Energy-Constrained Task Assignment and Resource Allocation – Optimization Simulation Dataset
- Citation Author(s):
-
Ling Guangsen
- Submitted by:
- Guangsen Ling
- Last updated:
- DOI:
- 10.21227/kca1-pj51
- Data Format:
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- Categories:
- Keywords:
Abstract
This dataset supports the numerical experiments conducted in the paper "Optimization of Energy-Constrained Computing Task Assignment and Resource Allocation Problem." It provides simulation data for the optimization of energy-constrained computing task assignment and resource allocation in end-edge-cloud collaborative systems.
Each dataset instance is generated using random sampling within predefined parameter ranges, covering diverse system configurations and scales. Specifically, the number of edge servers varies from 20 to 100, and the number of computing tasks ranges from 40 to 1000, enabling the modeling and analysis of typical scenarios in energy-aware collaborative computing environments.
Instructions:
Each instance is stored as a plain text file with the following structure:
- Line 1–3:
- Line 1: Instance ID
- Line 2: Number of edge servers
- Line 3: Number of computing tasks
- Line 4–10: Parameter arrays :
- Line 4: Computing resource capacity of each edge server (GHz)
- Line 5: VM deployment latency for each server (seconds)
- Line 6: Data size of each task (MB)
- Line 7: Computation amount of each task (Megacycles)
- Line 8: Transmission distance of each task (meters)
- Line 9: Channel gain from each device to its corresponding edge server
- Line 10: Transmission power of each task (mW)
