Table 2.
Key parameters of the simulation environment for training and testing the delay shift agent.
| Parameter | Value |
|---|---|
| Number of IoT devices | 1250 (50 per each of the 25 edge nodes) |
| Task arrival rate | 10–20 tasks per minute (Poisson distribution with ±10% fluctuations) |
| Number of edge nodes | 25 |
| Node CPU frequency | 2–3 GHz |
| Node RAM | up to 8 GB |
| Node power consumption | up to 30 W, 180 Wh (power budget) |
| Fog latency | 250 ms |
| Network topology | BA graph (attachment parameter m = 2) |
| Channel bandwidth | 1–20 Mbps |
| Channel latency | 10–150 ms |
| Simulation step/episode duration | 1 s/200 steps |
| Random number generator | fixed seed (seed = 42) |
| Input datasets | Orange D4D, Intel Lab Sensor Data |
| Programming language | Python 3.10 |
| Libraries used | TensorFlow 2.11, NumPy 1.24 |
| Hardware platform | AMD Ryzen 7 5800X, 64 GB RAM |