TY - JOUR
T1 - Wireless Network Slicing
T2 - Generalized Kelly Mechanism-Based Resource Allocation
AU - Tun, Yan Kyaw
AU - Tran, Nguyen H.
AU - Ngo, Duy Trong
AU - Pandey, Shashi Raj
AU - Han, Zhu
AU - Hong, Choong Seon
N1 - Funding Information:
Manuscript received October 10, 2018; revised June 16, 2019; accepted June 29, 2019. Date of publication July 10, 2019; date of current version August 6, 2019. This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean Government (MSIT) under Grant NRF-2017R1A2A2A05000995. (Corresponding author: Choong Seon Hong.) Y. K. Tun, S. R. Pandey, and C. S. Hong are with the Department of Computer Science and Engineering, Kyung Hee University, Yongin 17104, South Korea (e-mail: ykyawtun7@khu.ac.kr; shashiraj@khu.ac.kr; cshong@ khu.ac.kr).
Publisher Copyright:
© 2019 IEEE.
PY - 2019/8
Y1 - 2019/8
N2 - 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.
AB - 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.
KW - Generalized Kelly mechanism
KW - resource allocation
KW - wireless network slicing
KW - wireless network virtualization
UR - http://www.scopus.com/inward/record.url?scp=85069504360&partnerID=8YFLogxK
U2 - 10.1109/JSAC.2019.2927100
DO - 10.1109/JSAC.2019.2927100
M3 - Journal article
AN - SCOPUS:85069504360
SN - 0733-8716
VL - 37
SP - 1794
EP - 1807
JO - IEEE Journal on Selected Areas in Communications
JF - IEEE Journal on Selected Areas in Communications
IS - 8
M1 - 8759030
ER -