Synthetic Task-VM Dataset for Fog Computing Load Balancing Experiments

A synthetic dataset generated by CloudSim 6.0 for evaluating a hybrid Bacterial Colony Optimization and Particle Swarm Optimization load balancing algorithm. The dataset contains task-VM pairs with size ranges from 100 to 10,000 tasks and a Poisson distribution of task arrivals. It was created by Aryan Kumar and last updated on 2026-05-08.

Use Cases

• Benchmarking metaheuristic load balancing algorithms based on the described task-VM pairs.
• Simulating fog computing scheduling scenarios based on the synthetic workload data.
• Evaluating VM utilization and makespan reduction based on the described high-load test cases.
• Comparing hybrid optimization techniques like BCO-PSO against standard algorithms based on the experimental setup.

Strengths

• Dataset size is precisely 5.5 KB, indicating a compact and focused scope.
• Explicitly describes test scenarios with 5000 and 10000 tasks, providing concrete scale examples.
• Includes specific performance results, such as a 35.79% makespan reduction for 10000 tasks compared to AIW-PSO.

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

Synthetically generated using CloudSim 6.0 simulation software.

Time Range

Experimental timeframe not specified.

Freshness

Last updated 2026-05-08 17:30:57; freshness should be verified.

Geography

Not applicable; synthetic data.