Predictive scheduling of network processors

Abstract

To provide flexibility in deploying new protocols and services, general-purpose processing engines are being placed in the datapath of routers. Such network processors (NPs) are typically simple RISC multiprocessors that perform forwarding and custom application processing of packets. The inherent unpredictability of execution time of arbitrary instruction code poses a significant challenge in providing service guarantees for data flows that compete for such processing resources in the network. However, we show that network processing workloads are highly regular and predictable, which can be exploited for scheduling purposes. We present two such predictive processor scheduling algorithms that aim at providing service guarantees as well as improving the performance of the NP by increasing the instruction data locality. Simulation results show that these algorithms provide significantly better performance than processor scheduling algorithms that do not take packet processing times into consideration.