Publications
Improved scalability of demand-aware datacenter topologies with minimal route lengths and congestion
| Author | Pacut, Maciej; Dai, Wenkai; Labbe, Alexandre; Foerster, Klaus-T.; Schmid, Stefan |
|---|---|
| Date | 2021 |
| Type | Journal Article |
| Abstract | The performance of more and more cloud-based applications critically depends on the performance of the interconnecting datacenter network. Emerging reconfigurable datacenter networks have the potential to provide an unprecedented throughput by dynamically reconfiguring their topology in a demand-aware manner. This paper studies the algorithmic problem of how to design low-degree and hence scalable datacenter networks that are optimized toward the current traffic they serve. Our main contribution is a novel network design which provides asymptotically minimal route lengths and congestion. In comparison to prior work, our design reduces the degree requirements by a factor of four for sparse demand matrices. We further show that the problem is already NP-hard for tree-shaped demands, but permits a 2-approximation on the route lengths and a 6-approximation for congestion. We further report on a small empirical study on Facebook traces. |
| Url | https://publica.fraunhofer.de/handle/publica/271200 |
