Journal
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
Volume 37, Issue 8, Pages 1794-1807Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSAC.2019.2927100
Keywords
Generalized Kelly mechanism; resource allocation; wireless network virtualization; wireless network slicing
Funding
- National Research Foundation of Korea (NRF) - Korean Government (MSIT) [NRF-2017R1A2A2A05000995]
- National Research Foundation of Korea [21A20131612192] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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Wireless network slicing (i.e., network virtualization) is one of the potential technologies for addressing the issue of rapidly growing demand in mobile data services related to 5G cellular networks. It logically decouples the current cellular networks into two entities: infrastructure providers (InPs) and mobile virtual network operators (MVNOs). The resources of base stations (e.g., resource blocks, transmission power, and antennas), which are owned by the InP, are shared with multiple MVNOs who need resources for their mobile users. Specifically, the physical resources of an InP are abstracted into multiple isolated network slices, which are then allocated to MVNO's mobile users. In this paper, two-level allocation problem in network slicing is examined while enabling efficient resource utilization, inter-slice isolation (i.e., no interference among slices), and intra-slice isolation (i.e., no interference between users in the same slice). A generalized Kelly mechanism (GKM) is also designed, based on which the upper level of the resource allocation issue (i.e., between the InP and MVNOs) is addressed. The benefit of using such a resource bidding and allocation framework is that the seller (InP) does not need to know the true valuation of the bidders (MVNOs). For solving the lower level of resource allocation issue (i.e., between MVNOs and their mobile users), the optimal resource allocation is derived from each MVNO to its mobile users by using Karush-Kuhn-Tucker (KKT) conditions. Then, bandwidth resources are allocated to the users of MVNOs. Finally, the results of the simulation are presented to verify the theoretical analysis of our proposed two-level resource allocation problem in wireless network slicing.
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