Deterministic State Distribution Across Ephemeral Execution Nodes in Controller-Driven Real-Time Systems

Modern real-time systems exhibit non-deterministic behavior and state divergence due to latency, asynchronous communication, and event-driven architectures that lack guarantees of consistent execution across distributed devices. Traditional systems rely on event semantics, where discrete instructions are transmitted and interpreted independently by receiving nodes. This introduces a fundamental logical gap: the final system state becomes a byproduct of local interpretation, timing, and execution history rather than a centrally defined outcome. In distributed environments, this results in probabilistic drift. Event-based systems are temporally coupled to local clocks and network ordering, leading to cumulative error propagation when events are delayed, dropped, or processed inconsistently. Heterogeneous devices further amplify this issue, as identical events may produce divergent results depending on resource availability, execution timing, or prior state context. As a result, such systems typically achieve only eventual consistency rather than deterministic convergence. This work introduces a controller-driven deterministic model for state distribution across ephemeral execution nodes. Instead of transmitting instructions to be interpreted, the system distributes the complete definition of the desired outcome as a versioned state (Sₙ). Each state represents a full, self-contained snapshot of system intent, eliminating the need for historical reconstruction or local decision-making. Execution nodes are reduced to stateless renderers that conform directly to the authoritative state, ensuring that system behavior is outcome-defined rather than path-dependent. Authority within this model is strictly centralized. A single controller defines all state transitions, and a coordinating server enforces ordering and distributes state across the network. Because each state is atomic and versioned, nodes achieve immediate convergence upon receipt of the latest valid state, regardless of join time, prior connectivity, or missed transitions. Network variability affects only the timing of delivery, not the correctness of execution. The framework further introduces enforcement at the execution boundary through DAIOS (Deterministic AI Operating System) and DECTL (Deterministic Ethics-Constrained Transition Law). DAIOS operates as a kernel-level execution authority, enforcing binary decisions on whether a state may be realized. DECTL defines the formal rule system governing admissible state transitions, including structural validity, ordering constraints, and system-level operational boundaries. Together, these layers ensure that validation occurs prior to execution, preventing inadmissible states from ever reaching hardware. Rejected states result in a no-operation condition, preserving the last valid system state and eliminating undefined behavior. The model is evaluated through SYNKTRON, a working implementation demonstrating deterministic state convergence across heterogeneous devices within a real-time environment. SYNKTRON confirms that hardware variability does not affect outcome consistency, that network jitter impacts only delivery timing rather than execution correctness, and that system operation does not require replay mechanisms, synchronization backlogs, or persistent client logic. Nodes may join, leave, or reconnect at any time and immediately converge to the current authoritative state without historical dependency. This approach establishes a deterministic foundation for real-time system coordination by eliminating probabilistic inference and interpretive execution. By shifting from event-based messaging to authoritative state distribution and enforcing admissibility at the execution boundary, the model guarantees consistent outcomes across distributed systems. It replaces eventual consistency with immediate convergence and transforms execution nodes into ultra-thin, deterministic endpoints. The resulting architecture provides a scalable and reliable framework for environments requiring precise synchronization and outcome fidelity, including immersive systems, distributed device orchestration, and real-time human-interactive environments. By removing ambiguity, replay dependency, and local interpretation, deterministic state distribution defines a new paradigm for real-time system design grounded in centralized authority, atomic state propagation, and binary enforcement of execution.