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Methods of Resource Scheduling Based on Optimized Fuzzy Clustering in Fog Computing.
Li, Guangshun; Liu, Yuncui; Wu, Junhua; Lin, Dandan; Zhao, Shuaishuai.
Afiliação
  • Li G; School of Information Science and Engineering, Qufu Normal University, Rizhao 276800, China. Guangshunli@qfnu.edu.cn.
  • Liu Y; School of Information Science and Engineering, Qufu Normal University, Rizhao 276800, China. 15163315741@163.com.
  • Wu J; School of Information Science and Engineering, Qufu Normal University, Rizhao 276800, China. shdwjh@qfnu.edu.cn.
  • Lin D; School of Information Science and Engineering, Qufu Normal University, Rizhao 276800, China. 15725040625@163.com.
  • Zhao S; School of Information Science and Engineering, Qufu Normal University, Rizhao 276800, China. zhaoshuaishuaiys@163.com.
Sensors (Basel) ; 19(9)2019 May 08.
Article em En | MEDLINE | ID: mdl-31071923
ABSTRACT
Cloud computing technology is widely used at present. However, cloud computing servers are far from terminal users, which may lead to high service request delays and low user satisfaction. As a new computing architecture, fog computing is an extension of cloud computing that can effectively solve the aforementioned problems. Resource scheduling is one of the key technologies in fog computing. We propose a resource scheduling method for fog computing in this paper. First, we standardize and normalize the resource attributes. Second, we combine the methods of fuzzy clustering with particle swarm optimization to divide the resources, and the scale of the resource search is reduced. Finally, we propose a new resource scheduling algorithm based on optimized fuzzy clustering. The experimental results show that our method can improve user satisfaction and the efficiency of resource scheduling.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sensors (Basel) Ano de publicação: 2019 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sensors (Basel) Ano de publicação: 2019 Tipo de documento: Article País de afiliação: China