Symbol Table: Cloud-Edge-End Collaborative Intelligent Caching Simulation Results

A simulation results dataset from a study proposing an intelligent caching method for cloud-edge-end systems. The method uses incremental federated learning to protect privacy and adapt caching strategies to dynamic data. The dataset is 5.5 KB in size, authored by Xiang Huang, and last updated on June 3, 2026.

Use Cases

• Evaluating cache hit rates based on simulated node capabilities and data popularity
• Testing data replacement policies under cache space constraints
• Benchmarking federated learning aggregation performance for dynamic data updates
• Analyzing cache balance metrics in a multi-tier architecture

Strengths

• Dataset is openly licensed under CC-BY-4.0
• File size is precisely 5.5 KB

Limitations

• Row count is unknown, which may limit suitability assessment
• Column-level documentation is absent; field semantics must be inferred after download
• Description metadata is limited; actual data quality requires manual inspection after download

Provenance

Source

figshare

Collection Method

Likely generated from experimental simulations described in the associated study.

Freshness

Last updated 2026-06-03 17:30:10; freshness should be verified