Abstract-Reduction of unnecessary energy consumption is becoming a major concern in wired networking, because of the potential economical benefits and of its expected environmental impact. These issues, usually referred to as "green networking", relate to embedding energy-awareness in the design, in the devices and in the protocols of networks.In this work, we first formulate a more precise definition of the "green" attribute. We furthermore identify a few paradigms that are the key enablers of energy-aware networking research. We then overview the current state of the art and provide a taxonomy of the relevant work, with a special focus on wired networking. At a high level, we identify four branches of green networking research that stem from different observations on the root causes of energy waste, namely (i) Adaptive Link Rate, (ii) Interface proxying, (iii) Energy-aware infrastructures and (iv) Energy-aware applications. In this work, we do not only explore specific proposals pertaining to each of the above branches, but also offer a perspective for research.
Network monitoring has always played a key role in understanding telecommunication networks since the pioneering time of the Internet. Today, monitoring traffic has become a key element to characterize network usage and users' activities, to understand how complex applications work, to identify anomalous or malicious behaviors. In this paper, we present our experience in engineering and deploying Tstat, a free open source passive monitoring tool that has been developed in the past ten years. Started as a scalable tool to continuously monitor packets that flow on a link, Tstat has evolved into a complex application that gives to network researchers and operators the possibility to derive extended and complex measurements via advanced traffic classifiers. After discussing Tstat capabilities and internal design, we present some examples of measurements collected deploying Tstat at the edge of several ISP networks in the past years. We then discuss the scalability issues that software based tools have to cope with when deployed in real networks, showing the importance of properly identifying bottlenecks.
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