Aether NPP 6DOF movement showcase
2K video showcase of Aether NPP
Hey everyone! I’m a solo developer working on modular C++ systems for Unreal Engine 5. I wanted to share a technical breakdown and stress-test data for Aether, a 6DOF movement framework built on UE5’s Network Prediction Plugin (NPP).
And yes the video is raw,unedited footage of me just messing around with the physics trying to force the network to collapse! (12min & 19seconds for the video)
Aether Key Specs & Metrics
Engine Version: UE 5.7.4 (NPP)
Performance: 16–30 µs CPU time (vector math simulation)
Payload: 1.58 KB InputCMD
Tick Rate: 60 Hz Dedicated Server (16.67 ms frame budget)
Max Speed Tested: 55,000 cm/s
Network Stress Test Results
| Scenario | 1-Way Latency / RTT | Packet Loss / Jitter / Reorder | Client Visual Experience | Network Prediction & Buffer Behavior |
|---|---|---|---|---|
| Ideal | 0 ms / 0 ms | 0% / 0 ms / 0% | Baseline Flawless | 0 Restore Events / 0 Hard Rollbacks |
|---|---|---|---|---|
| GoodBroadband | 20 ms / 40 ms | 0% / 2 ms / 0% | Imperceptible from Ideal | Zero network desync |
| BadWiFi | 40 ms / 80 ms | 8% / 20 ms / 3% | Imperceptible from Ideal | Zero network desync |
| HighPing | 180 ms / 360 ms | 0% / 10 ms / 0% | Imperceptible from Ideal | Local prediction handles input latency cleanly |
| SevereJitter | 80 ms / 160 ms | 2% / 60 ms / 10% | Imperceptible from Ideal | Jitter absorbed by prediction buffer |
| PacketLossSpike | 50 ms / 100 ms | 15% / 10 ms / 0% | Imperceptible from Ideal | Zero visual stuttering |
| AetherStable | 300 ms / 600 ms | 15% / 80 ms / 1% | Imperceptible from Ideal | Full 600 ms RTT absorbed with 0 hard rollbacks |
| AetherUnstable | 600 ms / 1200 ms | 25% / 100 ms / 3% | Visually Smooth | Minor RESTORE EVENTS triggered; no client snaps |
| AetherExtreme | 1200 ms / 2400 ms | 35% / 200 ms / 5% | Visually Smooth | Velocity-compensated SmoothingTranslationOffset dikes out historical adjustments |
| JustNo | 3000 ms / 6000 ms | 70% / 300 ms / 10% | Playable (micro-stutters); increasing reconciliation thresholds trades sim accuracy for visual smoothness | Heavy Input Starvation & frequent resimulations; input lag noticeable |
Other Modules in Development
Nexus: Data-driven UI manager (SDL3 integration) with custom input processor and axis editor for HOTAS/HOSAS setups even crasy sim setups!
Flux: Bitmask-based grid shapes for infinite nested inventories, reflection stat handlers, and a custom GAS implementation.
Kinetix: Dynamic destruction & bullet manager utilizing vector math, physical penetration, and Geometry Scripting.
Happy to answer any technical questions about NPP, vector math optimization, or the overall C++ architecture!
I Promise I don’t bite! 