A clustering algorithm that maximizes throughput in 5G heterogeneous F-RAN networks

Date

2018-07-27

Author

Balevi, Eren
Gitlin, Richard D.

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© 2018 IEEE.In this paper, a clustering algorithm is proposed that dynamically determines the locations of fog nodes in 5G wireless networks, which are upgraded from small cells, in order to maximize throughput assuming the number of fog nodes and small cells are given as a priori information. The proposed algorithm dynamically clusters the small cells around the fog nodes. The approach is based on a soft clustering model where one small cell can be connected to many fog nodes. The numerical results demonstrate that the proposed clustering algorithm significantly enhances the throughput and lowers the latency with respect to the distance-based K- means hard clustering algorithm or Voronoi tessellation model.

Subject Keywords

Clustering, Fog computing, HetNets

URI

https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85051445028&origin=inward
https://hdl.handle.net/11511/100203

DOI

https://doi.org/10.1109/icc.2018.8422151

Conference Name

2018 IEEE International Conference on Communications, ICC 2018

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

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Citation Formats

E. Balevi and R. D. Gitlin, “A clustering algorithm that maximizes throughput in 5G heterogeneous F-RAN networks,” Missouri, Amerika Birleşik Devletleri, 2018, vol. 2018-May, Accessed: 00, 2022. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85051445028&origin=inward.