A new architecture to support efficient web browsing in a wireless mobile computing environment
Bibliographic record
Abstract
Mobile computing environments present several challenges arising from the limitations inherent in wireless networks and the inability of current network protocols to cope with these limitations. As the popularity of untethered access to the Internet increases, conventional network applications such as web browsing must overcome these challenges to support the needs of mobile users. Recent work in the mobile computing research community has attempted to increase the efficiency of web browsing in a mobile computing environment by employing a client/intercept/server architecture which enables the optimization of application layer data transmitted across the wireless portion of the network. Although effective, this strategy relies on the existence of a wired side agent, which introduces a new problem with respect to mobility across different heterogeneous networks where the agent may or may not be available). This thesis presents a new architecture to support the optimization of web browsing in a wireless mobile computing environment. The architecture uses mobile agents to dynamically deploy a client/intercept/server architecture on foreign networks that provide a certain mobility framework. The new architecture offers the following specific advantages: (1) A framework is identified that enables mobile units to discover and use mobile agent systems on foreign networks; (2) The benefits of a client/intercept/server architecture are translated to any network that supports this framework; (3) The architecture works with existing Internet protocols; (4) Mobile agent systems on foreign networks are modeled as a service that the foreign network provides, similar to other services such as printers. Finally, a prototype system is described that is implemented using the architecture to demonstrate the feasibility of the approach.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".