Network Slicing for Service-Oriented Networks with Flexible Routing and Guaranteed E2E Latency

TL;DR

This paper presents a new mixed binary linear programming model for network slicing in 5G networks, optimizing energy efficiency while ensuring service latency and resource constraints through flexible routing and function placement.

Contribution

It introduces a novel formulation that jointly optimizes resource allocation, function deployment, and routing to guarantee end-to-end latency in service-oriented networks.

Findings

The proposed model outperforms existing approaches in energy efficiency.

Numerical results confirm effective latency and resource management.

Flexible routing enhances network slicing performance.

Abstract

Network function virtualization is a promising technology to simultaneously support multiple services with diverse characteristics and requirements in the fifth generation and beyond networks. In practice, each service consists of a predetermined sequence of functions, called service function chain (SFC), running on a cloud environment. To make different service slices work properly in harmony, it is crucial to select the cloud nodes to deploy the functions in the SFC and flexibly route the flow of the services such that these functions are processed in sequence, the end-to-end (E2E) latency constraints of all services are guaranteed, and all resource constraints are respected. In this paper, we propose a new (mixed binary linear program) formulation of the above network slicing problem that optimizes the system energy efficiency while jointly considers the resource budget, functional instantiation, flow routing, and E2E latency requirement. Numerical results show the advantage of the proposed formulation compared to the existing ones.