A scalable load balancer for forwarding internet traffic

Abstract

Packet scheduling in parallel forwarding systems is a hard problem. Two major goals of a scheduler that distributes incoming packets to multiple forwarding engines are to achieve high system utilization (by balancing the load evenly among the multiple engines) and to maintain packet ordering within individual flows. Additionally, from the viewpoint of the overall performance, the system should exhibit a good cache behavior by preserving temporal locality in the workload of each forwarding engine. In this paper, we show how the burstiness in Internet flows can be exploited to improve the performance of the scheduler. Specifically, TCP flows, which contribute to over 90 percent of the Internet traffic, transmit in bursts with relatively large delays in between. We propose a load balancing scheme based on this insight to achieve the scheduling goals. Our design is verified by simulations driven by real-world traces.