All related repositories are also available at: https://github.com/topics/tin2017-88547-p
software & tools | open science & research experiments | datasets
Software & tools
YAFS: Yet Another Fog Simulator
https://github.com/acsicuib/YAFS
Related paper: https://doi.org/10.1109/ACCESS.2019.2927895 YAFS: A simulator for IoT scenarios in fog computing. IEEE Access. YAFS user guide (v1) (slides)
A Platform for Lightweight Deployment of IoT Applications Based on a Function-as-a-Service Model
https://github.com/acsicuib/IoT-Apps-Deployer
Related paper: https://doi.org/10.1109/TLA.2019.8931204
MARIO: a new fully decentralised and declarative approach for Managing Applications Running In Opportunistic Fog scenarios
https://github.com/acsicuib/MARIO
Related papers: https://doi.org/10.1007/s10723-021-09582-y
https://doi.org/10.1002/smr.2405
Open science & research experiments
Data and source code repositories for the reproducibility and the replicability of the results of the project
Paper: Comparing centrality indices for network usage optimization of data placement policies in fog devices (https://doi.org/10.1109/FMEC.2018.8364053) Source code & data: https://github.com/acsicuib/YAFS/tree/master/src/examples/FogCentrality/ Paper: Multi-objective Optimization for Virtual Machine Allocation and Replica Placement in Virtualized Hadoop (https://doi.org/10.1109/TPDS.2018.2837743) Source code & data: https://github.com/acsicuib/NSGA2VmHdfs/ Paper: A Lightweight Decentralized Service Placement Policy for Performance Optimization in Fog Computing (https://doi.org/10.1007/s12652-018-0914-0) Source code & data: https://github.com/carlosguerrero/iFogSimPopularityPlacement Paper: Availability-aware Service Placement Policy in Fog Computing Based on Graph Partitions (https://doi.org/10.1109/JIOT.2018.2889511) Source code & data: https://github.com/acsicuib/FogServicePlacement-ILPvsCN Paper: Evaluation and efficiency comparison of evolutionary algorithms for service placement optimization in fog architectures (https://doi.org/10.1016/j.future.2019.02.056) Source code & data: https://github.com/acsicuib/GA4FogPlacement Paper: Analyzing the Applicability of a Multi-Criteria Decision Method in Fog Computing Placement Problem (https://doi.org/10.1109/FMEC.2019.8795361) Source code & data: https://github.com/acsicuib/YAFS/tree/master/src/examples/MCDA/ Paper: Meet Genetic Algorithms in Monte Carlo: Optimised Placement of Multi-Service Applications in the Fog (https://doi.org/10.1109/EDGE.2019.00016) Source code & data: https://github.com/di-unipi-socc/FogTorchPI/tree/genetic-algs Paper: Towards Declarative Decentralised Application Management in the Fog (https://doi.org/10.1109/ISSREW51248.2020.00077) Source code & data: https://github.com/acsicuib/MARIO/tree/gauss2020/ Paper: Osmotic management of distributed complex systems: A declarative decentralised approach (https://doi.org/10.1002/smr.2405) Source code & data: https://github.com/acsicuib/MARIO/tree/SI-SoSs Paper: Declarative Application Management in the Fog (https://doi.org/10.1007/s10723-021-09582-y) Source code & data: https://github.com/acsicuib/MARIO/tree/MarioII Paper: Optimization Policy for File Replica Placement in Fog Domains (https://doi.org/10.1002/cpe.5343) Source code & data: https://github.com/acsicuib/CNDataPlacement
Datasets
Mobility model created for the users of the Wi-Fi of the University of the Balearic Islands
https://github.com/acsicuib/mobility-analysis-corporate-wifi Dataset created in the experimentation of https://doi.org/10.1016/j.jksuci.2022.03.014