The growing complexity and advanced performance requirements of Internet applications coupled with the diversity of today's technologies and devices have rendered network management an expensive and time-consuming task. In this talk, I will describe solutions to facilitate network management in two different types of networks: Home and small office networks, and Internet Service Provider networks.
n the first part of the talk, I will present HomeMaestro, a distributed system for the monitoring and instrumentation of home networks. HomeMaestro performs extensive measurements at the host level to infer application network requirements, and automatically identifies network related problems through time-series analysis. By sharing and correlating information across hosts in the home network, our system automatically detects and resolves contention over network resources based on predefined policies.
In the second part of the talk, I will present a fundamentally different approach to Internet traffic classification, one of the most important network management problems for ISPs. In contrast to previous methods, our approach is based on observing and identifying patterns of host behavior at the transport layer. Our approach operates in the dark, having (a) no access to packet payload, (b) no knowledge of port numbers and (c) no additional information other than what current flow collectors provide. These restrictions respect privacy, technological and practical constraints.
Thomas Karagiannis is researcher with the Systems and Networking group of Microsoft Research Cambridge, UK since 2006. He received his Ph.D. degree in Computer Science from the University of California, Riverside and B.S at the Applied Informatics department of the University of Macedonia, in Thessaloniki, Greece. Before joining Microsoft, he has also been with Intel Research and the Cooperative Association for Internet Data Analysis (CAIDA) at the University of California, San Diego. His research interests include Internet measurements and modelling, network architectures, analysis and characterization of the traffic of Internet applications, peer-to-peer and online social networks.