Designing Optimal Compact Oblivious Routing for Datacenter Networks in Polynomial Time.

Recent datacenter network topologies are shifting towards heterogeneous and structured topologies for high throughput, low cost, and simple manageability. However, they rely on sub-optimal routing approaches that fail to achieve their designed capacity. This paper proposes a process for designing optimal oblivious routing that is programmed compactly on programmable switches. The process consists of three contributions in tandem. We first transform a robust optimization problem for designing oblivious routing into a linear program, which is solvable in polynomial time but cannot scale for datacenter topologies. We then prove that the repeated structures in a datacenter topology lead to a structured optimal solution. We use this insight to formulate a scalable linear program, so an optimal oblivious routing solution is obtained in polynomial time for large-scale topologies. For real-world deployment, the optimal solution is converted into forwarding rules for programmable switches with stringent memory. With this constraint, we utilize the repeated structures in the optimal solution to group the forwarding rules, resulting in compact forwarding rules with a much smaller memory requirement. Extensive evaluations show our process i) obtains optimal solutions faster and more scalable than a state-of-the-art technique and ii) reduces the memory requirement by no less than 90% for most considered topologies.