Xwapseries.lat - Vaishnavy And Sharun Raj P15 H...

| Component | Specification | |-----------|----------------| | Client Devices | 3 × Google Pixel 7 (Android 13), 2 × Samsung Galaxy S24 (Android 13) | | Edge Server | Intel Xeon Silver 4310, 32 GB DDR5, 10 GbE NIC | | Back‑haul | 1 Gbps fiber (simulated jitter 5–30 ms) | | Wi‑Fi | 802.11ax (6 GHz) APs, 4×4 MIMO, 2 GHz channel, configurable load | | Traffic Generator | Custom XWap‑Lat client, generating mixed traffic: 1080p 60 fps AR video (≈ 8 Mbps), 2 Mbps control telemetry, 0.5 Mbps background sync. | | Measurement Tools | Wireshark, tcpdump, Android Profiler, PowerMeter (Monsoon), custom latency predictor (Python‑Cython). |

Statistical significance evaluated with paired t‑tests (α = 0.01). XWapseries.Lat - Vaishnavy And Sharun Raj P15 H...

| Scenario | Description | |----------|-------------| | S1 – Baseline | Standard QUIC over Wi‑Fi, no adaptation. | | S2 – XWap‑Lat (Static) | XWap‑Lat enabled with fixed deadlines (50 ms). | | S3 – XWap‑Lat (P15 H) | Full adaptive pipeline (ARMAX + Edge Offload + Adaptive Redundancy). | | S4 – Stress | Introduce artificial AP load (75 % utilisation) and burst packet loss (2 % every 30 s). | | S5 – Mobility | Client walks at 1.5 m/s across two AP coverage zones. | | Scenario | Description | |----------|-------------| | S1

Each scenario ran for 30 minutes, repeated five times, with random seed variation for stochastic components. repeated five times

XWapseries.Lat seeks to pre‑empt latency degradation by: