Accelerating the Development of Software-Defined Network Optimization Applications Using SOL

TL;DR

This paper introduces SOL, a framework that simplifies the development of SDN optimization applications by using a high-level path-based abstraction to generate efficient, near-optimal solutions, reducing manual effort and expertise needed.

Contribution

The paper presents SOL, a novel framework that unifies SDN optimization problems into a path-based abstraction, enabling efficient and scalable solution generation.

Findings

SOL simplifies SDN application development.

SOL achieves comparable or better scalability than custom solutions.

SOL can prototype diverse and new SDN applications.

Abstract

Software-defined networking (SDN) can enable diverse network management applications such as traffic engineering, service chaining, network function outsourcing, and topology reconfiguration. Realizing the benefits of SDN for these applications, however, entails addressing complex network optimizations that are central to these problems. Unfortunately, such optimization problems require significant manual effort and expertise to express and non-trivial computation and/or carefully crafted heuristics to solve. Our vision is to simplify the deployment of SDN applications using general high-level abstractions for capturing optimization requirements from which we can efficiently generate optimal solutions. To this end, we present SOL, a framework that demonstrates that it is indeed possible to simultaneously achieve generality and efficiency. The insight underlying SOL is that SDN applications can be recast within a unifying path-based optimization abstraction, from which it efficiently generates near-optimal solutions, and device configurations to implement those solutions. We illustrate the generality of SOL by prototyping diverse and new applications. We show that SOL simplifies the development of SDN-based network optimization applications and provides comparable or better scalability than custom optimization solutions.