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Genetic algorithm-based content distribution strategy for F-RAN architectures

  • Li, Xujie (College of Computer and Information, Hohai University) ;
  • Wang, Ziya (College of Computer and Information, Hohai University) ;
  • Sun, Ying (College of Computer and Information, Hohai University) ;
  • Zhou, Siyuan (College of Computer and Information, Hohai University) ;
  • Xu, Yanli (Department of Information Engineering, Shanghai Maritime University) ;
  • Tan, Guoping (College of Computer and Information, Hohai University)
  • Received : 2018.05.10
  • Accepted : 2018.10.08
  • Published : 2019.06.03

Abstract

Fog radio access network (F-RAN) architectures provide markedly improved performance compared to conventional approaches. In this paper, an efficient genetic algorithm-based content distribution scheme is proposed that improves the throughput and reduces the transmission delay of a F-RAN. First, an F-RAN system model is presented that includes a certain number of randomly distributed fog access points (F-APs) that cache popular content from cloud and other sources. Second, the problem of efficient content distribution in F-RANs is described. Third, the details of the proposed optimal genetic algorithm-based content distribution scheme are presented. Finally, simulation results are presented that show the performance of the proposed algorithm rapidly approaches the optimal throughput. When compared with the performance of existing random and exhaustive algorithms, that of the proposed method is demonstrably superior.

Acknowledgement

Supported by : Central Universities, National Natural Science Foundation of China

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