# Delay-Aware Flow Migration for Embedded Services in 5G Core Networks

## TL;DR

This paper proposes a delay-aware flow migration strategy for embedded services in 5G core networks, optimizing end-to-end delay while balancing load and minimizing reconfiguration costs under resource constraints.

## Contribution

It formulates a novel non-convex optimization problem for flow migration, transforms it into a tractable MIQCP, and proves the optimality gap is zero, enabling effective solutions.

## Key findings

- Flow migration improves E2E delay guarantees.
- The MIQCP approach achieves optimal solutions.
- Trade-offs between load balancing and reconfiguration overhead are demonstrated.

## Abstract

Service-oriented virtual network deployment is based on statistical resource demands of different services, while data traffic from each service fluctuates over time. In this paper, a delay-aware flow migration problem for embedded services is studied to meet end-to-end (E2E) delay requirement with time-varying traffic. A non-convex multi-objective mixed integer optimization problem is formulated, addressing the trade-off between maximum load balancing and minimum reconfiguration overhead due to flow migrations, under processing and transmission resource constraints and QoS requirement constraints. Since the original problem is non-solvable in optimization solvers due to unsupported types of quadratic constraints, it is transformed to a tractable mixed integer quadratically constrained programming (MIQCP) problem. The optimality gap between the two problems is proved to be zero, so we can obtain the optimum of the original problem through solving the MIQCP problem with some post-processing. Numerical results are presented to demonstrate the aforementioned trade-off, as well as the benefit from flow migration in terms of E2E delay performance guarantee.