Data-Local Inference Core
GraphSAGE-based Graph Neural Network models DNA sequence interactions locally without data exfiltration.
Edge AI
ZeroCloud-Edge-Mesh
A peer-to-peer state-synchronization prototype for edge-native biological research.
ZeroCloud-Edge-Mesh is a peer-to-peer state-synchronization prototype designed for edge-native biological research. It demonstrates architectural capability beyond standard web applications by combining local inference, deterministic persistence, logical clocks, and a Laravel preprocessing gateway.
Feature Breakdown
The core workflows and architecture highlights demonstrated by this project.
Hardware Optimization
Post-training static quantization with INT8 reduces model footprint by about 75% and stabilizes execution jitter.
Causal Event Ordering
Lamport logical clocks guarantee chronological mesh updates across distributed nodes.
Deterministic Persistence
SQLite with Write-Ahead Logging creates durable audit trails across power cycles and network partitions.
Laravel Preprocessing Gateway
PHP gateway handles initial API routing, FHIR-compatible structures, and mesh gossip triggers.