Energy-Aware Load Balancing for Parallel Packet Processing Engines

In this paper, we consider energy-aware network devices (e.g. routers, switches, etc.) able to trade their energy consumption for packet forwarding performance by means of both low power idle and adaptive rate schemes. We focus on state-of-the-art packet processing engines, which generally represent the most energy-starving components of network devices, and which are often composed of a number of parallel pipelines to "divide and conquer" the incoming traffic load. Our goal is to control both the power configuration of pipelines, and the way to distribute traffic flows among them, in order to optimize the trade-off between energy consumption and network performance indexes. With this aim, we propose and analyze a constrained optimization policy, which try to find the best tradeoff between power consumption and packet latency times. In order to deeply understand the impact of such policy, a number of tests have been performed by using experimental data from SW router architectures and real-world traffic traces.