ZFFT

Zero-Fail File Transfer (ZFFT): unbreakable live sync for unstable networks—zero corruption, priority lanes, real-time, live updates. Edits flow instantly from track to factory, every byte intact.

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Inspiration

High-stakes environments like Formula 1 racetracks generate critical, constantly evolving data — telemetry, setup sheets, video feeds — that must flow instantly between trackside teams and remote factories. Yet, unstable networks (due to high-speed vehicles, interference, or remote locations) cause dropped packets, corruption, and failed transfers. Traditional file transfer tools crumble under such conditions.

ZFFT (Zero-Fail File Transfer) is inspired by real-world pain points faced by MoneyGram Haas F1 and Mphasis in remote operations: ensuring zero-corruption, live-synced data across unreliable links in racetracks, disaster zones, rural labs, mobile clinics, and media field units.

What it does

ZFFT is a resilient, intelligent file transfer & live-sync system built for unstable networks. Key capabilities:

  • Selective Sync: Specify folders/files to transfer or ignore via config patterns.
  • Priority Lanes: Integer-based priority ranking (1–100) — e.g., live telemetry (P1) over post-session video (P10).
  • Real-Time Console Dashboard:
    • Per-file progress (sent/received/retry)
    • Active queue & in-flight files
    • Network health: bandwidth, latency, fragility index
  • Adaptive Transmission:
    • Dynamically adjusts packet size based on network fragility
    • Controls packet burst rate based on available bandwidth
  • Multi-Layer Integrity:
    • Checksums per packet
    • MD5 per buffer
    • SHA256 per file (pre/post transfer)
    • Auto-reconciliation on mismatch
  • Live File Watching & Sync:
    • Monitors specified paths (e.g., logs/, telemetry/) for changes
    • Instant delta propagation — edits sync in <1s over WebSocket-like streams
  • Zero-Fail Resilience:
    • Offline queuing + auto-resume
    • Graceful handling of: corruption, file deletion mid-transfer, timeouts, packet loss
    • Multi-path fallback (Wi-Fi → LTE → satellite)

How we built it

  • Core Engine: C for low-level packet crafting, fragmentation, and high-performance I/O
  • Smart Layer: Python for:
    • Network analysis & adaptive logic
    • Priority scheduling
    • File system monitoring (inotify/watchdog)
    • Real-time console UI with live graphs
  • Protocol: Custom lightweight protocol over UDP with reliability layer + fallback to QUIC
  • Sync Engine: WebSocket-inspired bidirectional streams for live file updates
  • Config: YAML-based rules for file path, priority, watchlist, etc.

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