Performance of publish/subscribe middleware in mobile wireless networks
Bibliographic record
Abstract
Publish/subscribe middlewares are becoming popular for distributed applications because of their flexible and scalable nature. Anonymous and loosely-coupled communication between publisher and subscriber, along with the inherently asynchronous nature of these systems, help them adapt quickly to changing environments, making them a good choice for mobile cellular networks. This paper studies publish/subscribe middleware performance in such networks in detail. As a first step, the paper characterizes a popular implementation of publish/subscribe system for the mobile domain, studying and analyzing the effect of different mobility parameters, which to the best of our knowledge is the first experimental research on the performance behavior of publish/subscribe systems in a mobile wireless domain. As a second step the paper presents the design, implementation and evaluation of middleware level handoffs, a well known solution to extend publish/subscribe systems to a mobile domain, and identifies the performance concerns of such extensions. The results show that such handoff protocols involving two brokers are impractical from a performance perspective under highly dynamic and unreliable mobile wireless settings. The paper identifies the basic reason for the limitations of middleware level handoffs.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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".