PhD Edge Telemetry Lab & Paper Pipeline MCP

Magnus Cruz & Matheus Torquato — CISUC / DEI, University of Coimbra • Updated: 2026-10-29T11:53:00Z
Manifest: SYNCHRONIZED (13 Campaigns) JSON Snapshot Literature Survey MCP →

1. Edge Node Telemetry Readiness (ubuntu@ubuntu-llm (192.168.0.205)) — Agenda A4 Verification

OUT-OF-BAND WALL POWER (1 Hz)
Tapo P115 @ 192.168.0.200 (1 Hz out-of-band telemetry — ACTIVE: 34 W idle / 151 W load)
IN-BAND CPU PACKAGE TEMPERATURE (1 Hz)
lm-sensors coretemp Package id 0 (1 Hz — ACTIVE: 25.0°C idle / 66.0°C–68.0°C load)
AMBIENT TEMPERATURE & HUMIDITY (BLE)
ambient-logger-ble.service -> /home/ubuntu/ambient_ble.csv (ACTIVE: 22.80°C–23.20°C, 48.0%–49.0% RH)

2. Experiment 1: Rejuvenation Energy Cost & Downtime Calibration (80/80 Cycles = 100%)

Model Intervention Action Action (s) Reload + 1st Infer (s) Total Cycle (s) Action Energy (J) Total Cycle Energy (J) Post-Action Decode Process Verification
qwen2.5:0.5b runner_restart_warm 0.927 s 5.316 s 6.243 s 33.6 J 521.6 J 107.30 tps PID Rotated (5/5)
qwen2.5:0.5b page_cache_drop 0.121 s 3.712 s 3.833 s 10.3 J 366.0 J 107.28 tps Same PID (0/5)
qwen2.5:0.5b runner_restart_cold 0.855 s 6.768 s 7.623 s 45.8 J 580.3 J 106.87 tps PID Rotated (5/5)
qwen2.5:0.5b idle_pause_control 6.885 s 4.588 s 11.473 s 244.8 J 688.4 J 106.02 tps Same PID (0/5)
phi3:mini runner_restart_warm 6.324 s 22.425 s 28.749 s 759.1 J 4007.5 J 23.26 tps PID Rotated (5/5)
phi3:mini page_cache_drop 0.048 s 67.966 s 68.014 s 4.1 J 9181.9 J 21.10 tps Same PID (0/5)
phi3:mini runner_restart_cold 6.888 s 40.052 s 46.940 s 585.5 J 6336.9 J 22.38 tps PID Rotated (5/5)
phi3:mini idle_pause_control 27.107 s 23.218 s 50.326 s 2304.1 J 6794.0 J 22.76 tps Same PID (0/5)
llama3.1:8b runner_restart_warm 3.470 s 47.493 s 50.962 s 294.9 J 6879.9 J 12.26 tps PID Rotated (5/5)
llama3.1:8b page_cache_drop 0.064 s 48.373 s 48.437 s 5.5 J 6539.0 J 12.21 tps Same PID (0/5)
llama3.1:8b runner_restart_cold 4.156 s 74.429 s 78.585 s 353.3 J 10609.0 J 12.16 tps PID Rotated (5/5)
llama3.1:8b idle_pause_control 50.193 s 46.144 s 96.337 s 4266.4 J 13005.4 J 12.16 tps Same PID (0/5)
deepseek-v2:lite runner_restart_warm 2.575 s 20.640 s 23.215 s 218.9 J 3134.1 J 29.02 tps PID Rotated (5/5)
deepseek-v2:lite page_cache_drop 0.171 s 16.009 s 16.181 s 14.6 J 2184.4 J 29.06 tps Same PID (0/5)
deepseek-v2:lite runner_restart_cold 2.342 s 60.800 s 63.141 s 199.0 J 8524.1 J 29.05 tps PID Rotated (5/5)
deepseek-v2:lite idle_pause_control 20.159 s 14.361 s 34.520 s 1713.5 J 4660.2 J 29.44 tps Same PID (0/5)

3. Four-Paper PhD Track Synchronization & Pipeline Status

paper1-iotj \TBD: 0
Sustained LLM Inference on Edge CPU Nodes: Efficiency Envelope and Late-Onset Degradation
SUBMITTED (IEEE IoT-J — ID: 06c45e02-4db2-4e00-ac4f-83074597dc84)
Cites PAPER1: 0 | Cites PAPER3: 0
paper2-aging-position \TBD: 0
Software Aging and Rejuvenation for Large Language Model Inference on IoT and Edge Nodes: A Position and Research Agenda
READY FOR FINAL CONCLUSION & VENUE SELECTION (85%)
Cites PAPER1: 9 | Cites PAPER3: 0
paper3-mechanism \TBD: 23
Locating Late-Onset Decode Degradation in Sustained Edge LLM Inference
DESIGN & PRE-COMMITMENT COMPLETE — MID-RUN CAMPAIGN NEXT (50%)
Cites PAPER1: 7 | Cites PAPER3: 0
paper4-framework \TBD: 19
Energy-Aware Orchestration of Edge LLM Inference
ARCHITECTURE & DECISION PROCEDURE READY — CALIBRATING E_REJUV TODAY (45%)
Cites PAPER1: 5 | Cites PAPER3: 5