State-of-the-art Framework 🏗 for Cloud Computing ⛅️ Simulation: a modern, full-featured, easier-to-use, highly extensible 🧩, faster 🚀 and more accurate ☕️ Java 17+ tool for cloud computing research 🎓. Examples: https://github.com/cloudsimplus/cloudsimplus-examples

Implementation of RL in the cloud for energy minimization due to migration and excess power consumption.

The results of the simulation show that the Genetic algorithm performs well compared to First Come First Serve Algorithm, Round Robin Algorithm, and Shortest Job First algorithm.

EDoS-ADS: An Enhanced Mitigation Technique Against Economic Denial of Sustainability (EDoS) Attacks

CloudSim is primarily a simulation framework for modeling and simulating cloud computing infrastructures and services. While CloudSim itself does not include built-in machine learning capabilities, you can integrate machine learning techniques into CloudSim to optimize various aspects of cloud resource management.

Task scheduling using Weighted Active Monitoring Load Distribution technique.

Integrating machine learning techniques into CloudSim can significantly optimize various aspects of cloud resource management. CloudSim is a popular simulation tool for modeling and experimenting with cloud computing environments and services.

This project simulates scheduling in a cloud computing environment using CloudSim. Multiple scheduling algorithms are implemented, allowing for flexibility in assigning tasks (cloudlets) to virtual machines (VMs).

Cloudsim simulation java implementation

CloudOrg Simulator is a Cloud Simulation and analysis Project built using CloudSim Plus Library and Scala 3.0.2 This project is also designed to be a primitive CloudSimulation Framework.

placement by learning automata

Simulation of Modified SJF Scheduling Algorithm using CloudSim based on evaluating the Avg response time and makespan in comparison to FCFS and SJF Scheduling