Jellyfish: Networking Data Centers Randomly

TL;DR

Jellyfish introduces a random graph topology for data center networks that supports incremental expansion, improves cost-efficiency, and offers flexible oversubscription, addressing challenges in routing and physical layout.

Contribution

The paper presents Jellyfish, a novel random graph-based network topology that enhances incremental expansion and cost-efficiency in data centers.

Findings

Supports 25% more servers than fat-tree at the same scale

More cost-efficient than traditional fat-tree networks

Flexible in building networks with various oversubscription levels

Abstract

Industry experience indicates that the ability to incrementally expand data centers is essential. However, existing high-bandwidth network designs have rigid structure that interferes with incremental expansion. We present Jellyfish, a high-capacity network interconnect, which, by adopting a random graph topology, yields itself naturally to incremental expansion. Somewhat surprisingly, Jellyfish is more cost-efficient than a fat-tree: A Jellyfish interconnect built using the same equipment as a fat-tree, supports as many as 25% more servers at full capacity at the scale of a few thousand nodes, and this advantage improves with scale. Jellyfish also allows great flexibility in building networks with different degrees of oversubscription. However, Jellyfish's unstructured design brings new challenges in routing, physical layout, and wiring. We describe and evaluate approaches that resolve these challenges effectively, indicating that Jellyfish could be deployed in today's data centers.