Sustainable Cloud-Fog-Edge Systems for Smart Buildings: Algorithmic Adaptation under Memory Constraints and Dynamic Orchestration Strategies

The paper proposes a holistic architectural and algorithmic framework for sustainable cloud‑fog‑edge systems in smart buildings, emphasizing real‑time responsiveness and reduced environmental impact. It validates resilient data acquisition using affordable Arduino hardware and secure persistence solutions, introduces the lightweight KOptim orchestration framework for dynamic SLA management, and adapts the Generalized Hebbian Algorithm for PCA on low‑power microcontrollers with an iterative learning strategy that preserves data diversity. Experimental results on high‑dimensional sensor data demonstrate that this approach converges to quality comparable to full‑memory processing while operating within strict memory constraints.

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• agents
• safety