The Augmentation-Speed Tradeoff for Consistent Network Updates

TL;DR

This paper introduces a method to accelerate consistent network updates by allowing a small, controlled oversubscription of links, significantly reducing update times while maintaining network properties.

Contribution

It formally analyzes the augmentation-speed tradeoff and presents algorithms that leverage this tradeoff to speed up network updates while preserving key properties.

Findings

Allowing 10% oversubscription reduces update times by over 32% on average.

The tradeoff enables faster updates with minimal practical impact.

Algorithms maintain network consistency during updates.

Abstract

Emerging software-defined networking technologies enable more adaptive communication infrastructures, allowing for quick reactions to changes in networking requirements by exploiting the workload's temporal structure. However, operating networks adaptively is algorithmically challenging, as meeting networks' stringent dependability requirements relies on maintaining basic consistency and performance properties, such as loop freedom and congestion minimization, even during the update process. This paper leverages an augmentation-speed tradeoff to significantly speed up consistent network updates. We show that allowing for a small and short (hence practically tolerable, e.g., using buffering) oversubscription of links allows us to solve many network update instances much faster, as well as to reduce computational complexities (i.e., the running times of the algorithms). We first explore this tradeoff formally, revealing the computational complexity of scheduling updates. We then present and analyze algorithms that maintain logical and performance properties during the update. Using an extensive simulation study, we find that the tradeoff is even more favorable in practice than our analytical bounds suggest. In particular, we find that by allowing just 10% augmentation, update times reduce by more than 32% on average, across a spectrum of real-world networks.