly easy to build nomadic service consumers that provide users transparent access to enterprise services. However, since nomadic consumers are typically characterized by limited computational resources, they are very dependent on reliable service providers. Unlike their more resource rich wired counterparts, that can in case of a provider slowdown or failure simply rebind to an alternative provider, the nomadic consumers lack the bandwidth to execute to do so in sufficient time. This leads to the question of how to ensure QoS for providers of nomadic consumers. Especially for composite services that aggregate other services this is still an open question. This paper presents an approach for ensuring QoS for nomadic applications that consume composite services. Using transparent proxies that are control the access to each service provider the scheduling of requests and therefore the enforcement of QoS becomes possible.
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 | 0.001 |
| 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".