Federated learning (FL) can achieve secure sharing of data, where all parties participate in model training locally and upload it to the server for aggregation. The data never leaves the parties involved, thus solving the problems of data privacy and data silos. However, FL faces issues such ...
much less attention has been paid to the fairness-aware multi-objective optimization, which is indeed commonly seen in real life, such as fair resource allocation problems and data-driven multi-objective
First Fit Decreasing (FFD) is a fundamental algorithm used in the community for benchmarking VM placement algorithms. FFD sorts the VMs according to their CPU and memory size in descending order, and sequentially places them on the first PM with sufficient resources. MM_MBFD [7] is a two ...