Multi-Tier IoT Resource Allocation Dataset

This dataset captures real-time resource allocation and workload distribution across a multi-tier IoT computing architecture (Device, Edge, Fog, and Cloud). It is designed to support research in ultra-low latency service management, predictive analytics, and intelligent resource allocation for jitter-sensitive IoT applications.

The dataset includes key metrics such as CPU utilization, memory usage, network latency, jitter, task execution time, and predicted vs. actual resource allocation. Additionally, an Efficiency Score serves as the target variable, representing the effectiveness of resource allocation.

This dataset is ideal for machine learning, optimization, and performance evaluation in intelligent IoT networks.

Use Cases:Machine Learning & Predictive Analytics: Train models to optimize IoT resource allocation.

Network Performance Analysis: Study latency, jitter, and execution efficiency.

Edge & Cloud Computing Optimization: Evaluate workload distribution strategies.