HotCocoa: Hardware Congestion Control Abstractions - Arashloo, Mina Tahmasbi; Ghobadi, Manya; Rexford, Jennifer; Walker, David (HotNets-XVI Proceedings of the 16th ACM Workshop on Hot Topics in Networks, 2017)
Congestion control in multi-tenant data centers is an active area of research because of its significant impact on customer experience, and, consequently, on revenue. Therefore, new algorithms and protocols are expected to emerge as the Cloud evolves. Deploying new congestion control algorithms in the end host’s hypervisor allows frequent updates, but processing packets at high rates in the hypervisor and implementing the elements of a congestion control algorithm, such as traffic shapers and timestamps, in software have well-studied inaccuracies and CPU inefficiencies. In this paper, we argue for implementing the entire congestion control algorithm in programmable NICs. To do so, we identify the absence of hardware-aware programming abstractions as the most immediate challenge and solve it using a simple high-level domain specific language called HotCocoa. HotCocoa lies at a sweet spot between the ability to express a broad set of congestion control algorithms and efficient hardware implementation. It offers a set of hardware-aware COngestion COntrol Abstractions that enable operators to specify their algorithm without having to worry about low-level hardware primitives. To evaluate HotCocoa, we implement four congestion control algorithms (Reno, DCTCP, PCC, and TIMELY) and use simulations to show that HotCocoa’s implementation of Reno perfectly tracks the behavior of a native implementation in C++.