Design of A QoS-Aware Service Composition and Management System in Peer-to-Peer Network Aided by DEVS
Bibliographic record
Abstract
QoS-aware service management and composition has become an interesting research topic with the rapid development of service oriented architecture (SOA). Differently with Web-services based systems, the emergence of peer-to-peer (P2P) based distributed network technology brings more challenge to the QoS-aware service management and composition. In this paper, we propose our design of a QoS-aware hierarchical service composition and management system in a context of JXTA-enabled P2P network. We conducted a comparison experiment of our design with commonly used flat-based service composition and management, and found that our design outperforms the flat-based one in terms of a higher success rate for satisfying the user's QoS requirement. Furthermore, we used a RT-DEVS model based formal approach to validate our design, and believe that it can be a promising technology in aiding the design of an efficient QoS-aware service composition and management system.
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 | 0.000 | 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".