iFogSimPopularityPlacement

Mobility analysis in a corporate WiFi with data mining.

Genetic algorithms for the placement of services in Fog domains

These are the implementations of two service placement algorithms for fog computing in python 2.7. One is an ILP-based algorithm and the second one is based on the use of complex networks and graph partitions.

NSGA-II implemetation for the elaboration included the research paper entitled "Multi-objective Optimization for Virtual Machine Allocation and Replica Placement in Virtualized Hadoop Architecture"

Managing Applications Running In Opportunistic Fog Scenarios (MARIO)

Distributed GA implementation based on a publish/subscriber pattern

Optimization for HDFS placement and MapReduce schedulling using NSGA-II Genetic Algorithms

Multi-objective application placement in fog computing using graph neural network-based reinforcement learning

Yet Another Fog Simulator (YAFS)