Fair resource allocation algorithms (MLF-DRS, FFMRA, H-FFFMRA): The output and source codes for the experiments

Hamzeh, Hamed (2021) Fair resource allocation algorithms (MLF-DRS, FFMRA, H-FFFMRA): The output and source codes for the experiments.

In this thesis, we have used randomly generated workloads to evaluate the performance of proposed fair resource allocation algorithms (MLF-DRS, FFMRA, H-FFFMRA). The produced workloads have been directly fed into the simulation environment, considering different metrics such as resource allocation, utilization, and fairness. A sample CSV file has been provided that illustrates how the raw data generated by the mathematical models look (workload_0). This is a sample generated workload based on a single task with various resource demands in time-series experiments. The generated workload is used to determine allocation with respect to other tasks, submitted to the system.