  Fog computing is a promising paradigm for real-time and mission-critical
Internet of Things (IoT) applications. Regarding the high distribution,
heterogeneity, and limitation of fog resources, applications should be placed
in a distributed manner to fully utilize these resources. In this paper, we
propose a linear formulation for assuring the different availability
requirements of application services while maximizing the utilization of fog
resources. We also compare three multiobjective evolutionary algorithms, namely
MOPSO, NSGA-II, and MOEA/D for a trade-off between the mentioned optimization
goals. The evaluation results in the iFogSim simulator demonstrate the
efficiency of all three algorithms and a generally better behavior of MOPSO
algorithm in terms of obtained objective values, application deadline
satisfaction, and execution time.
