Node Architecture
Zusama’s decentralized AI infrastructure is designed to redefine how social behavioral data is collected, processed, and utilized through an integrated network of intelligent nodes.
1. Architecture Overview
Zusama’s architecture consists of three primary computational layers:
Node Layer – Responsible for data sourcing, validation, and pre-processing.
Data Ledger Layer – Handles proof of contribution, record integrity, and reward distribution on-chain.
Federated Learning Layer – Performs distributed AI training without centralizing raw data.
These layers interact harmoniously to form an autonomous intelligence loop, where data and computation flow seamlessly between contributors and the AI engine.
2. Node Architecture
Each Zusama Node acts as a decentralized micro-server within the network. Users can deploy nodes on browsers, personal devices, or VPS servers to contribute computing power and social data insights.
2.1 Node Roles
Browser Node
Lightweight node embedded in user’s browser extension.
Captures anonymized interaction metrics, webpage behaviors, and session contexts.
VPS Node
Full-scale compute node deployed on private or rented infrastructure.
Performs intensive data structuring, feature extraction, and local model updates.
Partner Node
Enterprise-level nodes hosted by institutional partners.
Provides high-bandwidth data aggregation and serves as regional training hubs.
2.2 Data Processing Pipeline
Zusama Nodes operate through a secure data lifecycle pipeline comprising the following stages:
Data Acquisition – The node collects anonymized user interaction signals (e.g., engagement metrics, content patterns, and semantic context).
Feature Extraction – The data is processed locally using lightweight ML modules that extract high-value features while discarding personal identifiers.
Data Normalization & Vectorization – Structured into a consistent feature vector format for federated aggregation.
Encrypted Transmission – Transmits only statistical model updates (not raw data) to the Zusama network via encrypted P2P channels.
Through this pipeline, Zusama ensures no raw personal or private content ever leaves the user’s environment — maintaining GDPR-grade privacy compliance.
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