Energy efficient routers are important and promising devices in the roadmap toward green networking. In this paper, we explore this topic with a traffic aware design that can automatically adapt the router's energy consumption to the network traffic in real time with transitions at the scale from microseconds to nanoseconds. In this paper, we make three contributions. First, we propose an energy efficient router architecture using frequency scaling, which is extended from the contemporary line card architecture of the router. Second, we prototype our architecture on a gigabit NetFPGA platform, which extends a router design on that platform to dynamically work at six frequencies. Then, we discuss the implementation in detail and present a per-packet-based power consumption model from real-world measurements. Third, we further propose four algorithms, which efficiently and automatically adapt power grades under the methodology of periodical and threshold-based scaling. Our experiments are carried out on two platforms, a NetFPGA prototype for feasible scenarios and a simulator for other scenarios in excess of the NetFPGA port limit with parameters synthetically generated to the real-world measurement. Experimental results show that approximately 25% power can be saved with our architecture and algorithms. Conclusions are also given to summarize our findings.

Energy efficient router is one of the most important and promising devices in the roadmap towards green communication and networking. In recent years, automatical power scaling adapting with real-time network traffic in a router has been proved to be practical on real hardware, which is an implementation under the traffic aware philosophy. In this paper, we further explore this direction, and present four real-time power scaling algorithms for the fine-grained energy management within a router. These algorithms are all based on the traffic aware philosophy. We first classify the traffic characteristics into three categories of the core router, access router and home router and analyze the differences among them. Then, we propose two design methodologies, periodical scaling and threshold scaling, and address four algorithms in details. Finally, we use real network traffic to evaluate these algorithms and draw the conclusions. The experiments on real traffic show that more than 40\% of the energy in a router can be saved by using proposed system-level power scaling methods. Based on those evaluations, we also find that three status modes with two working frequencies and a sleep in a router are enough to achieve near-optimal energy efficiency by using our algorithms, which indicates an easy and practical hardware modification.

Energy efficient routers (EERs) are promising devices to achieve green communications for ISP to save energy and cost. However, deploying this kind of routers may introduce severe accumulated packet delay, especially for high-end optical routers. In this paper, we present three contributions to solve the above issue with dynamically balancing QoS and the energy consumption, while preserve the real deployment simple and flexible. First, we propose a QoS aware power scaling algorithm for single self-motivated EER. Second, we present a QoS aware open-loop deployment method by using a short-term traffic forecast model. This model can assist EERs to adapt their capacities with the information of the incoming network traffic along the traffic path. Third, we propose a QoS aware feedback deployment method for better energy efficiency by building local control systems between two adjacent EER pairs. We evaluate the above algorithms by performing simulations. The results show that our methods are energy efficieny while controlling the packet delay.