Load balancing for parallel forwarding

Workload distribution is. critical to the performance of network processor based, parallel forwarding systems. Scheduling schemes, that operate at the packet level, e.g., round-robin, cannot preserve packet-ordering within individual TCP connections. Moreover, these schemes create duplicate information in processor caches-and therefore are inefficient in resource utilization. Hashing operates at the flow level and is naturally able to maintain per-connection packet ordering; besides, it does, not pollute caches. A pure hash-based system, however, cannot balance processor load in the face of highly skewed flow-size distributions in the Internet; usually, adaptive methods are needed. In this paper, based on measurements of Internet traffic, we examine the sources of load imbalance in hash-based scheduling schemes. We prove that under certain Zipf-like flow-size distributions, hashing alone is not-able to balance workload. We introduce a new metric to quantify. the effects of adaptive,load balancing on overall forwarding performance. To achieve both load balancing and efficient system. resource utilization, we propose a scheduling scheme that classifies Internet flows: into two categories: the aggressive and the normal and applies different scheduling policies to the two classes of flows. Compared with most state-of-the-art parallel forwarding schemes, our Work exploits flow-level Internet traffic characteristics.