Schema–Segment Composition Computing System
A Structure-Defined, Constraint-Conditioned, and Observation-Centric Computational System Architecture Abstract SSCCS (Schema–Segment Composition Computing System) is an observation-driven computing model and infrastructure specification that redefines computation as the traceable projection of immutable Segments within a structured Scheme. While contemporary innovation focuses on material hardware shifts, SSCCS addresses fundamental inefficiencies of the Von Neumann bottleneck at the logical layer. By formalizing computation as the simultaneous resolution of static potential under dynamic constraints rather than a sequence of state mutations, the architecture reframes data movement, concurrency, and verifiability. SSCCS embodies three core principles: Immutability (segments and schemes are immutable once created), Structural Integrity (computations adhere to predefined scheme-segment relationships), and Traceability (every projection is deterministically derived and cryptographically verifiable). Its layered ontology—Segments, Schemes, Fields, Observations, Projections, and Data—ensures that information remains unchanged, operations are transparent, and all outcomes can be audited. Driven by a software‑first philosophy, this architecture ensures deterministic reproducibility by completely decoupling execution logic from mutable state through structural and cryptographic isolation. This open specification, intended for validation across diverse domains, provides a roadmap where logical design dictates physical implementation, spanning from software emulation to hardware‑level support. By integrating intrinsic energy efficiency with high interpretability, SSCCS establishes a foundation for sustainable, accountable computational infrastructures, ultimately transitioning logic into a transparent, verifiable, and accessible Intellectual Public Commons.
Authors
- Taeho Lee
Institutions
- Shree Guru Gobind Singh Tricentenary University (IN)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-02-16
- DOI
- https://doi.org/10.5281/zenodo.18825775
- Primary Topic
- Parallel Computing and Optimization Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00