On-Demand Cooperation Among Multiple Infrastructure Networks for Multi-Tenant Slicing: a Complex Network Perspective
Author(s) -
Wanqing Guan,
Xiangming Wen,
Luhan Wang,
Zhaoming Lu
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2018.2885143
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Network slicing is a promising technology for wireless networks to provide various services using limited resources of infrastructure networks. In order to decrease capital expenditure and operational expenditure, multi-tenant slicing provides resource sharing mechanisms among multiple infrastructure providers (InPs). However, one of the main challenges for cooperation among InPs is to meet the diverse demands of various services considering the different structural characteristics of each InP. In this paper, we investigate on-demand cooperation among multiple infrastructure networks from a perspective of the complex network. Four typical network topologies are used to imitate different practical infrastructure networks. The proposed cooperation strategy contains two stages, the selection of connectors and the creation of interconnections. We adopt the complex network theory to obtain the topological information of infrastructure networks. With the topological information, connectors are selected with selection fitness, and interconnections between connectors are created using the two-sided matching. Finally, extensive simulations are conducted, and the effects of variables in the two stages are analyzed. The simulation results illustrate that the proposed strategy performs better in terms of meeting the demand.
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