Performance comparison of architectures for client-server interactions in CORBA
Why this work is in the frame
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Bibliographic record
Abstract
Middleware promotes interoperability as well as provides transparent location of servers in heterogeneous client-server environments. Although a number of benefits are provided by middleware, careful consideration of system architecture is required to achieve high performance. Based on implementation and measurements made on a network of workstations running a commercial CORBA compliant ORB called ORBeline the paper is concerned with the impact of client-agent-server interaction architecture on performance. The paper reports on the relative performances of three interaction architectures under different workload conditions. In particular the impact of inter-node delays, message size, and request service times on the latency and scalability attributes of these architectures is analyzed. A method called agent cloning and how it can be used for improving system performance are described.
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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 it