Uncertainty-Aware Resource Provisioning for Network Slicing

Abstract

Network slicing allows Mobile Network Operators to split the physical infrastructure into isolated virtual networks (slices), managed by Service Providers to accommodate customized services. The Service Function Chains (SFCs) belonging to a slice are usually deployed on a best-effort premise: nothing guarantees that network infrastructure resources will be sufficient to support a varying number of users, each with uncertain requirements.Taking the perspective of a network Infrastructure Provider (InP), this paper proposes a resource provisioning approach for slices, robust to a partly unknown number of users with random usage of the slice resources. The provisioning scheme aims to maximize the total earnings of the InP, while providing a probabilistic guarantee that the amount of provisioned network resources will meet the slice requirements. Moreover, the proposed provisioning approach is performed so as to limit its impact on low-priority background services, which may co-exist with slices in the infrastructure network.A Mixed Integer Linear Programming formulation of the slice resource provisioning problem is proposed. Optimal joint and suboptimal sequential solutions are proposed. These solutions are compared to a provisioning scheme that does not account for best-effort services sharing the common infrastructure network.

Foresighted Resource Provisioning for Network Slicing

“…Infrastructure nodes and links provide a given amount of computing, storage, and possibly wireless resources (a c , a m , a w ), expressed in number of CPUs, Gbytes, and Gbps, depending on the layer they are located. The per-unit resource cost (c n (i), ∀n ∈ Υ and c b (ij)), the node disposal cost c f (i), and the fixed cost c d (i) are set respectively to 1, 50, and 20, In each time slot k, we assume that a random part of the infrastructure resources are partly consumed by besteffort background services, see [5]. The performance of the proposed provisioning variants are evaluated considering different network conditions in terms of resource consumption by background services.…”

“…The constraint (10) is nonlinear due to the need to evaluate p s,k (κ s,k ) using (11). Using the approach introduced in [5], one can replace the SSP constraint (10) by the following linear deterministic constraints, for each slice s,…”

“…R s,n,k (v) and R s,n,k (v) are the mean and standard deviation of R s,n,k (v), while R s,b,k (vw) and R s,b,k (vw) are the mean and standard deviation of R s,b,k (vw). Their evaluation is detailed in [5].…”

“…The aim is to provide a probabilistic guarantee of meeting the slice resource requirements while maximizing the benefits of the InP. This work adapts it to a dynamic context the slice resource provisioning approach introduced in [5]. It provides a provisioning mechanism robust against the dynamic behavior of concurrent slice provisioning requests, each of which has random arrival, activation, and deactivate time.…”

Placement and Allocation of Communications Resources in Slicing-aware Flying Networks

“…However, a fixed network infrastructure is typically assumed. Providing wireless connectivity on-demand for ensuring coverage-aware network slices in dynamic environments has not been addressed so far [21].…”