On Optimal Placement of Hybrid Service Function Chains (SFCs) of Virtual Machines and Containers in a Generic Edge-Cloud Continuum

TL;DR

This paper presents an optimization framework for the strategic placement of hybrid service function chains using VMs and containers across edge and cloud environments, balancing costs and SLA constraints.

Contribution

It introduces a novel mixed-integer linear programming model and heuristic for optimal hybrid SFC placement considering costs, delays, and migration effects.

Findings

Hybrid placement reduces operational costs in edge-cloud networks.

The model effectively balances SLA adherence and cost efficiency.

Migration strategies impact overall network performance.

Abstract

Traditionally, Network Function Virtualization (NFV) has been implemented to run on Virtual Machines (VMs) in form of Virtual Network Functions (VNFs). More recently, the so-called Serverless Computing has gained traction in cloud computing, offering Function-as-a-Service (FaaS) platforms that make use of containerization techniques to deploy services. In contrast to VM-based VNFs, where resources are usually reserved and continuously running, FaaS can just be subsets of code implementing small functions allowing for event-driven, on-demand instantiations. Thus, a hybrid VM-Container based Service Function Chains (SFCs) are a natural evolution of NFV architecture. We study a novel problem of optimal placement of hybrid SFCs from an Internet Service Provider (ISP) point of view, whereby VNFs can be instantiated either over VMs or containers in a generic edge and cloud continuum. To this end, we propose a Mixed-Integer Linear Programming model as well as a heuristic solution to solve this optimization problem that considers three objectives unique to the specific VM and container deployment in a carrier network: operational costs for maintaining servers in the edge, costs of placing VNFs in third-party cloud providers and penalty costs applied when SLA agreements are violated in terms of end-to-end delay. We also propose 2-phases optimization process to analyze the effect on performance as a result of replications and migrations of VNFs. The model can be used to highlight scenarios where a combination of VMs and containers can provide most benefits from the monetary costs point of view.