A scheme for load balancing in heterogenous distributed hash tables
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Bibliographic record
Abstract
We present a scheme for evenly partitioning the key space in distributed hash tables among the participating nodes. The scheme is based on the multiple random choices paradigm [3, 19], and handles both node joins and leaves. It achieves, with high probability, a ratio of at most 4 between the loads of the most and least burdened nodes, in the face or arbitrary node arrivals and departures. Each join or leave operation incurs message cost that is, with high probability, Oh(log2n), where n is the number of nodes, and causes the relocation of keys from at most one node (for joins) or three nodes (for leaves). A version of our scheme is suitable for heterogeneous systems, where the capacities of nodes to serve keys can vary widely.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 it