Balancing Global and Local Fairness Allocation Model in Heterogeneous Data Center - Network and Parallel Computing (NPC 2017)
Conference Papers Year : 2017

Balancing Global and Local Fairness Allocation Model in Heterogeneous Data Center

Bingyu Zhou
  • Function : Author
Guangjun Qin
  • Function : Author
Limin Xiao
  • Function : Author
  • PersonId : 1006934
Zhisheng Huo
  • Function : Author
Bing Wei
  • Function : Author
Jiulong Chang
  • Function : Author
Nan Zhou
  • Function : Author
  • PersonId : 1027997
Li Ruan
  • Function : Author
Haitao Wang

Abstract

Aiming at the problem that the bandwidth allocation method in heterogeneous data center can’t take into account the global and local fairness, we propose an allocation method called GLA that satisfies fair attributes and can improve the utilization of system resources by nearly 20% when the number of clients are more than six contrasting with the existing methods. The algorithm is also protable and scalable that can adapt to most of systems.
Fichier principal
Vignette du fichier
457609_1_En_15_Chapter.pdf (259.92 Ko) Télécharger le fichier
Origin Files produced by the author(s)
Loading...

Dates and versions

hal-01705453 , version 1 (09-02-2018)

Licence

Identifiers

Cite

Bingyu Zhou, Guangjun Qin, Limin Xiao, Zhisheng Huo, Bing Wei, et al.. Balancing Global and Local Fairness Allocation Model in Heterogeneous Data Center. 14th IFIP International Conference on Network and Parallel Computing (NPC), Oct 2017, Hefei, China. pp.136-139, ⟨10.1007/978-3-319-68210-5_15⟩. ⟨hal-01705453⟩
72 View
88 Download

Altmetric

Share

More