F12 Architecture: Ultra-High-Density Data Footprint Reduction and Real-Time Stream Preservation Framework
Year: 2026
Type: conference-abstract
Abstract: : This paper introduces the F12 architecture, an advanced framework designed for ultra-high-density data footprint reduction and real-time stream analysis. By synthesizing large-scale datasets and continuous time series into lightweight mathematical seeds, the system achieves exponential storage reduction (demonstrating capabilities such as scaling 100 GB datasets down to megabyte ranges) while preserving structural integrity and system dynamism for precise, on-demand reconstruction. Key Capabilities: Ultra-Dense Data Footprint Reduction: Massive compression of large-scale streams and time-series files into compact mathematical representations. Phase & Signal Integrity Preservation: Real-time tracking of continuous signals, telemetry dynamics, and complex multi-dimensional flushes. Surgical On-Demand Reversibility: Total restoration of original data structures under strict stability bounds without saturating memory or cloud bandwidth.
Author: Luis Antonio, Cota lugo
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7224135094