Hust Media System Overview

Introduction & Core Concepts

Hust Media System Overview is a Distributed Data Middleware designed to standardize automated workflows and validate data quality through a Compute Credits mechanism. The system operates on a high-performance Client-Server model, distinctly separating the API Gateway, Core Services, Data Pipeline, and Verification Engine to maintain stable Real-time Latency for large-scale processing.

Core flow:

  • Data Ingestion → Execution → Validation → Credit Allocation → Resource Balancing
  • Microservices organized by functional business logic.
  • Hybrid Delivery: React for real-time dashboards, Next.js for SEO/SSR documentation.

System Design Goals

  • Scalability: Horizontal scaling via load offloading; vertical scaling via RAM/GPU expansion.
  • Low Latency: Two-tier caching strategy (client store + SSR/SSG cache), optimized queries, and strict timeout management.
  • Data Integrity: Audit chain based on aliases/hashed links to trace data lineage.
  • Threat Intelligence: Anomaly detection module + AI pipeline for data sanitization.
  • Operational Efficiency: Automated updates via Git, supporting on-premise + hybrid cloud deployment.

Architecture Overview

Logical Topology

Client (Web/App)
  -> API Gateway (Nginx / Go / Node)
    -> Core Services (PHP / Go / Python)
      -> Data Stores (MariaDB / MongoDB)
        -> Integrations (MQTT, Cloudflare, Provider APIs)

Data Pipeline

  • Ingestion: collect tasks, evidence, and status logs.
  • Normalization: normalize JSON and identify by alias.
  • Verification: reconcile via third-party APIs + image/video checks.
  • Settlement: allocate credits, exchange services, update status.

Technology Stack

| Layer | Technology | Role | | --- | --- | --- | | Frontend | React / Next.js | Real-time dashboards + SEO/SSR public pages. | | Mobile | React Native + WebView | Native shell with fast web logic updates. | | Backend | Node.js / PHP / Go / Python | REST APIs, job queues, automation, AI utilities. | | Storage | MariaDB / MongoDB | Structured + semi-structured data. | | Infra | Nginx + Cloudflare Tunnel | Gateway, reverse proxy, IP masking. |

Hybrid Frontend Strategy

React SPA handles real-time interactions (dashboards, tasks), while Next.js serves entry pages that require SEO/SSR. Both share a data contract to prevent behavioral drift.

render(view) -> state.sync(...) -> ui.update(...)

MQTT/WebSocket keeps the real-time pipeline consistent between React and Next.

Core Modules

Module A — Community Growth

Facilitates organic interactions (Follow / Like / View) via Smart Matching.

Workflow:

  • Campaign Optimization: Breaks outreach goals into small interaction steps.
  • Relevant Matching: Pairs content with trusted users by reputation scores.
  • Authentic Interaction: Users engage naturally and confirm activity.
  • Quality Assurance: Verifies results through a transparent dual-check system.
  • Reward Allocation: Updates progress and distributes community credits.

Module B — Rating with Evidence

Module B boosts rating/vote with evidence. Execution time is cleaned using IQR Filtering to remove outliers.

q1 = percentile(sorted_data, 25)
q3 = percentile(sorted_data, 75)
iqr = q3 - q1
lower = q1 - 1.0 * iqr
upper = q3 + 1.0 * iqr
filtered = [x for x in sorted_data if lower <= x <= upper]
avg = sum(filtered) / len(filtered)

Module C — Security & Trust Assurance

Module C ensures Community Safety via data verification and feedback:

  • Data Standardization: Formats diverse inputs (contacts, links, social profiles) for accuracy.
  • Instant Query: Rapidly retrieves status via optimized MongoDB indexes.
  • Transparent History: Provides comprehensive safety records from MariaDB.
  • AI-Powered Moderation: Validates new reports with a dual-layer AI review system before publishing.

Reward Engine

Reward Points are an internal currency:

  • Users complete tasks and receive credits.
  • Credits fund new tasks to create a self-sustaining loop.
  • Alias/shortlinks are used to audit the full task chain.

API & Data Contract

Mission Creation (P2P)

POST https://domain/api/v3
{
  "action": "add",
  "comments": ["comment_1", "comment_2"],
  "key": "{API_KEY}",
  "link": "{target_link}",
  "quantity": 1000,
  "service": "{service_id}"
}

Response

{ "order": 98412 }

Security & Privacy

  • API Key authenticates requests with rate limiting.
  • Cloudflare Tunnel masks origin IPs to reduce DDoS risk.
  • Database Hardening: change default ports, limit privileges, scheduled backups.
c.Header("Access-Control-Allow-Origin", "*")
c.Header("Access-Control-Allow-Methods", "GET, POST, OPTIONS")
c.Header("Access-Control-Allow-Credentials", "true")

ingress:
  - hostname: ws.hust.media
    service: http://localhost:8793
  - hostname: nginx.hust.media
    service: http://localhost:8794
  - service: http_status:404

Deployment & Operations

  • On-prem servers for core services, hybrid networking via Cloudflare.
  • Auto-restart sequence: Nginx → Golang → Workers.
  • Git Auto-Update for fast sync and reduced downtime.

Observability & Reliability

  • Background QA Jobs review backlog tasks.
  • Audit Trail tracks full task status and activity history.
  • Alerting via Telegram + system dashboards.

Performance Benchmarks

  • Local API hop: 0.01-0.05 ms internal.
  • Timeout Guardrail: auto-cancel tasks > 180s to avoid overload.
  • Cache Strategy: client store + SSR cache reduce repeated queries.
  • Hybrid Routing: fast SSR entry points with smooth real-time interactions.