Optimization for HDFS placement and MapReduce schedulling using NSGA-II Genetic Algorithms
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Updated
Jul 11, 2024 - Python
Optimization for HDFS placement and MapReduce schedulling using NSGA-II Genetic Algorithms
Mobility analysis in a corporate WiFi with data mining.
Distributed GA implementation based on a publish/subscriber pattern
Managing Applications Running In Opportunistic Fog Scenarios (MARIO)
Multi-objective application placement in fog computing using graph neural network-based reinforcement learning
iFogSimPopularityPlacement
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"
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.
Yet Another Fog Simulator (YAFS)
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