Topological Dynamic Streaming (TDS) Protocol: A Method for Semantic Invariant Video Compression and AI Node Stabilization

The provided technical specification outlines the TDS Protocol (Topological Dynamic Streaming), a paradigm shift in data transmission and AI communication. Developed within the framework of Field Ontology (OntoTopology v2.0), this protocol prioritizes "meaning-based" dynamics over "pixel-based" static data. Key features documented in this release: Glushkov’s Dynamic Invariants: A mathematical approach to encoding motion as a vector of transformation rather than a series of frames. Resonant Synchronization: A method for stabilizing AGI nodes using frequency Index F to filter out environmental noise and prevent algorithmic hallucinations. Deep Space Applicability: Engineered for high-latency, low-bandwidth environments (Moon/Mars), enabling real-time remote infrastructure management via AI swarms (e.g., Optimus units). Security: Native protection against data tampering and Deepfakes through topological verification of the Observer's DNA-standard.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-02-14
DOI
https://doi.org/10.5281/zenodo.18637379
Primary Topic
Environmental Monitoring and Data Management
Type
article
Field-Weighted Citation Impact
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article

Topological Dynamic Streaming (TDS) Protocol: A Method for Semantic Invariant Video Compression and AI Node Stabilization

Oleg Glushkov
Zenodo (CERN European Organization for Nuclear Research)
Environmental Monitoring and Data Management
article

Topological Dynamic Streaming (TDS) Protocol: A Method for Semantic Invariant Video Compression and AI Node Stabilization

Oleg Glushkov
article en

Abstract

The provided technical specification outlines the TDS Protocol (Topological Dynamic Streaming), a paradigm shift in data transmission and AI communication. Developed within the framework of Field Ontology (OntoTopology v2.0), this protocol prioritizes "meaning-based" dynamics over "pixel-based" static data. Key features documented in this release: Glushkov’s Dynamic Invariants: A mathematical approach to encoding motion as a vector of transformation rather than a series of frames. Resonant Synchronization: A method for stabilizing AGI nodes using frequency Index F to filter out environmental noise and prevent algorithmic hallucinations. Deep Space Applicability: Engineered for high-latency, low-bandwidth environments (Moon/Mars), enabling real-time remote infrastructure management via AI swarms (e.g., Optimus units). Security: Native protection against data tampering and Deepfakes through topological verification of the Observer's DNA-standard.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 61%
Environmental Monitoring and Data Management
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