4.7 Article

Network Slicing for Guaranteed Rate Services: Admission Control and Resource Allocation Games

Journal

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
Volume 17, Issue 10, Pages 6419-6432

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TWC.2018.2859918

Keywords

Wireless networks; network slicing; multi-tenant networks; resource allocation; guaranteed rate servi.e.; inelastic traffic

Funding

  1. H2020 5G-MoNArch Project [761445]
  2. 5GCity Project of the Spanish Ministry of Economy and Competitiveness [TEC2016-76795-C6-3-R]
  3. H2020 5G-Transformer Project [761536]

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Technologies that enable network slicing are expected to be a key component of next generation mobile networks. Their promise lies in enabling tenants (such as mobile operators and/or services) to reap the cost and performance benefits of sharing resources while retaining the ability to customize their own allocations. When employing dynamic sharing mechanisms, tenants may exhibit strategic behavior, optimizing their choices in response to those of other tenants. This paper analyzes dynamic sharing in network slicing when tenants support inelastic users with minimum rate requirements. We propose a NEtwork Slicing (NES) framework combining: 1) admission control; 2) resource allocation; and 3) user dropping. We model the network slicing system with admitted users as a NES game; this is a new class of game where the inelastic nature of the traffic may lead to dropping users whose requirements cannot be met. We show that, as long as admission control guarantees that slices can satisfy the rate requirements of all their users, this game possesses a Nash equilibrium. Admission control policies (a conservative and an aggressive one) are considered, along with a resource allocation scheme and a user dropping algorithm, geared at maintaining the system in Nash equilibria. We analyze our NES framework's performance in equilibrium, showing that it achieves the same or better utility than static resource partitioning, and bound the difference between NES and the socially optimal performance. Simulation results confirm the effectiveness of the proposed approach.

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