Stream-based macro-programming of Wwreless sensor, actuator network applications with SOSNA
Bibliographic record
Abstract
Wireless sensor, actuator networks distinguish themselves\nfrom wireless sensor networks by the need to coordinate\nactuators’ actions, real-time constraints on communication\nand the frequently feedback-based nature of computation\nperformed in the network. In this paper we propose a func-\ntional macro-programming language, SOSNA, that employs\nthe stream programming paradigm to concisely specify data\ntransformations in the network so that wireless sensor actu-\nator network (WSAN) application developers can focus on\nhigher-level control-oriented problems rather than on design-\ning the way in which communication is organised in the net-\nwork. SOSNA accommodates a broad class of WSAN coor-\ndination models, supports mobility and provides a means of\nemploying feedback for distributed state maintenance. Pro-\ngram execution proceeds in rounds providing real-time guar-\nantees on actuator decision making and synchronisation. In\naddition, static program semantics permit nodes to switch\ntheir radios off to conserve energy.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".