Statistical Multiplexing and Traffic Shaping Games for Network Slicing
Jiaxiao Zheng, Pablo Caballero, Gustavo de Veciana, Seung Jun Baek,, Albert Banchs

TL;DR
This paper analyzes a dynamic resource sharing policy for network slicing in wireless networks, demonstrating its performance benefits, dimensioning strategies, and game-theoretic user management, supported by simulations.
Contribution
It introduces and characterizes the Share Constrained Proportionally Fair (SCPF) policy, providing performance analysis, robust dimensioning solutions, and a traffic shaping game framework.
Findings
SCPF outperforms static slicing, especially with imbalanced or orthogonal loads.
A feasible share allocation exists under certain load and performance conditions.
High load equilibrium and gains are explicitly characterized.
Abstract
Next generation wireless architectures are expected to enable slices of shared wireless infrastructure which are customized to specific mobile operators/services. Given infrastructure costs and the stochastic nature of mobile services' spatial loads, it is highly desirable to achieve efficient statistical multiplexing amongst such slices. We study a simple dynamic resource sharing policy which allocates a 'share' of a pool of (distributed) resources to each slice-Share Constrained Proportionally Fair (SCPF). We give a characterization of SCPF's performance gains over static slicing and general processor sharing. We show that higher gains are obtained when a slice's spatial load is more 'imbalanced' than, and/or 'orthogonal' to, the aggregate network load, and that the overall gain across slices is positive. We then address the associated dimensioning problem. Under SCPF, traditional…
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Taxonomy
TopicsNetwork Traffic and Congestion Control · Wireless Networks and Protocols · Optimization and Search Problems
See pages 1-last of extended-paper.pdf
