期刊
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
卷 97, 期 -, 页码 131-144出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.future.2019.02.056
关键词
Fog computing; Resource management; Evolutionary algorithms; Service placement
资金
- Spanish Government (Agencia Estatal de Investigacion)
- European Commission (Fondo Europeo de Desarrollo Regional) [TIN2017-88547-P MINECO/AEI/FEDER, UE]
This study compares three evolutionary algorithms for the problem of fog service placement: weighted sum genetic algorithm (WSGA), non-dominated sorting genetic algorithm II (NSGA-II), and multiob-jective evolutionary algorithm based on decomposition (MOEA/D). A model for the problem domain (fog architecture and fog applications) and for the optimization (objective functions and solutions) is presented. Our main concerns are related to optimize the network latency, the service spread and the use of the resources. The algorithms are evaluated with a random Barabasi-Albert network topology with 100 devices and with two experiment sizes of 100 and 200 application services. The results showed that NSGA-II obtained the highest optimizations of the objectives and the highest diversity of the solution space. On the contrary, MOEA/D was better to reduce the execution times. The WSGA algorithm did not show any benefit with regard to the other two algorithms. (C) 2019 Elsevier B.V. All rights reserved.
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