Abstract-The rapidly increasing energy consumption by computing and communications equipment is a significant economic and environmental problem that needs to be addressed. Ethernet network interface controllers (NICs) in the US alone consume hundreds of millions of US dollars in electricity per year. Most Ethernet links are underutilized and link energy consumption can be reduced by operating at a lower data rate. In this paper, we investigate Adaptive Link Rate (ALR) as a means of reducing the energy consumption of a typical Ethernet link by adaptively varying the link data rate in response to utilization. Policies to determine when to change the link data rate are studied. Simple policies that use output buffer queue length thresholds and fine-grain utilization monitoring are shown to be effective. A Markov model of a state-dependent service rate queue with rate transitions only at service completion is used to evaluate the performance of ALR with respect to the mean packet delay, the time spent in an energy-saving low link data rate, and the oscillation of link data rates. Simulation experiments using actual and synthetic traffic traces show that an Ethernet link with ALR can operate at a lower data rate for over 80 percent of the time, yielding significant energy savings with only a very small increase in packet delay.

The IT equipment comprising the Internet in the USA uses about $6 billion of electricity every year. Much of this electricity use is wasted on idle, but fully powered-up, desktop PCs and network links. We show how to recover a large portion of the wasted electricity with improved power management methods that are focused on network issues.

Rapidly increasing energy use by computing and communications equipment is a significant problem that needs to be addressed. Ethernet network interface controllers (NICs) consume hundreds of millions of US$ in electricity per year. Most Ethernet links are underutilized and link power consumption can be reduced by operating at lower data rates. An output buffer threshold policy to change link data rate in response to utilization is investigated. Analytical and simulation models are developed to evaluate the performance of Adaptive Link Rate (ALR) with respect to mean packet delay and time spent in low data rate with Poisson traffic and 100 Mb/s network traces as inputs. A Markov model of a state-dependent service rate queue with rate transitions only at service completion is developed. For the traffic traces, it is found that a link can operate at 10 Mb/s for over 99% of the time yielding energy savings with no user-perceivable increase in packet delay.

The Internet and the devices that connect to it consume a growing and significant amount of electricity.The utilization of desktop-to-switch Ethernet links is generally very low and thus there is a potential for energy savings by using an Adaptive Link Rate (ALR) protocol that matches link rate to utilization. In this paper, we design and evaluate a new ALR policy suitable for both bursty and smooth traffic. The policy uses output buffer thresholds and fine-grain utilization monitoring to determine when to switch link data rate. We develop a new traffic model for generating synthetic 1 and 10 Gb/s bursty traffic traces. Using this traffic model and simulation, we show that the new ALR policy is suitable for smooth traffic and also does not degrade performance for bursty traffic. Performance is measured in packet delay versus time in low (and energy saving) data rate.

Storage, memory, processor, and communications bandwidth are all relatively plentiful and inexpensive. However, a growing expense in the operation of computer networks is electricity usage. Estimates place devices connected to the Internet as consuming about 2%, and growing, of the total electricity produced in the USA-much of this power consumption is unnecessary. Power management is needed to reduce this large and growing energy consumption of the Internet. We see power management as the 'next frontier' in research in computer networks. In this paper, we propose methods for reducing energy consumption of networked desktop computers. Using traffic characterization of university dormitory computers, we show that there is significant idle time that can be exploited for power management. However, current Ethernet adapters in desktop computers lack the capabilities needed to allow existing system power management features to be enabled. We address this problem with a proxying Ethernet adapter that handles routine network tasks for a desktop computer when it is in a low-power sleep mode. This proxying adapter can allow existing power management features in desktop computers to remain enabled and have the computer be 'on the network' at all times. The energy that we expect can be saved is in the range of 0.8-2.7 billion US dollars/year. q