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 article 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. Taking all these constraints into account leads to an integer programming problem with many nonlinear constraints. These constraints are first relaxed to get an integer linear programming formulation of the slice resource provisioning problem. This problem is then solved considering the slice resource provisioning demands jointly. A suboptimal approach is finally proposed where slice resource provisioning demands are considered sequentially. Both solutions are compared to provisioning schemes that do not account for best-effort services sharing the common infrastructure network, as well as uncertainties in the slice resource demands.

中文翻译：

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用于网络切片的不确定性资源配置

网络切片允许移动网络运营商将物理基础架构拆分为隔离的虚拟网络（片），由服务提供商进行管理以适应定制服务。属于片的服务功能链（SFC）通常是在尽力而为的前提下部署的：没有任何保证可以保证网络基础结构资源足以支持不同数量的用户，每个用户的需求都不确定。从网络基础结构提供程序（InP）的角度出发，本文提出了一种用于切片的资源供应方法，该方法对于随机使用切片资源的部分未知数量的用户具有鲁棒性。供应方案旨在最大程度地提高InP的总收入，同时提供概率保证，所供应的网络资源量将满足分片要求。此外，执行提议的配置方法是为了限制其对低优先级后台服务的影响，该服务可能与基础结构网络中的分片共存。考虑所有这些约束会导致带有许多非线性约束的整数编程问题。首先放宽这些约束，以获取切片资源供应问题的整数线性规划公式。然后共同考虑片资源配置需求来解决该问题。最终提出了一种次优方法，其中顺序考虑切片资源的配置需求。两种解决方案都与不考虑共享通用基础结构网络的尽力而为服务以及配额资源需求的不确定性的配置方案进行了比较。执行建议的配置方法是为了限制其对低优先级后台服务的影响，该服务可能与基础结构网络中的分片并存。考虑所有这些约束会导致具有许多非线性约束的整数编程问题。首先放宽这些约束，以获取切片资源供应问题的整数线性规划公式。然后共同考虑片资源配置需求来解决该问题。最终提出了一种次优的方法，其中顺序考虑切片资源的配置需求。将这两种解决方案与不考虑共享公用基础结构网络的尽力而为服务以及配额资源需求的不确定性的配置方案进行了比较。执行建议的配置方法是为了限制其对低优先级后台服务的影响，该服务可能与基础结构网络中的分片并存。考虑所有这些约束会导致具有许多非线性约束的整数编程问题。首先放宽这些约束，以获取切片资源供应问题的整数线性规划公式。然后共同考虑片资源配置需求来解决该问题。最终提出了一种次优方法，其中顺序考虑切片资源的配置需求。两种解决方案都与不考虑共享通用基础结构网络的尽力而为服务以及配额资源需求的不确定性的配置方案进行了比较。