DARD: A Practical Distributed Adaptive Routing Architecture for Datacenter Networks

Datacenter networks typically have multiple paths connecting each host pair to achieve higher bisection bandwidth. However, existing transport and routing protocols have little support for multipath in the scale of a datacenter. We advocate to design practical datacenter architectures for easy operation, i.e., an architecture should be reliable, capable of improving bisection bandwidth, scalable and debugging-friendly. By strictly following these four guidelines, We propose DARD, a Distributed Adaptive Routing architecture for Datacenter networks. DARD allows each end host to reallocate traffic from overloaded paths to underloaded paths without central coordination. We use congestion game theory to show that DARD converges to a Nash equilibrium in finite steps and its gap to the optimal flow allocation is bounded in the order of 1 logL with L being the number of links. We use a testbed implementation and simulations to show that DARD can achieve a close-to-optimal flow allocation with small control overhead in practice.