Energy efficiency in access and aggregation networks: From current traffic to potential savings

Abstract

Access and aggregation networks account nowadays for a large share of the consumed energy in communication networks, and actions to ameliorate their energy cost are under investigation by the research community. In this work, we present a study of the possible savings that could be achieved if such technologies were in place. We take advantage of large datasets of measurements collected from the network of FASTWEB, a national-wide Internet Service Provider in Italy. We first perform a detailed characterization of the energy consumption of Points of Presence (PoPs) investigating on how factors such as external temperature, cooling technology and traffic load influence the consumed energy. Our measurements precisely quantify how the power consumption in today networks is practically independent from the traffic volume, while it is correlated only with the external temperature. We then narrow down our analysis to consider the traffic generated by each household. More specifically, by observing about 10,000 ADSL customers, we characterize the typical traffic patterns generated by users who access the Internet.Using the available real data, we thus investigate if the energy consumption can be significantly reduced by applying simple energy-efficient policies that are currently under studies. We investigate energy-to-traffic proportional and resource consolidation technologies for the PoP, while sleep modes policies are considered at the ADSL lines. All these energy-efficient policies, even if they are not yet available, are currently being widely investigated by both manufacturers and researchers. At the PoP level, our dataset shows that it would be possible to save up to 50% of energy, and that even simple mechanisms would easily allow to save 30% of energy. Considering the ADSL lines, it results that sleep mode policies can be effectively implemented, reducing the energy consumption of ADSL modems with little or marginal impact on the Quality of Service offered to users. We make available all datasets used in this paper to allow other researchers to benchmark their proposals considering actual traffic traces.