arXiv:2607. 11725v1 Announce Type: cross Abstract: Prefabricated prefinished volumetric construction moves most building work into module factories, whose production floor operates as a flexible job shop.
By Ziheng Zhang, Wei Zhang
arXiv:2606. 17266v1 Announce Type: new Abstract: Production planning increasingly has to treat workforce capability as a decision variable: certifications lapse when skills are not maintained, new products require skills the current workforce does not hold, and reskilling competes for the same worker hours needed for production.
By Carlos Eduardo Sanoja
arXiv:2605. 26418v2 Announce Type: replace-cross Abstract: A properly calibrated rule-based autoscaler can beat every one of six mainstream deep reinforcement learning (DRL) algorithms on cost across every workload we test - so when, if ever, does DRL actually help?
By Guilin Zhang, Chuanyi Sun, Kai Zhao, Shahryar Sarkani, John Fossaceca
The study investigates whether learned scoring functions can outperform hand‑tuned heuristics in Kubernetes node‑selection. Two models—a Random Forest on engineered features and a graph neural network on job dependency graphs—were trained on a large production trace; both achieved modest regression gains (R²≈0.042) but lagged behind a simple free‑CPU heuristic in Top‑1 ranking accuracy (65‑66% vs. 74‑84%). The authors attribute this gap to objective mismatch, noting that pointwise regression rather than a ranking‑specific loss likely limits performance.
By Wang Xuying, Zhibek Sarypbekova
arXiv:2608. 19488v1 Announce Type: new Abstract: Production machine learning systems degrade under concept drift, yet practitioners have little principled guidance on when to retrain.
By Sawan Dasari
arXiv:2609.37085v1 Announce Type: cross
Abstract: Data-intensive services in the Computing Continuum must balance analytics quality, resource usage, and cost across heterogeneous nodes with limited a...
By Javier Mateos-Bravo, Sergio Laso, Juan Luis Herrera, Ilir Murturi, Pantelis Frangoudis, Schahram Dustdar