CheetahFlow: Towards Low Latency Software-Defined Network

Software defined networking (SDN), which enables programmability, has the advantage of global visibility and high flexibility. However, when forwarding new flows in SDN, the interaction between the switch and the controller imposes extra latency such as round-trip time and routing path search time. Even though such latency is acceptable for elephant flows since it only takes limited ratio of total transmission time of elephant flows, it is an overkill to pay certain overheads for mice flows due to the their short transmission time. Moreover, the controller is frequently invoked by the mice flows since the number of mice flows accounts for a large portion of the total number of flows. Hence, the frequent controller invocation is mainly responsible for the controller performance degradation, and thus increasing the flow setup latency significantly. To solve this problem, we propose CheetahFlow, a novel scheme to predict frequent communication pairs via support vector machine and proactively setup wildcard rules to reduce flow setup latency. Particularly, in order to avoid congestion along a fixed path, elephant flows are detected and rerouted to the non-congestion path efficiently by applying blocking island paradigm. Extensive experiments show that CheetahFlow prominently reduces latency without any loss of flexibility of SDN.