# Stringer: Balancing Latency and Resource Usage in Service Function Chain Provisioning

arXiv: https://arxiv.org/abs/1604.08618 · HTML: https://mlsanity.com/paper/1604.08618/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Apr 2016.

## Built on by (most cited first, 2 of 2)

- [Low Complexity Adaptive Machine Learning Approaches for End-to-End Latency Prediction](https://mlsanity.com/paper/2301.13536/) (2023)
- [Low Complexity Approaches for End-to-End Latency Prediction](https://mlsanity.com/paper/2302.00004/) (2023)

## Abstract (arXiv)

Network Functions Virtualization, or NFV, enables telecommunications infrastructure providers to replace special-purpose networking equipment with commodity servers running virtualized network functions (VNFs). A service provider utilizing NFV technology faces the SFC provisioning problem of assigning VNF instances to nodes in the physical infrastructure (e.g., a datacenter), and routing Service Function Chains (sequences of functions required by customers, a.k.a. SFCs) in the physical network. In doing so, the provider must balance between various competing goals of performance and resource usage. We present an approach for SFC provisioning, consisting of three elements. The first element is a fast, scalable round-robin heuristic. The second element is a Mixed Integer Programming (MIP) based approach. The third element is a queueing-theoretic model to estimate the average latency associated with any SFC provisioning solution. Combined, these elements create an approach that generates a set of SFC provisioning solutions, reflecting different tradeoffs between resource usage and performance.