Bibliographic record
Abstract
Influenced by the availability of powerful portable computers, and the expansion of Internet-based services, consumers demand mobile Internet. This implies supporting user mobility while sustaining network connectivity which in turn requires more sophisticated routing methods than simple static Internet protocol. Routing optimization is critical for the efficiency of mobile Internet as it directly impacts resource utilization in the network. On the other hand, while connected to the Internet, users want to enjoy real-time services. Granting quality of service for real-time multimedia applications is one of the major concerns for Internet Service Providers. In the mobile Internet context, as a result of a signalling conflict, providing quality of service declines in presence of routing optimisation. This conflict must be resolved to achieve efficient resource utilization in the networks and provide quality of service for real-time Internet-based services. This thesis presents a solution for resolving the aforementioned conflict. Initially a set of requirements are established for a new solution. The fundamental idea is developed based on exercising routing optimization according to quality of service requirements and network conditions. A new protocol architecture for Mobile IP (MIP) is built based on a cross-layer design technique. This design implies that a new data flow collects the necessary parameters in the network. This data is passed to a new entity in the network layer of the MIP protocol stack that inter-connects IP, routing, mobility and resource reservation protocols. Based on network conditions and the quality of service requirements the optimal path is selected over which the resources are reserved for the duration of the connection. The new solution named MIP with Routing Optimization and QoS (MIP-ROQS) removes the signalling conflict and furthermore, results in increased network performance. Simulation of this solution demonstrates reduction in application end-to-end delay and delay variation, improved core network by reducing the amount of control traffic and dropped traffic and improved access network by reducing its delay. Moreover, we integrate Multi Protocol Label Switching (MPLS) architecture and MIP-ROQS to take advantage of MPLS labelling mechanism to label the optimal path selected by MIP-ROQS for the duration of a session. This integration makes IP-in-IP tunnelling in data forwarding redundant. MPLS is used to switch packets and label the optimal path over which the resources are reserved. Using this approach, the transmission delay, and packet processing overhead are further reduced.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".