Bibliographic record
Abstract
Nowadays, new multimedia services have been deployed with stringent requirements for Quality of Service (QoS). The QoS provisioning is faced with the heterogeneity of system components. This thesis presents two research: on architectures for QoS management at the application layer, fulfilled mainly by software components; and on distributed software architectures for routing devices providing desired QoS at the underlying communication layer. At the application layer, the QoS architecture we propose, based on the Quality Driven Delivery (QDD) framework, deals with the increasing amount of QoS information of a distributed system. Based on various QoS information models we define for key actors of a distributed system, a QoS information base is generated using QoS information collecting and analysis tools. To translate QoS information among different components, we propose mechanisms to build QoS mapping rules from statistical data. Experiments demonstrate that efficient QoS decisions can be made effectively regarding the contribution of all system components with the help of the QoS information management system. At the underlying layer, we investigate distributed and scalable software architectures for QoS-enabled devices. Due to the huge volume of traffic to be switched, the traditional software model used for current generation routers, where the control card of the router performs all the processing tasks, is no longer appropriate in the near future. We propose a new scalable and distributed architecture to fully exploit the hardware platforms of the next generation routers, and to improve the quality of routers, particularly with respect to scalability and to a lesser extent to resiliency and availability. Our proposal is a distributed software framework where control tasks are shared among the control and line cards of the router. Specific architectures for routing, signaling protocols and routing table management are developed. We investigate the challenges for such distributed architectures and proposed various solutions to overcome them. Based on a general distributed software framework, an efficient scalable distributed architecture for MPLS/LDP and different scalable distributed schemes for the routing table manager (RTM) are developed. We also evaluate the performance of proposed distributed schemes and discuss where to deploy these architectures depending on the type of routers (i.e., their hardware capacity)
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".